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Sample records for modeling driver behavior

  1. Modeling taxi driver anticipatory behavior

    NARCIS (Netherlands)

    Zheng, Zhong; Rasouli, S.; Timmermans, H.J.P.

    2018-01-01

    As part of a wider behavioral agent-based model that simulates taxi drivers’ dynamic passenger-finding behavior under uncertainty, we present a model of strategic behavior of taxi drivers in anticipation of substantial time varying demand at locations such as airports and major train stations. The

  2. Driver's Behavior Modeling Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Sehraneh Ghaemi

    2010-01-01

    Full Text Available In this study, we propose a hierarchical fuzzy system for human in a driver-vehicle-environment system to model takeover by different drivers. The driver's behavior is affected by the environment. The climate, road and car conditions are included in fuzzy modeling. For obtaining fuzzy rules, experts' opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. Also the precision, age and driving individuality are used to model the driver's behavior. Three different positions are considered for driving and decision making. A fuzzy model called Model I is presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. Also we obtained two other models based on fuzzy rules called Model II and Model III by using Sugeno fuzzy inference. Model II and Model III have less linguistic terms than Model I for the steering angle and direction of car. The results of three models are compared for a driver who drives based on driving laws.

  3. Theoretical models of drivers behavior on the road

    Directory of Open Access Journals (Sweden)

    Marcin Piotr Biernacki

    2017-06-01

    Full Text Available Understanding of mechanisms and factors responsible for the driver behavior on the road is the subject of ongoing interest to transportation psychologists, occupational doctors and engineers. Models of driver behavior are a key point for the understanding the mechanisms and factors which may cause limitations to the optimal functioning on the road. They also systematize knowledge about the factors responsible for the behavior of the driver and thus constitute a starting point for formulating empirical or diagnostic hypotheses. The aim of this study is to present models of driver behavior from the descriptive and functional perspectives. Med Pr 2017;68(3:401–411

  4. MODELING DRIVER BEHAVIOR IN THE DRIVING OF THEIR MOTOR VEHICLE

    Directory of Open Access Journals (Sweden)

    A. V. Skrypnikov

    2015-01-01

    Full Text Available The article holds the gradual formation of images and actions of the driver. As outlined the author's arguments based on the following assumptions: We consider the motion of the mass, mass-produced currently by the domestic industry of automobiles; considered the motion of single cars as the most common and most dangerous cases, allowing to evaluate the influence of parameters on the road driving mode "pure"; drivers tend to reduce travel times and therefore move with the maximum possible speed; drivers choose speed, visually estimating lying in front of part of the way and given the speed at the time of this evaluation; driver behavior, ceteris paribus determined the influence of visibility limitations and conditions visual perception; considered the motion on the ascent and descent, but the determining factor is the direction of descent. Set of operations, branches off the driver, can be represented as a multi-level system comprising three main groups of psycho-physiological processes, activities analyzers (perception of information; the work of the central nervous system (processing and storage; effective activity (responses to the implementation of the decision. On the basis of the received information in human consciousness formed images of the environment, the totality of which is an information model of the object. Comparing it with the standards (memory engrams, the driver generates the mo st appropriate in the circumstances set of actions. Implementation of the decision is the final stage of human response to the external environment and is expressed in the change of the degree of use of traction engine or braking force; change the steering angle as that does not affect the speed of motion, the algorithm of the driver is not taken into account. Analysis of the schemes of algorithms allows to obtain quantitative characteristics of the vehicle: stereotyped figures, logical complexity.

  5. Driver behavior in traffic.

    Science.gov (United States)

    2012-02-01

    Existing traffic analysis and management tools do not model the ability of drivers to recognize their environment and respond to it with behaviors that vary according to the encountered driving situation. The small body of literature on characterizin...

  6. Modeling and Recognizing Driver Behavior Based on Driving Data: A Survey

    Directory of Open Access Journals (Sweden)

    Wenshuo Wang

    2014-01-01

    Full Text Available In recent years, modeling and recognizing driver behavior have become crucial to understanding intelligence transport systems, human-vehicle systems, and intelligent vehicle systems. A wide range of both mathematical identification methods and modeling methods of driver behavior are presented from the control point of view in this paper based on the driving data, such as the brake/throttle pedal position and the steering wheel angle, among others. Subsequently, the driver’s characteristics derived from the driver model are embedded into the advanced driver assistance systems, and the evaluation and verification of vehicle systems based on the driver model are described.

  7. Modeling and Recognizing Driver Behavior Based on Driving Data: A Survey

    OpenAIRE

    Wang, Wenshuo; Xi, Junqiang; Chen, Huiyan

    2014-01-01

    In recent years, modeling and recognizing driver behavior have become crucial to understanding intelligence transport systems, human-vehicle systems, and intelligent vehicle systems. A wide range of both mathematical identification methods and modeling methods of driver behavior are presented from the control point of view in this paper based on the driving data, such as the brake/throttle pedal position and the steering wheel angle, among others. Subsequently, the driver’s characteristics de...

  8. Regulating Hazardous-materials Transportation with Behavioral Modeling of Drivers

    Science.gov (United States)

    2018-01-29

    Changhyun Kwon (ORCID ID 0000-0001-8455-6396) This project considers network regulation problems to minimize the risk of hazmat accidents and potential damages to the environment, while considering bounded rationality of drivers. We consider governme...

  9. Characteristics of Chinese Driver Behavior

    NARCIS (Netherlands)

    Li, J.

    2014-01-01

    The high growth rate of vehicle ownership and many novel drivers in China determine the special features of Chinese driver behavior. This thesis introduces a comparative study on driver behavior by the analysis of saturation flow at urban intersections, Driver Behavior Questionnaire surveys, focus

  10. A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication.

    Science.gov (United States)

    Yang, Ching-Han; Chang, Chin-Chun; Liang, Deron

    2018-03-28

    All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication-an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment-confirm the feasibility of this approach.

  11. Modeling the Speed Choice Behaviors of Drivers on Mountainous Roads with Complicated Shapes

    Directory of Open Access Journals (Sweden)

    Yiming Shao

    2015-02-01

    Full Text Available Roadway geometric features and pavement conditions can significantly affect driver behavior, particularly with regard to vehicle speed. This paper presents the development of an algorithm for speed selection for use in automated passenger car travel (without driver input on mountainous roads with complicated shapes. The relationship between favorable driving speed and the geometric features of horizontal curves was established on the basis of driving experiments and spot speed observation data, and speed control models were established for driving on curves, curve approaches/departures, and tangents. The models developed can be used to calculate a driver's desired speed on any roadway with a defined geometry. The model considers the driver's behavior type and the vehicle's dynamic properties. This paper presents the results of simulation experiments on roads with small curve radii and narrow widths. The algorithms developed may be used for assisted and automated driving. Under automated driving conditions, speed control and speed change based on the algorithms developed make drivers feel natural as if they drive the car themselves.

  12. Modeling Crossing Behavior of Drivers at Unsignalized Intersections with Consideration of Risk Perception

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    Liu Miaomiao

    2016-01-01

    Full Text Available Drivers’ risk perception is vital to driving behavior and traffic safety. In the dynamic interaction of a driver-vehicle-environment system, drivers’ risk perception changes dynamically. This study focused on drivers’ risk perception at unsignalized intersections in China and analyzed drivers’ crossing behavior. Based on cognitive psychology theory and an adaptive neuro-fuzzy inference system, quantitative models of drivers’ risk perception were established for the crossing processes between two straight-moving vehicles from the orthogonal direction. The acceptable risk perception levels of drivers were identified using a self-developed data analysis method. Based on game theory, the relationship among the quantitative value of drivers’ risk perception, acceptable risk perception level, and vehicle motion state was analyzed. The models of drivers’ crossing behavior were then established. Finally, the behavior models were validated using data collected from real-world vehicle movements and driver decisions. The results showed that the developed behavior models had both high accuracy and good applicability. This study would provide theoretical and algorithmic references for the microscopic simulation and active safety control system of vehicles.

  13. Driver's Behavior and Decision-Making Optimization Model in Mixed Traffic Environment

    Directory of Open Access Journals (Sweden)

    Xiaoyuan Wang

    2015-02-01

    Full Text Available Driving process is an information treating procedure going on unceasingly. It is very important for the research of traffic flow theory, to study on drivers' information processing pattern in mixed traffic environment. In this paper, bicycle is regarded as a kind of information source to vehicle drivers; the “conflict point method” is brought forward to analyze the influence of bicycles on driving behavior. The “conflict” is studied to be translated into a special kind of car-following or lane-changing process. Furthermore, the computer clocked scan step length is dropped to 0.1 s, in order to scan and analyze the dynamic (static information which influences driving behavior in a more exact way. The driver's decision-making process is described through information fusion based on duality contrast and fuzzy optimization theory. The model test and verification show that the simulation results with the “conflict point method” and the field data are consistent basically. It is feasible to imitate driving behavior and the driver information fusion process with the proposed methods. Decision-making optimized process can be described more accurately through computer precision clocked scan strategy. The study in this paper can provide the foundation for further research of multiresource information fusion process of driving behavior.

  14. Energy and Environmental Drivers of Stress and Conflict in Multi scale Models of Human Social Behavior

    Science.gov (United States)

    2017-10-31

    resolved by the recognition that cities are first and foremost self- organizing social networks embedded in space and enabled by urban infrastructure and...AUTHORS 7. PERFORMING ORGANIZATION NAMES AND ADDRESSES 15. SUBJECT TERMS b. ABSTRACT 2. REPORT TYPE 17. LIMITATION OF ABSTRACT 15. NUMBER OF PAGES 5d...Report: Energy and Environmental Drivers of Stress and Conflict in Multi-scale Models of Human Social Behavior The views, opinions and/or findings

  15. Modeling driver stop/run behavior at the onset of a yellow indication considering driver run tendency and roadway surface conditions.

    Science.gov (United States)

    Elhenawy, Mohammed; Jahangiri, Arash; Rakha, Hesham A; El-Shawarby, Ihab

    2015-10-01

    The ability to model driver stop/run behavior at signalized intersections considering the roadway surface condition is critical in the design of advanced driver assistance systems. Such systems can reduce intersection crashes and fatalities by predicting driver stop/run behavior. The research presented in this paper uses data collected from two controlled field experiments on the Smart Road at the Virginia Tech Transportation Institute (VTTI) to model driver stop/run behavior at the onset of a yellow indication for different roadway surface conditions. The paper offers two contributions. First, it introduces a new predictor related to driver aggressiveness and demonstrates that this measure enhances the modeling of driver stop/run behavior. Second, it applies well-known artificial intelligence techniques including: adaptive boosting (AdaBoost), random forest, and support vector machine (SVM) algorithms as well as traditional logistic regression techniques on the data in order to develop a model that can be used by traffic signal controllers to predict driver stop/run decisions in a connected vehicle environment. The research demonstrates that by adding the proposed driver aggressiveness predictor to the model, there is a statistically significant increase in the model accuracy. Moreover the false alarm rate is significantly reduced but this reduction is not statistically significant. The study demonstrates that, for the subject data, the SVM machine learning algorithm performs the best in terms of optimum classification accuracy and false positive rates. However, the SVM model produces the best performance in terms of the classification accuracy only. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems.

    Science.gov (United States)

    Bärgman, Jonas; Boda, Christian-Nils; Dozza, Marco

    2017-05-01

    As the development and deployment of in-vehicle intelligent safety systems (ISS) for crash avoidance and mitigation have rapidly increased in the last decades, the need to evaluate their prospective safety benefits before introduction has never been higher. Counterfactual simulations using relevant mathematical models (for vehicle dynamics, sensors, the environment, ISS algorithms, and models of driver behavior) have been identified as having high potential. However, although most of these models are relatively mature, models of driver behavior in the critical seconds before a crash are still relatively immature. There are also large conceptual differences between different driver models. The objective of this paper is, firstly, to demonstrate the importance of the choice of driver model when counterfactual simulations are used to evaluate two ISS: Forward collision warning (FCW), and autonomous emergency braking (AEB). Secondly, the paper demonstrates how counterfactual simulations can be used to perform sensitivity analyses on parameter settings, both for driver behavior and ISS algorithms. Finally, the paper evaluates the effect of the choice of glance distribution in the driver behavior model on the safety benefit estimation. The paper uses pre-crash kinematics and driver behavior from 34 rear-end crashes from the SHRP2 naturalistic driving study for the demonstrations. The results for FCW show a large difference in the percent of avoided crashes between conceptually different models of driver behavior, while differences were small for conceptually similar models. As expected, the choice of model of driver behavior did not affect AEB benefit much. Based on our results, researchers and others who aim to evaluate ISS with the driver in the loop through counterfactual simulations should be sure to make deliberate and well-grounded choices of driver models: the choice of model matters. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Development of a real-time prediction model of driver behavior at intersections using kinematic time series data.

    Science.gov (United States)

    Tan, Yaoyuan V; Elliott, Michael R; Flannagan, Carol A C

    2017-09-01

    As connected autonomous vehicles (CAVs) enter the fleet, there will be a long period when these vehicles will have to interact with human drivers. One of the challenges for CAVs is that human drivers do not communicate their decisions well. Fortunately, the kinematic behavior of a human-driven vehicle may be a good predictor of driver intent within a short time frame. We analyzed the kinematic time series data (e.g., speed) for a set of drivers making left turns at intersections to predict whether the driver would stop before executing the turn. We used principal components analysis (PCA) to generate independent dimensions that explain the variation in vehicle speed before a turn. These dimensions remained relatively consistent throughout the maneuver, allowing us to compute independent scores on these dimensions for different time windows throughout the approach to the intersection. We then linked these PCA scores to whether a driver would stop before executing a left turn using the random intercept Bayesian additive regression trees. Five more road and observable vehicle characteristics were included to enhance prediction. Our model achieved an area under the receiver operating characteristic curve (AUC) of 0.84 at 94m away from the center of an intersection and steadily increased to 0.90 by 46m away from the center of an intersection. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Sexual behavior among truck drivers.

    Science.gov (United States)

    Singh, Rajiv Kumar; Joshi, Hari Shankar

    2012-01-01

    A cross-sectional study was conducted on Lucknow highway in Bareilly district of Uttar Pradesh to study the knowledge of truck drivers about HIV transmission and prevention and to study the sexual behaviour of these drivers with reference to HIV/AIDS. Age, marital status, education, income, drinking alcohol, length of stay away from home, knowledge about transmission and prevention of HIV, and HIV-prone behavior of truck drivers were studied. Chi-square, mean, and SD were calculated. In all, 289 (97.6%) drivers had heard about HIV/AIDS. Only 242 (81.8%) were aware of HIV transmission by heterosexual route. Misconceptions such as HIV transmission by mosquito bites, living in same room, shaking hands, and sharing food were found. Out of 174 (58.8%) who visited Commercial Sex Workers (CSW), 146 (83.9%) used a condom. 38 (12.8%) visited more than 5 CSW in the last 3 months. Time away from home on the road, marital status, alcohol use, and income class were associated with visiting CSW. High-risk behavior was established in the study population. Safe sex and use of condoms need to be promoted among the truck drivers and better condom availability needs to be assured on highways.

  19. Towards a social psychology-based microscopic model of driver behavior and decision-making : modifying Lewin's field theory

    Science.gov (United States)

    2014-01-01

    Central to effective roadway design is the ability to understand how drivers behave as they traverse a segment of : roadway. While simple and complex microscopic models have been used over the years to analyse driver behaviour, : most models: 1.) inc...

  20. Testing the effects of safety climate and disruptive children behavior on school bus drivers performance: A multilevel model.

    Science.gov (United States)

    Zohar, Dov; Lee, Jin

    2016-10-01

    The study was designed to test a multilevel path model whose variables exert opposing effects on school bus drivers' performance. Whereas departmental safety climate was expected to improve driving safety, the opposite was true for in-vehicle disruptive children behavior. The driving safety path in this model consists of increasing risk-taking practices starting with safety shortcuts leading to rule violations and to near-miss events. The study used a sample of 474 school bus drivers in rural areas, driving children to school and school-related activities. Newly developed scales for measuring predictor, mediator and outcome variables were validated with video data taken from inner and outer cameras, which were installed in 29 buses. Results partially supported the model by indicating that group-level safety climate and individual-level children distraction exerted opposite effects on the driving safety path. Furthermore, as hypothesized, children disruption moderated the strength of the safety rule violation-near miss relationship, resulting in greater strength under high disruptiveness. At the same time, the hypothesized interaction between the two predictor variables was not supported. Theoretical and practical implications for studying safety climate in general and distracted driving in particular for professional drivers are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Bridging Models and Business: Understanding heterogeneity in hidden drivers of customer purchase behavior

    NARCIS (Netherlands)

    E. Korkmaz (Evsen)

    2014-01-01

    markdownabstract__Abstract__ Recent years have seen many advances in quantitative models in the marketing literature. Even though these advances enable model building for a better understanding of customer purchase behavior and customer heterogeneity such that firms develop optimal targeting and

  2. Novice drivers' individual trajectories of driver behavior over the first three years of driving.

    Science.gov (United States)

    Roman, Gabriela D; Poulter, Damian; Barker, Edward; McKenna, Frank P; Rowe, Richard

    2015-09-01

    Identifying the changes in driving behavior that underlie the decrease in crash risk over the first few months of driving is key to efforts to reduce injury and fatality risk in novice drivers. This study represented a secondary data analysis of 1148 drivers who participated in the UK Cohort II study. The Driver Behavior Questionnaire was completed at 6 months and 1, 2 and 3 years after licensure. Linear latent growth models indicated significant increases across development in all four dimensions of aberrant driving behavior under scrutiny: aggressive violations, ordinary violations, errors and slips. Unconditional and conditional latent growth class analyses showed that the observed heterogeneity in individual trajectories was explained by the presence of multiple homogeneous groups of drivers, each exhibiting specific trajectories of aberrant driver behavior. Initial levels of aberrant driver behavior were important in identifying sub-groups of drivers. All classes showed positive slopes; there was no evidence of a group of drivers whose aberrant behavior decreased over time that might explain the decrease in crash involvement observed over this period. Male gender and younger age predicted membership of trajectories with higher levels of aberrant behavior. These findings highlight the importance of early intervention for improving road safety. We discuss the implications of our findings for understanding the behavioral underpinnings of the decrease in crash involvement observed in the early months of driving. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Chinese Road Safety and Driver Behavior Research

    OpenAIRE

    Wang, Junhua

    2015-01-01

    The seminar will begin with a brief overview of the Chinese road safety situation, including current safety problems, and then move on to discuss safety research including driver behavior, freeway operational safety, and infrastructure development.

  4. An Overview on Study of Identification of Driver Behavior Characteristics for Automotive Control

    Directory of Open Access Journals (Sweden)

    Na Lin

    2014-01-01

    Full Text Available Driver characteristics have been the research focus for automotive control. Study on identification of driver characteristics is provided in this paper in terms of its relevant research directions and key technologies involved. This paper discusses the driver characteristics based on driver’s operation behavior, or the driver behavior characteristics. Following the presentation of the fundamental of the driver behavior characteristics, the key technologies of the driver behavior characteristics are reviewed in detail, including classification and identification methods of the driver behavior characteristics, experimental design and data acquisition, and model adaptation. Moreover, this paper discusses applications of the identification of the driver behavior characteristics which has been applied to the intelligent driver advisory system, the driver safety warning system, and the vehicle dynamics control system. At last, some ideas about the future work are concluded.

  5. An application of the driver behavior questionnaire to Chinese carless young drivers.

    Science.gov (United States)

    Zhang, Qian; Jiang, Zuhua; Zheng, Dongpeng; Wang, Yifan; Man, Dong

    2013-01-01

    Carless young drivers refers to those drivers aged between 18 and 25 years who have a driver's license but seldom have opportunities to practice their driving skills because they do not have their own cars. Due to China's lower private car ownership, many young drivers turn into carless young drivers after licensure, and the safety issue associated with them has become a matter of great concern in China. Because few studies have examined the driving behaviors of these drivers, this study aims to utilize the Driver Behavior Questionnaire (DBQ) to investigate the self-reported driving behaviors of Chinese carless young drivers. A total of 523 Chinese carless young drivers (214 females, 309 males) with an average age of 21.91 years completed a questionnaire including the 27-item DBQ and demographics. The data were first randomized into 2 subsamples for factor analysis and then combined together for the following analyses. Both an exploratory factor analysis (EFA, n = 174) and a confirmatory factor analysis (CFA, n = 349) were performed to investigate the factor structure of the DBQ. Correlation analysis was conducted to examine the relationships between the demographics and the DBQ scales' variables. Multivariate linear regression and logistic regression were performed to investigate the prediction of the DBQ scales and crash involvement in the previous year. The EFA produced a 4-factor structure identified as errors, violations, attention lapses, and memory lapses, and the CFA revealed a good model fit after the removal of one item with a low factor loading and the permission of the error covariance between some items. The Chinese carless young drivers reported a comparatively low level of aberrant driving behaviors. The 3 most frequently reported behaviors were all lapses and the 3 least were all violations. Gender was the only significant predictor of the 2 lapses scales and lifetime mileage was the only significant predictor of the violations scale. Only the

  6. Evaluating urban parking policies with agent-based model of driver parking behavior

    NARCIS (Netherlands)

    Martens, C.J.C.M.; Benenson, I.

    2008-01-01

    This paper presents an explicit agent-based model of parking search in a city. In the model, “drivers” drive toward their destination, search for parking, park, remain at the parking place, and leave. The city’s infrastructure is represented by a high-resolution geographic information system (GIS)

  7. Modeling of Driver Steering Operations in Lateral Wind Disturbances toward Driver Assistance System

    Science.gov (United States)

    Kurata, Yoshinori; Wada, Takahiro; Kamiji, Norimasa; Doi, Shun'ichi

    Disturbances decrease vehicle stability and increase driver's mental and physical workload. Especially unexpected disturbances such as lateral winds have severe effect on vehicle stability and driver's workload. This study aims at building a driver model of steering operations in lateral wind toward developing effective driver assistance system. First, the relationship between the driver's lateral motion and its reactive quick steering behavior is investigated using driving simulator with lateral 1dof motion. In the experiments, four different wind patterns are displayed by the simulator. As the results, strong correlation was found between the driver's head lateral jerk by the lateral disturbance and the angular acceleration of the steering wheel. Then, we build a mathematical model of driver's steering model from lateral disturbance input to steering torque of the reactive quick feed-forward steering based on the experimental results. Finally, validity of the proposed model is shown by comparing the steering torque of experimental results and that of simulation results.

  8. Research on Driver Behavior in Yellow Interval at Signalized Intersections

    Directory of Open Access Journals (Sweden)

    Zhaosheng Yang

    2014-01-01

    Full Text Available Vehicles are often caught in dilemma zone when they approach signalized intersections in yellow interval. The existence of dilemma zone which is significantly influenced by driver behavior seriously affects the efficiency and safety of intersections. This paper proposes the driver behavior models in yellow interval by logistic regression and fuzzy decision tree modeling, respectively, based on camera image data. Vehicle’s speed and distance to stop line are considered in logistic regression model, which also brings in a dummy variable to describe installation of countdown timer display. Fuzzy decision tree model is generated by FID3 algorithm whose heuristic information is fuzzy information entropy based on membership functions. This paper concludes that fuzzy decision tree is more accurate to describe driver behavior at signalized intersection than logistic regression model.

  9. Secondary Behavior of Drivers on Cell Phones.

    Science.gov (United States)

    Farmer, Charles M; Klauer, Sheila G; McClafferty, Julie A; Guo, Feng

    2015-01-01

    The objective of this study was to determine whether cell phone use by drivers leads to changes in the frequency of other types of potentially distracting behavior. There were 2 main questions of interest: (1) As each driver changes cell phone use, does he or she change the amount of driving time spent on other distracting behavior? (2) As each driver changes cell phone use, does he or she change the amount of driving time spent looking away from the driving task? Day-to-day driving behavior of 105 volunteer subjects was monitored over a period of 1 year. The amount of driving time during each trip spent on tasks secondary to driving (or looking away from the driving task) was correlated to the amount of time on a cell phone, taking into account the relationships among trips taken by the same driver. Drivers spent 42% of the time engaging in at least one secondary activity. Drivers were talking on a cell phone 7% of the time, interacting in some other way with a cell phone 5% of the time, and engaging in some other secondary activity (sometimes in conjunction with cell phone use) 33% of the time. Other than cell phone use, the most common secondary activities were interacting with a passenger (12% of driving time), holding but not otherwise interacting with an object (6%), and talking/singing/dancing to oneself (5%). Drivers were looking straight forward 81% of the time, forward left or right 5% of time, in a mirror 4% of the time, and elsewhere (eyes off driving task) 10% of time. On average, for each 1 percentage point increase in cell phone talking, the other secondary behavior rate decreased by 0.28 percentage points (P cell phone interaction per trip, the other secondary behavior rate decreased by 0.08 percentage points (P =.0558), but the rate of eyes off driving task increased by 0.06 percentage points (P cell phone can be distracting from the driving task, other secondary activities can be equally or more distracting, at least as measured by eye glances

  10. Driver behavior following an automatic steering intervention.

    Science.gov (United States)

    Fricke, Nicola; Griesche, Stefan; Schieben, Anna; Hesse, Tobias; Baumann, Martin

    2015-10-01

    The study investigated driver behavior toward an automatic steering intervention of a collision mitigation system. Forty participants were tested in a driving simulator and confronted with an inevitable collision. They performed a naïve drive and afterwards a repeated exposure in which they were told to hold the steering wheel loosely. In a third drive they experienced a false alarm situation. Data on driving behavior, i.e. steering and braking behavior as well as subjective data was assessed in the scenarios. Results showed that most participants held on to the steering wheel strongly or counter-steered during the system intervention during the first encounter. Moreover, subjective data collected after the first drive showed that the majority of drivers was not aware of the system intervention. Data from the repeated drive in which participants were instructed to hold the steering wheel loosely, led to significantly more participants holding the steering wheel loosely and thus complying with the instruction. This study seems to imply that without knowledge and information of the system about an upcoming intervention, the most prevalent driving behavior is a strong reaction with the steering wheel similar to an automatic steering reflex which decreases the system's effectiveness. Results of the second drive show some potential for countermeasures, such as informing drivers shortly before a system intervention in order to prevent inhibiting reactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. A Framework for Estimating Long Term Driver Behavior

    Directory of Open Access Journals (Sweden)

    Vijay Gadepally

    2017-01-01

    Full Text Available We present a framework for estimation of long term driver behavior for autonomous vehicles and vehicle safety systems. The Hybrid State System and Hidden Markov Model (HSS+HMM system discussed in this article is capable of describing the hybrid characteristics of driver and vehicle coupling. In our model, driving observations follow a continuous trajectory that can be measured to create continuous state estimates. These continuous state estimates can then be used to estimate the most likely driver state using decision-behavior coupling inherent to the HSS+HMM system. The HSS+HMM system is encompassed in a HSS structure and intersystem connectivity is determined by using signal processing and pattern recognition techniques. The proposed method is suitable for a number of autonomous and vehicle safety scenarios such as estimating intent of other vehicles near intersections or avoiding hazardous driving events such as unexpected lane changes. The long term driver behavior estimation system involves an extended HSS+HMM structure that is capable of including external information in the estimation process. Through the grafting and pruning of metastates, the HSS+HMM system can be dynamically updated to best represent driver choices given external information. Three application examples are also provided to elucidate the theoretical system.

  12. Modeling drivers' passing duration and distance in a virtual environment

    Directory of Open Access Journals (Sweden)

    Haneen Farah

    2013-07-01

    The main contribution of this paper is in the empirical models developed for passing duration and distance which highlights the factors that affect drivers' passing behavior and can be used to enhance the passing models in simulation programs.

  13. A Driver Behavior Learning Framework for Enhancing Traffic Simulation

    Directory of Open Access Journals (Sweden)

    Ramona Maria Paven

    2014-06-01

    Full Text Available Traffic simulation provides an essential support for developing intelligent transportation systems. It allows affordable validation of such systems using a large variety of scenarios that involves massive data input. However, realistic traffic models are hard to be implemented especially for microscopic traffic simulation. One of the hardest problems in this context is to model the behavior of drivers, due the complexity of human nature. The work presented in this paper proposes a framework for learning driver behavior based on a Hidden Markov Model technique. Moreover, we propose also a practical method to inject this behavior in a traffic model used by the SUMO traffic simulator. To demonstrate the effectiveness of this method we present a case study involving real traffic collected from Timisoara city area.

  14. Study on driving control behavior for lane change maneuver. Analysis of expert driver using neural network system; Shasen henkoji no driver sosa tokusei. Neural network system ni yoru jukuren driver no kaiseki

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Z; Okayama, T; Katayama, T [Japan Automobile Research Institute Inc., Tsukuba (Japan); Kageyama, I [Nihon University, Tokyo (Japan)

    1997-10-01

    In order to study driver steering control behavior for vehicle, a driver model for single-lane change maneuver is constructed by a neural network system concerned with the man-machine-environment system. And, using sensitivity analysis, it is found that the model represent the driver control behavior, and the relation between the driver control behavior and vehicle responses. The sensitivity analysis is also examined by applying to the 2nd order predictive driver model. The validity of the sensitivity analysis is confirmed. 5 refs., 8 figs.

  15. Modeling individual and collective opinion in online social networks: drivers of choice behavior and effects of marketing interventions

    NARCIS (Netherlands)

    Koster, S.E.; Langley, D.J.

    2013-01-01

    We investigate factors influencing choice behavior in online social networks. We use twitter data from a Dutch television talent show. In study one, we implement a nested conditional logit model with latent classes. We find heterogeneous effects. For two latent classes, cognitive factors most

  16. Lane-changing model with dynamic consideration of driver's propensity

    Science.gov (United States)

    Wang, Xiaoyuan; Wang, Jianqiang; Zhang, Jinglei; Ban, Xuegang Jeff

    2015-07-01

    Lane-changing is the driver's selection result of the satisfaction degree in different lane driving conditions. There are many different factors influencing lane-changing behavior, such as diversity, randomicity and difficulty of measurement. So it is hard to accurately reflect the uncertainty of drivers' lane-changing behavior. As a result, the research of lane-changing models is behind that of car-following models. Driver's propensity is her/his emotion state or the corresponding preference of a decision or action toward the real objective traffic situations under the influence of various dynamic factors. It represents the psychological characteristics of the driver in the process of vehicle operation and movement. It is an important factor to influence lane-changing. In this paper, dynamic recognition of driver's propensity is considered during simulation based on its time-varying discipline and the analysis of the driver's psycho-physic characteristics. The Analytic Hierarchy Process (AHP) method is used to quantify the hierarchy of driver's dynamic lane-changing decision-making process, especially the influence of the propensity. The model is validated using real data. Test results show that the developed lane-changing model with the dynamic consideration of a driver's time-varying propensity and the AHP method are feasible and with improved accuracy.

  17. Matching Countermeasures to Driver Types and Speeding Behavior : Traffic Tech

    Science.gov (United States)

    2017-06-01

    Speeding is a common behavior; most drivers exceed the speed limit some of the time. It is also a complicated behavior that varies by driver and situation. Speeding-related crashes take a large annual toll in injuries, lost lives, and high economic c...

  18. Assessing the relationship between the Driver Behavior Questionnaire and the Driver Skill Inventory: Revealing sub-groups of drivers

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Møller, Mette; Prato, Carlo Giacomo

    2014-01-01

    The Driver Behavior Questionnaire and the Driver Skill Inventory are two of the most frequently used measures of self-reported driving style and driving skill. The motivation behind the present study was to identify sub-groups of drivers that potentially act dangerously in traffic (as measured...... self-reported driving skills and whether the reported skill level was reflected in the reported aberrant driving behaviors. 3908 drivers aged 18–84 participated in the survey. K-means cluster analysis revealed four distinct sub-groups that differed in driving skills and frequency of aberrant driving...... by frequency of aberrant driving behaviors and level of driving skills), as well as to test whether the sub-groups differ in characteristics such as age, gender, annual mileage and accident involvement. Furthermore, the joint analysis of the two instruments was used to test drivers’ assessment of their own...

  19. Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes.

    Science.gov (United States)

    Wu, Qiong; Zhang, Guohui; Ci, Yusheng; Wu, Lina; Tarefder, Rafiqul A; Alcántara, Adélamar Dely

    2016-05-18

    Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle-infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities. Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality. The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups. The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.

  20. Discriminating Drivers through Human Factor and Behavioral Difference

    Directory of Open Access Journals (Sweden)

    Ju Seok Oh

    2011-05-01

    Full Text Available Since Greenwood and Woods' (1919 study in tendency of accident, many researchers have insisted that various human factors (sensation seeking, anger, anxiety are highly correlated with reckless driving and traffic accidents. Oh and Lee (2011 designed the Driving Behavior Determinants Questionnaire, a psychological tool to predict danger level of drivers and discriminate them into three groups (normal, unintentionally reckless, and intentionally reckless by their characteristics, attitude, and expected reckless behavior level. This tool's overall accuracy of discrimination was 70%. This study aimed to prove that the discrimination reflects the behavioral difference of drivers. Twenty-four young drivers were requested to react to the visual stimuli (tests for subjective speed sense, simple visual reaction time, and left turning at own risk. The results showed no differences in subjective speed sense among the driver groups, which means drivers' excessive speeding behaviors occur due to intention based on personality and attitude, not because of sensory disorders. In addition, there were no differences in simple reaction time among driver groups. However, the results of the ‘Left turning at drivers’ own risk task” revealed significant group differences. All reckless drivers showed a greater degree of dangerous left turning behaviors than the normal group did.

  1. Anticipating the Environmental Impacts and Behavioral Drivers of Deep Decarbonization

    Science.gov (United States)

    EPA is seeking regular and early career applications proposing research that will contribute to an improved ability to understand and anticipate the public health and environmental impacts and behavioral drivers of significant changes in energy consumption

  2. Taxonomy of Older Driver Behaviors and Crash Risk : Appendix C

    Science.gov (United States)

    2012-02-01

    This projects objectives were to identify risky behaviors, driving habits, and exposure patterns that have been shown to increase the likelihood of crash involvement among older drivers; and to classify these crash-contributing factors according t...

  3. Visual behaviour analysis and driver cognitive model

    Energy Technology Data Exchange (ETDEWEB)

    Baujon, J.; Basset, M.; Gissinger, G.L. [Mulhouse Univ., (France). MIPS/MIAM Lab.

    2001-07-01

    Recent studies on driver behaviour have shown that perception - mainly visual but also proprioceptive perception - plays a key role in the ''driver-vehicle-road'' system and so considerably affects the driver's decision making. Within the framework of the behaviour analysis and studies low-cost system (BASIL), this paper presents a correlative, qualitative and quantitative study, comparing the information given by visual perception and by the trajectory followed. This information will help to obtain a cognitive model of the Rasmussen type according to different driver classes. Many experiments in real driving situations have been carried out for different driver classes and for a given trajectory profile, using a test vehicle and innovative, specially designed, real-time tools, such as the vision system or the positioning module. (orig.)

  4. Review on identification study of driver behavior intention and characteristics

    Directory of Open Access Journals (Sweden)

    Gang LI

    2017-08-01

    Full Text Available In order to better improve vehicle active safety and realize personalized driving, aiming at the problem of the identification of driver behavior intention and characteristics, the electronic control systems' important role in the automobile and the importance of the driver behavior intention and characteristic identification are discussed. The relative domestic and foreign research is summarized, and the prospect is put forward. In order to improve the performance of automobile electronic control system and realize the intelligent control for the cars, the identification of driver behavior intention and characteristics needs to be studied. How to rationally classify and on-line identify drivers' characteristics correctly for the steering, braking and acceleration characteristics is a long term research topic.

  5. Does automatic transmission improve driving behavior in older drivers?

    Science.gov (United States)

    Selander, Helena; Bolin, Ingrid; Falkmer, Torbjörn

    2012-01-01

    Most older drivers continue to drive as they age. To maintain safe and independent transport, mobility is important for all individuals, but especially for older drivers. The objective of this study was to investigate whether automatic transmission, compared with manual transmission, may improve the driving behavior of older drivers. In total, 31 older drivers (mean age 75.2 years) and 32 younger drivers - used as a control group (mean age 39.2 years) - were assessed twice on the same fixed route; once in a car with manual transmission and once in a car with automatic transmission. The cars were otherwise identical. The driving behavior was assessed with the Ryd On-Road Assessment driving protocol. Time to completion of left turns (right-hand side driving) and the impact of a distraction task were measured. The older group had more driving errors than the younger group, in both the manual and the automatic transmission car. However, and contrary to the younger drivers, automatic transmission improved the older participants' driving behavior as demonstrated by safer speed adjustment in urban areas, greater maneuvering skills, safer lane position and driving in accordance with the speed regulations. Switching to automatic transmission may be recommended for older drivers as a means to maintain safe driving and thereby the quality of their transport mobility. Copyright © 2011 S. Karger AG, Basel.

  6. Traffic safety issues in North Dakota : phase II : driver knowledge, attitude, behavior and beliefs : focus group : young male drivers

    Science.gov (United States)

    2008-10-01

    Traffic safety is a widespread social concern. Tackling the problem requires understanding the people : who are driving. This includes information about driver behavior, but also about perceptions these drivers : hold regarding their driving. North D...

  7. Modeling of driver's collision avoidance maneuver based on controller switching model.

    Science.gov (United States)

    Kim, Jong-Hae; Hayakawa, Soichiro; Suzuki, Tatsuya; Hayashi, Koji; Okuma, Shigeru; Tsuchida, Nuio; Shimizu, Masayuki; Kido, Shigeyuki

    2005-12-01

    This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

  8. Driver Performance Model: 1. Conceptual Framework

    National Research Council Canada - National Science Library

    Heimerl, Joseph

    2001-01-01

    ...'. At the present time, no such comprehensive model exists. This report discusses a conceptual framework designed to encompass the relationships, conditions, and constraints related to direct, indirect, and remote modes of driving and thus provides a guide or 'road map' for the construction and creation of a comprehensive driver performance model.

  9. Aberrant Behaviors and Road Accidents among Iranian Truck Drivers, 2010

    Directory of Open Access Journals (Sweden)

    Amir Houshang Mehrparvar

    2011-12-01

    Full Text Available structural dimensions of which as well as technologic failures such as road quality, and tech-nical faults of automobiles, need to be assessed in detail. Iran has the first order in the world for deadly road accidents. This study was designed to assess the association between aberrant behaviors of truck drivers and the incidence of road accidents in Yazd, center of Iran, in 2010.Methods: This cross-sectional descriptive-analytic study was conducted on 300 truck drivers in Yazd. We used 3 questionnaires, including one for demographic data, Driver Behavior Questionnaire (DBQ, and one for drivers' self-evaluation of the of their driving.Results: Five types of the behavior had the highest frequency: Misjudge speed of oncoming vehicle when overtaking.; Deliberately disregard the speed limits late at night or very early in the morning.; Ignore 'give way' signs, and narrowly avoid colliding with traffic having right of way.; Stuck behind a slow-moving vehicle on a two-lane highway, you are driven by frustration to try to overtake in risky circumstances.; Drive with only 'half-an-eye' on the road while looking at a map, changing a cassette or radio channel, etc. The more the driver's driv-ing was influenced by emotional and mental states the more deliberate violations and slips.Conclusion: Among truck drivers, safety has not developed sufficiently, and because of the dangers of road accidents both for the drivers and other people and its economic losses, the importance of the presenting some solutions is completely obvious.

  10. Driver behavior analysis for right-turn drivers at signalized intersections using SHRP 2 naturalistic driving study data.

    Science.gov (United States)

    Wu, Jianqing; Xu, Hao

    2017-12-01

    Understanding driver behavior is important for traffic safety and operation, especially at intersections where different traffic movements conflict. While most driver-behavior studies are based on simulation, this paper documents the analysis of driver-behavior at signalized intersections with the SHRP 2 Naturalistic Driving Study (NDS) data. This study analyzes the different influencing factors on the operation (speed control) and observation of right-turn drivers. A total of 300 NDS trips at six signalized intersections were used, including the NDS time-series sensor data, the forward videos and driver face videos. Different factors of drivers, vehicles, roads and environments were studied for their influence on driver behavior. An influencing index function was developed and the index was calculated for each influencing factor to quantitatively describe its influencing level. The influencing index was applied to prioritize the factors, which facilitates development and selection of safety countermeasures to improve intersection safety. Drivers' speed control was analyzed under different conditions with consideration of the prioritized influencing factors. Vehicle type, traffic signal status, conflicting traffic, conflicting pedestrian and driver age group were identified as the five major influencing factors on driver observation. This research revealed that drivers have high acceleration and low observation frequency under Right-Turn-On-Red (RTOR), which constituted potential danger for other roadway users, especially for pedestrians. As speed has a direct influence on crash rates and severities, the revealed speed patterns of the different situations also benefit selection of safety countermeasures at signalized intersections. Published by Elsevier Ltd.

  11. Conditions that Influence Drivers' Yielding Behavior for Uncontrolled Crossings

    Science.gov (United States)

    Bourquin, Eugene; Emerson, Robert Wall; Sauerburger, Dona

    2011-01-01

    Pedestrians with visual impairments need to cross streets where traffic signals and traffic signage are not present. This study examined the influences of several interventions, including a pedestrian's use of a mobility cane, on the behavior of drivers when they were expected to yield to a pedestrian crossing at an uncontrolled crossing.…

  12. Driver's various information process and multi-ruled decision-making mechanism: a fundamental of intelligent driving shaping model

    Directory of Open Access Journals (Sweden)

    Wuhong Wang

    2011-05-01

    Full Text Available The most difficult but important problem in advance driver assistance system development is how to measure and model the behavioral response of drivers with focusing on the cognition process. This paper describes driver's deceleration and acceleration behavior based on driving situation awareness in the car-following process, and then presents several driving models for analysis of driver's safety approaching behavior in traffic operation. The emphasis of our work is placed on the research of driver's various information process and multi-ruled decisionmaking mechanism by considering the complicated control process of driving; the results will be able to provide a theoretical basis for intelligent driving shaping model.

  13. Can We Model Driver Perceptions? An In-Situ Experiment in Real-World Conditions

    Directory of Open Access Journals (Sweden)

    Aly M. Tawfik, PhD

    2014-06-01

    Full Text Available It is clear that perceptions play a significant role in traveler decisions. Consequently, traveler perceptions are a corner stone in the feasibility of traveler information systems; for traveler information systems are only valuable if the drivers are incapable of accurately acquiring the provided information on their own, and if the provided information is relevant for the drivers' decision criteria. Accuracy of traveler perceptions has been repeatedly researched in public transportation, and has been found to vary according to different reasons. However, in spite of the clear significance of traveler perceptions, minimal effort has been put into modeling it. Almost all travel behavior models are based on traveler experiences, which are assumed to reflect traveler perceptions via the addition of some random error component. This works introduces an alternative approach: instead of adding an error component to represent driver perceptions, it proposes to model driver perceptions. This work is based on a real-world route choice experiment of a sample of 20 drivers who made more than 2,000 real-world route choices. Each of the drivers' experiences, perceptions, and choices were recorded, analyzed and cross examined. The paper demonstrates that: i driver experiences are different from driver perceptions, ii driver perceptions explain driver choices better than driver experiences, iii it is possible to model and predict driver perceptions of travel distance, time and speed.

  14. A study of driver's route choice behavior based on evolutionary game theory.

    Science.gov (United States)

    Jiang, Xiaowei; Ji, Yanjie; Du, Muqing; Deng, Wei

    2014-01-01

    This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

  15. Exploring the safety implications of young drivers' behavior, attitudes and perceptions.

    Science.gov (United States)

    Hassan, Hany M; Abdel-Aty, Mohamed A

    2013-01-01

    The present study aims at identifying and quantifying significant factors (i.e., demographic, aberrant driving behavior) associated with young drivers' involvement in at-fault crashes or traffic citations at the ages of 16-17 (while having the Operational License) and 18-24 years old (while having the Full License). A second objective was to investigate the main reason(s) for involvement in risky driving behavior by young drivers. The data used for the analyses were obtained from a self-reported questionnaire survey carried out among 680 young drivers in Central Florida. To achieve these goals, the structural equation modeling approach was adopted. The results revealed that aggressive violations, in-vehicle distractions and demographic characteristics were the significant factors affecting young drivers' involvement in at-fault crashes or traffic violations at the age of 16-17. However, in-vehicle distractions, attitudes toward speeding and demographic characteristics were the significant factors affecting young drivers' crash risk at 18-24. Additionally, the majority of participants reported that "running late" is the main reason for taking risk while driving (i.e., speeding, accept short gaps, or drive so close to the car in front) followed by "racing other cars". Additionally, "exceed speed limits" was the main reason for receiving traffic citations at 16-17 and 18-24 age groups. Practical suggestions on how to reduce crash risk and promote safe driving among young drivers are also discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Geometrical Design Errors in Duhok Intersections by Driver Behavior

    Directory of Open Access Journals (Sweden)

    Dilshad Ali Mohammed

    2018-03-01

    Full Text Available In many situations, drivers if certain of the absence traffic monitoring system tend to shorten their driving paths and travel time across intersections. This behavior will be encouraged if the geometrical design suffers from mistakes, or the geometrical design and road conditions make it harder for drivers to follow the correct routes. Sometimes the intersection arrangement is confusing for the driver to distinguish the right from the wrong track. In this study, two sites with large number of driving mistakes were noticed. One site is a roundabout within the university of Duhok campus. The other is the intersection just outside the University of Duhok eastern main gate. At both sites, the geometry is very confusing and encourage driving mistakes. The university roundabout which was the first site investigated, was not properly designed encouraging wrong side driving. Many traffic accidents took place at this roundabout.  Wrong side driving reaches 32 % at peak hour in one approach.  This was reduced to 6% when temporary divisional island was installed. The other approach has a 15% wrong side driving and no remedy could be done to it. At the intersection near the university gate, wrong side driving reaches 56% of the traffic emerging from the main gate at peak hour. This was reduced to 14% when drivers are guided through direction sign. This percentage was reduced further to 9% with standing policeman.

  17. How to identify the key factors that affect driver perception of accident risk. A comparison between Italian and Spanish driver behavior.

    Science.gov (United States)

    de Oña, Juan; de Oña, Rocio; Eboli, Laura; Forciniti, Carmen; Mazzulla, Gabriella

    2014-12-01

    Road crashes can be caused by different factors, including infrastructure, vehicles, and human variables. Many research studies have focused solely on identifying the key factors that cause road crashes. From these studies, it emerged that human factors have the most relevant impact on accident severity. More specifically, accident severity depends on several factors related directly to the driver, i.e., driving experience, driver's socio-economic characteristics, and driving behavior and attitudes. In this paper, we investigate driver behaviors and attitudes while driving and specifically focus on different methods for identifying the factors that most affect the driver's perception of accident risk. To this end, we designed and conducted a survey in two different European contexts: the city of Cosenza, which is located in the south of Italy, and the city of Granada, which is located in the south of Spain. Samples of drivers were contacted for their opinions on certain aspects of driving rules and attitudes while driving, and different types of questions were addressed to the drivers to assess their judgments of these aspects. Consequently, different methods of data analysis were applied to determine the aspects that heavily influence driver perception of accident risk. An experiment based on the stated preferences (SP) was carried out with the drivers, and the SP data were analyzed using an ordered probit (OP) model. Interesting findings emerged from different analyses of the data and from the comparisons among the data collected in the two different territorial contexts. We found that both Italian and Spanish drivers consider driving in an altered psychophysical state and violating the overtaking rules to be the most risky behaviors. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Behavior and lifestyle characteristics of male Kuwaiti drivers.

    Science.gov (United States)

    Al-Hemoud, Ali M; Simmons, Rodney J; Al-Asfoor, May M

    2010-08-01

    The high traffic accident risk among young drivers is a well-known and well-documented fact in most countries. Lifestyle has proven to affect driving behavior as well as accident risk. This study covers the lifestyle component of the problems related to young male Kuwaiti drivers' accident risk. The purpose of the study is to measure the relationship between lifestyle and accident risk. Lifestyle is measured through a questionnaire, where 302 male Kuwaiti drivers (mean age=28 years; range 25-35 years) answer 39 questions related to behavioral and social factors, road conditions, police enforcement, and life satisfaction. They also report their involvement in accidents and traffic violations. The questionnaire's validity and reliability (Cronbach's alpha=0.7) were achieved. Principal component analysis reduced the 39 items on the questionnaire to 5 factors. Inadequate police enforcement is strongly correlated (r=0.862) to accident risk and traffic violations and is thus considered the best predictor of traffic accidents in Kuwait. As driving-related incidents (on-the-job and off-the-job) are a significant source of fatalities and lost-work-days, the study points to the importance of considering cultural factors in the design of comprehensive safety programs for industry. 2010. Published by Elsevier Ltd.

  19. Driver steering model for closed-loop steering function analysis

    Science.gov (United States)

    Bolia, Pratiksh; Weiskircher, Thomas; Müller, Steffen

    2014-05-01

    In this paper, a two level preview driver steering control model for the use in numerical vehicle dynamics simulation is introduced. The proposed model is composed of cascaded control loops: The outer loop is the path following layer based on potential field framework. The inner loop tries to capture the driver's physical behaviour. The proposed driver model allows easy implementation of different driving situations to simulate a wide range of different driver types, moods and vehicle types. The expediency of the proposed driver model is shown with the help of developed driver steering assist (DSA) function integrated with a conventional series production (Electric Power steering System with rack assist servo unit) system. With the help of the DSA assist function, the driver is prevented from over saturating the front tyre forces and loss of stability and controllability during cornering. The simulation results show different driver reactions caused by the change in the parameters or properties of the proposed driver model if the DSA assist function is activated. Thus, the proposed driver model is useful for the advanced driver steering and vehicle stability assist function evaluation in the early stage of vehicle dynamics handling and stability evaluation.

  20. Integrating Qualitative and Quantitative Methods in Participatory Modeling to Elicit Behavioral Drivers in Environmental Dilemmas: the Case of Air Pollution in Talca, Chile.

    Science.gov (United States)

    Meinherz, Franziska; Videira, Nuno

    2018-04-10

    The aim of this paper is to contribute to the exploration of environmental modeling methods based on the elicitation of stakeholders' mental models. This aim is motivated by the necessity to understand the dilemmas and behavioral rationales of individuals for supporting the management of environmental problems. The methodology developed for this paper integrates qualitative and quantitative methods by deploying focus groups for the elicitation of the behavioral rationales of the target population, and grounded theory to code the information gained in the focus groups and to guide the development of a dynamic simulation model. The approach is applied to a case of urban air pollution caused by residential heating with wood in central Chile. The results show how the households' behavior interrelates with the governmental management strategies and provide valuable and novel insights into potential challenges to the implementation of policies to manage the local air pollution problem. The experience further shows that the developed participatory modeling approach allows to overcome some of the issues currently encountered in the elicitation of individuals' behavioral rationales and in the quantification of qualitative information.

  1. Crash risk and aberrant driving behaviors among bus drivers: the role of personality and attitudes towards traffic safety.

    Science.gov (United States)

    Mallia, Luca; Lazuras, Lambros; Violani, Cristiano; Lucidi, Fabio

    2015-06-01

    Several studies have shown that personality traits and attitudes toward traffic safety predict aberrant driving behaviors and crash involvement. However, this process has not been adequately investigated in professional drivers, such as bus drivers. The present study used a personality-attitudes model to assess whether personality traits predicted aberrant self-reported driving behaviors (driving violations, lapses, and errors) both directly and indirectly, through the effects of attitudes towards traffic safety in a large sample of bus drivers. Additionally, the relationship between aberrant self-reported driving behaviors and crash risk was also assessed. Three hundred and one bus drivers (mean age=39.1, SD=10.7 years) completed a structured and anonymous questionnaire measuring personality traits, attitudes toward traffic safety, self-reported aberrant driving behaviors (i.e., errors, lapses, and traffic violations), and accident risk in the last 12 months. Structural equation modeling analysis revealed that personality traits were associated to aberrant driving behaviors both directly and indirectly. In particular altruism, excitement seeking, and normlessness directly predicted bus drivers' attitudes toward traffic safety which, in turn, were negatively associated with the three types of self-reported aberrant driving behaviors. Personality traits relevant to emotionality directly predicted bus drivers' aberrant driving behaviors, without any mediation of attitudes. Finally, only self-reported violations were related to bus drivers' accident risk. The present findings suggest that the hypothesized personality-attitudes model accounts for aberrant driving behaviors in bus drivers, and provide the empirical basis for evidence-based road safety interventions in the context of public transport. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Incorporating driver distraction in car-following models: Applying the TCI to the IDM

    OpenAIRE

    Hoogendoorn, R.G.; van Arem, B.; Hoogendoorn, S.P.

    2013-01-01

    ITS can play a significant role in the improvement of traffic flow, traffic safety and greenhouse gas emissions. However, the implementation of Advanced Driver Assistance Systems may lead to adaptation effects in longitudinal driving behavior following driver distraction. It was however not yet clear how to model these adaptation effects in driving behavior mathematically and on which theoretical framework this should be grounded. To this end in this contribution we introduce a theoretical fr...

  3. How driving duration influences drivers' visual behaviors and fatigue ...

    African Journals Online (AJOL)

    unhcc

    Eye fixations express the focus of driver's visual attention on driving, ... driver's attention is attracted by fatigue. The second ... was divided into seven refined categories (see Table 1), ...... driver fatigue in terms of line crossing: a pilot study.

  4. FRIB driver linac vacuum model and benchmarks

    CERN Document Server

    Durickovic, Bojan; Kersevan, Roberto; Machicoane, Guillaume

    2014-01-01

    The Facility for Rare Isotope Beams (FRIB) is a superconducting heavy-ion linear accelerator that is to produce rare isotopes far from stability for low energy nuclear science. In order to achieve this, its driver linac needs to achieve a very high beam current (up to 400 kW beam power), and this requirement makes vacuum levels of critical importance. Vacuum calculations have been carried out to verify that the vacuum system design meets the requirements. The modeling procedure was benchmarked by comparing models of an existing facility against measurements. In this paper, we present an overview of the methods used for FRIB vacuum calculations and simulation results for some interesting sections of the accelerator. (C) 2013 Elsevier Ltd. All rights reserved.

  5. Driver's mental workload prediction model based on physiological indices.

    Science.gov (United States)

    Yan, Shengyuan; Tran, Cong Chi; Wei, Yingying; Habiyaremye, Jean Luc

    2017-09-15

    Developing an early warning model to predict the driver's mental workload (MWL) is critical and helpful, especially for new or less experienced drivers. The present study aims to investigate the correlation between new drivers' MWL and their work performance, regarding the number of errors. Additionally, the group method of data handling is used to establish the driver's MWL predictive model based on subjective rating (NASA task load index [NASA-TLX]) and six physiological indices. The results indicate that the NASA-TLX and the number of errors are positively correlated, and the predictive model shows the validity of the proposed model with an R 2 value of 0.745. The proposed model is expected to provide a reference value for the new drivers of their MWL by providing the physiological indices, and the driving lesson plans can be proposed to sustain an appropriate MWL as well as improve the driver's work performance.

  6. Routing Service Quality—Local Driver Behavior Versus Routing Services

    DEFF Research Database (Denmark)

    Ceikute, Vaida; Jensen, Christian S.

    2013-01-01

    of the quality of one kind of location-based service, namely routing services. Specifically, the paper presents a framework that enables the comparison of the routes provided by routing services with the actual driving behaviors of local drivers. Comparisons include route length, travel time, and also route...... popularity, which are enabled by common driving behaviors found in available trajectory data. The ability to evaluate the quality of routing services enables service providers to improve the quality of their services and enables users to identify the services that best serve their needs. The paper covers......Mobile location-based services is a very successful class of services that are being used frequently by users with GPS-enabled mobile devices such as smartphones. This paper presents a study of how to exploit GPS trajectory data, which is available in increasing volumes, for the assessment...

  7. Evaluating the effectiveness of Behavior-Based Safety education methods for commercial vehicle drivers.

    Science.gov (United States)

    Wang, Xuesong; Xing, Yilun; Luo, Lian; Yu, Rongjie

    2018-08-01

    Risky driving behavior is one of the main causes of commercial vehicle related crashes. In order to achieve safer vehicle operation, safety education for drivers is often provided. However, the education programs vary in quality and may not always be successful in reducing crash rates. Behavior-Based Safety (BBS) education is a popular approach found effective by numerous studies, but even this approach varies as to the combination of frequency, mode and content used by different education providers. This study therefore evaluates and compares the effectiveness of BBS education methods. Thirty-five drivers in Shanghai, China, were coached with one of three different BBS education methods for 13 weeks following a 13-week baseline phase with no education. A random-effects negative binomial (NB) model was built and calibrated to investigate the relationship between BBS education and the driver at-fault safety-related event rate. Based on the results of the random-effects NB model, event modification factors (EMF) were calculated to evaluate and compare the effectiveness of the methods. Results show that (1) BBS education was confirmed to be effective in safety-related event reduction; (2) the most effective method among the three applied monthly face-to-face coaching, including feedback with video and statistical data, and training on strategies to avoid driver-specific unsafe behaviors; (3) weekly telephone coaching using statistics and strategies was rated by drivers as the most convenient delivery mode, and was also significantly effective. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Novice drivers' risky driving behavior, risk perception, and crash risk: findings from the DRIVE study.

    Science.gov (United States)

    Ivers, Rebecca; Senserrick, Teresa; Boufous, Soufiane; Stevenson, Mark; Chen, Huei-Yang; Woodward, Mark; Norton, Robyn

    2009-09-01

    We explored the risky driving behaviors and risk perceptions of a cohort of young novice drivers and sought to determine their associations with crash risk. Provisional drivers aged 17 to 24 (n = 20 822) completed a detailed questionnaire that included measures of risk perception and behaviors; 2 years following recruitment, survey data were linked to licensing and police-reported crash data. Poisson regression models that adjusted for multiple confounders were created to explore crash risk. High scores on questionnaire items for risky driving were associated with a 50% increased crash risk (adjusted relative risk = 1.51; 95% confidence interval = 1.25, 1.81). High scores for risk perception (poorer perceptions of safety) were also associated with increased crash risk in univariate and multivariate models; however, significance was not sustained after adjustment for risky driving. The overrepresentation of youths in crashes involving casualties is a significant public health issue. Risky driving behavior is strongly linked to crash risk among young drivers and overrides the importance of risk perceptions. Systemwide intervention, including licensing reform, is warranted.

  9. The Effect of Passengers on Teen Driver Behavior

    Science.gov (United States)

    2012-04-01

    A number of studies have shown that passengers substantially increase the risk of crashes for young, novice drivers. This increased risk may result from distractions that young passengers create for drivers. Alternatively, the presence of passengers ...

  10. The effect of passengers on teen driver behavior : traffic tech.

    Science.gov (United States)

    2012-04-01

    A number of studies have shown that passengers substantially : increase the risk of crashes for young, novice drivers. : This increased risk may result from distractions that young : passengers create for drivers. Alternatively, the presence : of pas...

  11. Analyzing the Influence of Mobile Phone Use of Drivers on Traffic Flow Based on an Improved Cellular Automaton Model

    Directory of Open Access Journals (Sweden)

    Yao Xiao

    2015-01-01

    Full Text Available This paper aimed to analyze the influence of drivers’ behavior of phone use while driving on traffic flow, including both traffic efficiency and traffic safety. An improved cellular automaton model was proposed to simulate traffic flow with distracted drivers based on the Nagel-Schreckenberg model. The driving characters of drivers using a phone were first discussed and a value representing the probability to use a phone while driving was put into the CA model. Simulation results showed that traffic flow rate was significantly reduced if some drivers used a phone compared to no phone use. The flow rate and velocity decreased as the proportion of drivers using a phone increased. While, under low density, the risk of traffic decreased first and then increased as the distracted drivers increased, the distracted behavior of drivers, like using a phone, could reduce the flow rate by 5 percent according to the simulation.

  12. Understanding & modeling bus transit driver availability.

    Science.gov (United States)

    2014-07-01

    Bus transit agencies are required to hire extraboard (i.e. back-up) operators to account for unexpected absences. Incorrect sizing of extra driver workforce is problematic for a number of reasons. Overestimating the appropriate number of extraboard o...

  13. An analysis on older driver's driving behavior by GPS tracking data: Road selection, left/right turn, and driving speed

    Directory of Open Access Journals (Sweden)

    Yanning Zhao

    2018-02-01

    Full Text Available With the high older-related accident ratio and increasing population aging problem, understanding older drivers' driving behaviors has become more and more important for building and improving transportation system. This paper examines older driver's driving behavior which includes road selection, left/right turn and driving speed. A two-month experiment of 108 participants was carried out in Aichi Prefecture, Japan. Since apparently contradictory statements were often drawn in survey-based or simulators-based studies, this study collected not only drivers' basic information but also GPS data. Analysis of road selection demonstrates that older drivers are reluctant to drive on expressway not only in short trips but also in long trips. The present study did not find significant difference between older drivers and others while turning at the intersections. To investigate the impact factors on driving speed, a random-effects regression model is constructed with explanatory variables including age, gender, road types and the interaction terms between age and road types. Compared with other variables, it fails to find that age (60 years old or over has significant impact on driving speed. Moreover, the results reflect that older drivers drive even faster than others at particular road types: national road and ordinary municipal road. The results in this study are expected to help improve transportation planning and develop driving assistance systems for older drivers.

  14. Chinese carless young drivers' self-reported driving behavior and simulated driving performance.

    Science.gov (United States)

    Zhang, Qian; Jiang, Zuhua; Zheng, Dongpeng; Man, Dong; Xu, Xunnan

    2013-01-01

    Carless young drivers refers to those drivers aged between 18 and 25 years who have a driver's license but seldom have opportunities to practice their driving skills because they do not have their own cars. Due to China's lower private car ownership, many young drivers become carless young drivers after licensure, and the safety issue associated with them has raised great concern in China. This study aims to provide initial insight into the self-reported driving behaviors and simulated driving performance of Chinese carless young drivers. Thirty-three carless young drivers and 32 young drivers with their own cars (as a comparison group) participated in this study. A modified Driver Behavior Questionnaire (DBQ) with a 4-factor structure (errors, violations, attention lapses, and memory lapses) was used to study carless young drivers' self-reported driving behaviors. A simulated driving experiment using a low-cost, fixed-base driving simulator was conducted to measure their simulated driving performance (errors, violations, attention lapses, driving maintenance, reaction time, and accidents). Self-reported DBQ outcomes showed that carless young drivers reported similar errors, more attention lapses, fewer memory lapses, and significantly fewer violation behaviors relative to young drivers with their own cars, whereas simulated driving results revealed that they committed significantly more errors, attention lapses, and violation behaviors than the comparison group. Carless young drivers had a lower ability to maintain the stability of speed and lane position, drove more cautiously approaching and passing through red traffic lights, and committed more accidents during simulated driving. A tendency to speed was not found among carless young drivers; their average speed and speeding frequency were all much lower than that of the comparison group. Lifetime mileage was the only significant predictor of carless young drivers' self-reported violations, simulated violations

  15. The Research of the Driver Attention Field Modeling

    Directory of Open Access Journals (Sweden)

    Pengfei Tao

    2014-01-01

    Full Text Available For expanding the application scope of car-following, based on the basic idea of the noncontact interaction of the objects in physics, establish an attention field model to describe the driving behavior. Firstly, propose the time distance concept to describe the degree of driver perception to the front one-dimensional space and extend its application range to the two-dimensional space. Secondly, connect the point which has the same time distance to constitute the equipotential line of drivers’ attention field equipotent, and establish a model to describe it. Thirdly, define the effective range of the driver’s psychological field with the feature of the driver’s visual distance range increasing and the angle decreasing. Finally, design the calculation method to collect projection of the object in the psychological field scope and calculate the curve points to determine the object’s intensity of psychological field. Preliminarily build the driving behavior model and use the numerical simulation method to simulate the simple transport scenarios; initially verify the validity of the model.

  16. Does assisted driving behavior lead to safety-critical encounters with unequipped vehicles' drivers?

    Science.gov (United States)

    Preuk, Katharina; Stemmler, Eric; Schießl, Caroline; Jipp, Meike

    2016-10-01

    With Intelligent Transport Systems (e.g., traffic light assistance systems) assisted drivers are able to show driving behavior in anticipation of upcoming traffic situations. In the years to come, the penetration rate of such systems will be low. Therefore, the majority of vehicles will not be equipped with these systems. Unequipped vehicles' drivers may not expect the driving behavior of assisted drivers. However, drivers' predictions and expectations can play a significant role in their reaction times. Thus, safety issues could arise when unequipped vehicles' drivers encounter driving behavior of assisted drivers. This is why we tested how unequipped vehicles' drivers (N=60) interpreted and reacted to the driving behavior of an assisted driver. We used a multi-driver simulator with three drivers. The three drivers were driving in a line. The lead driver in the line was a confederate who was followed by two unequipped vehicles' drivers. We varied the equipment of the confederate with an Intelligent Transport System: The confederate was equipped either with or without a traffic light assistance system. The traffic light assistance system provided a start-up maneuver before a light turned green. Therefore, the assisted confederate seemed to show unusual deceleration behavior by coming to a halt at an unusual distance from the stop line at the red traffic light. The unusual distance was varied as we tested a moderate (4m distance from the stop line) and an extreme (10m distance from the stop line) parameterization of the system. Our results showed that the extreme parametrization resulted in shorter minimal time-to-collision of the unequipped vehicles' drivers. One rear-end crash was observed. These results provided initial evidence that safety issues can arise when unequipped vehicles' drivers encounter assisted driving behavior. We recommend that future research identifies counteractions to prevent these safety issues. Moreover, we recommend that system developers

  17. Effects of fog, driver experience and gender on driving behavior on S-curved road segments.

    Science.gov (United States)

    Li, Xiaomeng; Yan, Xuedong; Wong, S C

    2015-04-01

    Driving on curved roads has been recognized as a significant safety issue for many years. However, driver behavior and the interactions among variables that affect driver performance on curves is complicated and not well understood. Previous studies have investigated various factors that influence driver performance on right- or left-turn curves, but have paid little attention to the effects of foggy weather, driver experience and gender on driver performance on complex curves. A driving simulator experiment was conducted in this study to evaluate the relationships between driving behavior on a continuous S-curve and foggy weather, driver experience and gender. The process of negotiating a curve was divided into three stages consisting of a straight segment, the transition from the straight segment to the S-curve and the S-curve. The experimental results indicated that drivers tended to drive more cautiously in heavy fog, but the driving risk was still increased, especially in the transition stage from the straight segment to the S-curve. The non-professional (NP) drivers were less sensitive to the impending change in the road geometry, and less skilled in both longitudinal and lateral vehicle control than the professional drivers. The NP female drivers in particular were found to be the most vulnerable group in S-curve driving. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. The background factor of the driving compensation behavior among elderly drivers

    OpenAIRE

    Usui, Shinnosuke; Taishi, Nozomi

    2016-01-01

    The purpose of this study is to examine what factors lead to driving compensation behavior among elderly drivers, particularly focusing on the effect of self-reported driving performance, and to investigate the relationship between driving compensation behavior and traffic accidents or violations. After analyzing 237 elderly drivers, the results showed that whereas self-reported driving performances influenced driving compensation behaviors, the relationship between self-reported driving perf...

  19. The Drivers of Success in Business Model Transformation

    Directory of Open Access Journals (Sweden)

    Nenad Savič

    2016-01-01

    Full Text Available Existing empirical literature on business models is still inconclusive about the key drivers of successful business model transformation. The paper explores this issue by using a single longitudinal case study design in combination with grounded theory approach on a medium-sized, high-tech and globally oriented company. Based on on-site visits, interviews and secondary documentation data analysis, the study identifies six generic drivers of successful business model transformation: transformational leadership, discovery driven decision-making, industry improvement – customer specific orientation, content-oriented communication, self-initiative collaborators, and phased separation strategy. The new drivers supplement our existing knowledge on how successful transformation takes place and add to existing drivers, while extensive discussion of their implications may help the managers to execute business transformations more effectively.

  20. Testing a structural model of young driver willingness to uptake Smartphone Driver Support Systems.

    Science.gov (United States)

    Kervick, Aoife A; Hogan, Michael J; O'Hora, Denis; Sarma, Kiran M

    2015-10-01

    There is growing interest in the potential value of using phone applications that can monitor driver behaviour (Smartphone Driver Support Systems, 'SDSSs') in mitigating risky driving by young people. However, their value in this regard will only be realised if young people are willing to use this technology. This paper reports the findings of a study in which a novel structural model of willingness to use SDSSs was tested. Grounded in the driver monitoring and Technology Acceptance (TA) research literature, the model incorporates the perceived risks and gains associated with potential SDSS usage and additional social cognitive factors, including perceived usability and social influences. A total of 333 smartphone users, aged 18-24, with full Irish driving licenses completed an online questionnaire examining willingness or Behavioural Intention (BI) to uptake a SDSS. Following exploratory and confirmatory factor analyses, structural equation modelling indicated that perceived gains and social influence factors had significant direct effects on BI. Perceived risks and social influence also had significant indirect effects on BI, as mediated by perceived gains. Overall, this model accounted for 72.5% of the variance in willingness to uptake SDSSs. Multi-group structural models highlighted invariance of effects across gender, high and low risk drivers, and those likely or unlikely to adopt novel phone app technologies. These findings have implications for our understanding of the willingness of young drivers to adopt and use SDSSs, and highlight potential factors that could be targeted in behavioural change interventions seeking to improve usage rates. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Predicting Driver Behavior during the Yellow Interval Using Video Surveillance

    Directory of Open Access Journals (Sweden)

    Juan Li

    2016-12-01

    Full Text Available At a signalized intersection, drivers must make a stop/go decision at the onset of the yellow signal. Incorrect decisions would lead to red light running (RLR violations or crashes. This study aims to predict drivers’ stop/go decisions and RLR violations during yellow intervals. Traffic data such as vehicle approaching speed, acceleration, distance to the intersection, and occurrence of RLR violations are gathered by a Vehicle Data Collection System (VDCS. An enhanced Gaussian Mixture Model (GMM is used to extract moving vehicles from target lanes, and the Kalman Filter (KF algorithm is utilized to acquire vehicle trajectories. The data collected from the VDCS are further analyzed by a sequential logit model, and the relationship between drivers’ stop/go decisions and RLR violations is identified. The results indicate that the distance of vehicles to the stop line at the onset of the yellow signal is an important predictor for both drivers’ stop/go decisions and RLR violations. In addition, vehicle approaching speed is a contributing factor for stop/go decisions. Furthermore, the accelerations of vehicles after the onset of the yellow signal are positively related to RLR violations. The findings of this study can be used to predict the probability of drivers’ RLR violations and improve traffic safety at signalized intersections.

  2. Modeling safety risk perception due to mobile phone distraction among four wheeler drivers

    Directory of Open Access Journals (Sweden)

    Raghunathan Rajesh

    2017-04-01

    Full Text Available Nowadays, there is an increasing trend in the use of information and communication technology devices in new vehicles. Due to these increasing service facilities, driver distraction has become a major concern for transportation safety. To reduce safety risks, it is crucial to understand how distracting activities affect driver behavior at different levels of vehicle control. The objective of this work is to understand how the vehicle and driver characteristics influence mobile phone usage while driving and associated risk perception of road safety incidents. Based on literature review, a man–machine framework for distracted driving and a mobile phone distraction model is presented. The study highlights the findings from a questionnaire survey conducted in Kerala, India. The questionnaire uses a 5-point Likert scale. Responses from 1203 four-wheeler drivers are collected using random sampling approach. The questionnaire items associated with three driver-drive characteristics are: (i Human Factors (age, experience, emotional state, behavior of driver, (ii Driver space (meter, controls, light, heat, steering, actuators of vehicle, (iii Driving conditions (speed, distance, duration, traffic, signals. This mobile phone distraction model is tested using structural equation modeling procedure. The study indicates that among the three characteristics, ‘Human Factors’ has the highest influence on perceived distraction due to mobile phones. It is also observed that safety risk perception due to mobile phone usage while driving is moderate. The practical relevance of the study is to place emphasis on behavior-based controls and to focus on strategies leveraging perception of distraction due to mobile phones while driving.

  3. Executive report : toll roads, toll rates, and driver behavior.

    Science.gov (United States)

    2012-12-01

    State and federal research has examined toll roads and attempted to identify methods to make toll roads a more attractive option for drivers. Researchers examined various views of toll road transactions and concluded: : Truckers and trucking comp...

  4. An extended continuum model accounting for the driver's timid and aggressive attributions

    International Nuclear Information System (INIS)

    Cheng, Rongjun; Ge, Hongxia; Wang, Jufeng

    2017-01-01

    Considering the driver's timid and aggressive behaviors simultaneously, a new continuum model is put forwarded in this paper. By applying the linear stability theory, we presented the analysis of new model's linear stability. Through nonlinear analysis, the KdV–Burgers equation is derived to describe density wave near the neutral stability line. Numerical results verify that aggressive driving is better than timid act because the aggressive driver will adjust his speed timely according to the leading car's speed. The key improvement of this new model is that the timid driving deteriorates traffic stability while the aggressive driving will enhance traffic stability. The relationship of energy consumption between the aggressive and timid driving is also studied. Numerical results show that aggressive driver behavior can not only suppress the traffic congestion but also reduce the energy consumption. - Highlights: • A new continuum model is developed with the consideration of the driver's timid and aggressive behaviors simultaneously. • Applying the linear stability theory, the new model's linear stability is obtained. • Through nonlinear analysis, the KdV–Burgers equation is derived. • The energy consumption for this model is studied.

  5. An extended continuum model accounting for the driver's timid and aggressive attributions

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Rongjun; Ge, Hongxia [Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211 (China); Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing 210096 (China); National Traffic Management Engineering and Technology Research Centre Ningbo University Sub-centre, Ningbo 315211 (China); Wang, Jufeng, E-mail: wjf@nit.zju.edu.cn [Ningbo Institute of Technology, Zhejiang University, Ningbo 315100 (China)

    2017-04-18

    Considering the driver's timid and aggressive behaviors simultaneously, a new continuum model is put forwarded in this paper. By applying the linear stability theory, we presented the analysis of new model's linear stability. Through nonlinear analysis, the KdV–Burgers equation is derived to describe density wave near the neutral stability line. Numerical results verify that aggressive driving is better than timid act because the aggressive driver will adjust his speed timely according to the leading car's speed. The key improvement of this new model is that the timid driving deteriorates traffic stability while the aggressive driving will enhance traffic stability. The relationship of energy consumption between the aggressive and timid driving is also studied. Numerical results show that aggressive driver behavior can not only suppress the traffic congestion but also reduce the energy consumption. - Highlights: • A new continuum model is developed with the consideration of the driver's timid and aggressive behaviors simultaneously. • Applying the linear stability theory, the new model's linear stability is obtained. • Through nonlinear analysis, the KdV–Burgers equation is derived. • The energy consumption for this model is studied.

  6. THE RELATION BETWEEN DRIVER BEHAVIOR AND INTELLIGENT TRANSPORT SYSTEM

    Directory of Open Access Journals (Sweden)

    Alica Kalašová

    2017-12-01

    Full Text Available The main objective of Slovakia’s transport policy is to reduce the number of traffic accidents and increase safety on our roads. Implementation of intelligent transport systems presents one of the possibilities how to meet this goal. Acceptance of these systems by motor vehicle drivers and other road traffic participants is necessary in order for them to fulfill their purpose. Only if the drivers will accept intelligent transport systems, it is possible to flexibly and effectively manage road traffic flexibly and effectively. From the perspective of a driver it concerns, in particular, the possibility of using alternative routes when traffic accidents or other obstacles occurs on the route that would significantly affect the continuity and safety of road traffic. Thanks to these technologies, it is possible to choose the appropriate route while driving, of course based on the criterion, which the driver considers the most important during the transport from origin to destination (driving time, distance from origin to destination, fuel consumption, quality of infrastructure. Information isare provided to the driver through variable message signs or directly in the vehicle (RDS-TMC. Another advantage of intelligent transport systems is a positive impact on psychological well-being of the driver while driving. Additional information about the possible obstacles, weather conditions and dangerous situations that occur on the roads as well as alternative routes are provided to the driver well in advance. This paper is mainly focused on how the drivers perceive the influence of intelligent transport systems in Žilina region.

  7. Green Driver: Travel Behaviors Revisited on Fuel Saving and Less Emission

    Directory of Open Access Journals (Sweden)

    Nurul Hidayah Muslim

    2018-01-01

    Full Text Available Road transportation is the main energy consumer and major contributor of ever-increasing hazardous emissions. Transportation professionals have raised the idea of applying the green concept in various areas of transportation, including green highways, green vehicles and transit-oriented designs, to tackle the negative impact of road transportation. This research generated a new dimension called the green driver to remediate urgently the existing driving assessment models that have intensified emissions and energy consumption. In this regard, this study aimed to establish the green driver’s behaviors related to fuel saving and emission reduction. The study has two phases. Phase one involves investigating the driving behaviors influencing fuel saving and emission reduction through a systematic literature review and content analysis, which identified twenty-one variables classified into four clusters. These clusters included the following: (i FEf1, which is driving style; (ii FEf2, which is driving behavior associated with vehicle transmission; (iii FEf3, which is driving behavior associated with road design and traffic rules; and (iv FEf4, which is driving behavior associated with vehicle operational characteristics. The second phase involves validating phase one findings by applying the Grounded Group Decision Making (GGDM method. The results of GGDM have established seventeen green driving behaviors. The study conducted the Green Value (GV analysis for each green behavior on fuel saving and emission reduction. The study found that aggressive driving (GV = 0.16 interferes with the association between fuel consumption, emission and driver’s personalities. The research concludes that driver’s personalities (including physical, psychological and psychosocial characteristics have to be integrated for advanced in-vehicle driver assistance system and particularly, for green driving accreditation.

  8. Driver's views and behaviors about safety in China--what do they NOT know about driving?

    Science.gov (United States)

    Zhang, Wei; Huang, Yueng-Hsiang; Roetting, Matthias; Wang, Ying; Wei, Hua

    2006-01-01

    Driving safety has become an extremely severe problem in China due to rapid motorization. Unless more effective measures are taken, the fatality risk and the total fatalities due to road traffic accidents are expected to continue to increase. Therefore, focus group discussions were conducted to explore driver attitudes and safe driver characteristics. The results were then compared with a similar study conducted with US drivers. Although similarities were found, differences were of more importance. The Chinese drivers concentrate more on driving skills and capabilities, whereas the US drivers concentrate more on practical safe driving guidelines. Then direct field observations were conducted for the Chinese drivers to empirically investigate the issues discovered. The use of safety belts, running lights, headlights, and turn signals were observed to investigate the drivers' behaviors. Results show that the safety belt use ratio is about 64%, running light use is nearly zero during rainy and snowy weather, headlights use after sunset is substantially delayed, and only about 40% of drivers use turn signals to indicate their intention to change lanes. These findings indicate that the authorities need to take appropriate countermeasures to change the views of the Chinese drivers regarding driving safety and their unsafe driving behaviors. Improvement of training content and methods as well as police enforcement would be recommended.

  9. Conditions that influence drivers' yielding behavior at uncontrolled crossings and intersections with traffic signal controls.

    Science.gov (United States)

    2015-08-31

    There is a dearth of studies on how pedestrian who are blind might positively influence driver yielding in different travel situations. This project assessed common pedestrian behaviors (head turning, holding a cane, taking a step, holding up a hand,...

  10. Racial Bias in Drivers' Yielding Behavior at Crosswalks : Understanding the Effect

    Science.gov (United States)

    2017-10-01

    This project explores social identity factors (race and gender) that influence drivers' behavior in interactions with pedestrians at crosswalks. One dangerous potential point of conflict for pedestrians within the transportation system is interaction...

  11. Taxonomy of Older Driver Behaviors and Crash Risk : with Appendices A and B

    Science.gov (United States)

    2012-02-01

    This projects objectives were to identify risky behaviors, driving habits, and exposure patterns that have been shown to increase the likelihood of crash involvement among older drivers; and to classify these crash-contributing factors according t...

  12. Traffic modelling validation of advanced driver assistance systems

    NARCIS (Netherlands)

    Tongeren, R. van; Gietelink, O.J.; Schutter, B. de; Verhaegen, M.

    2007-01-01

    This paper presents a microscopic traffic model for the validation of advanced driver assistance systems. This model describes single-lane traffic and is calibrated with data from a field operational test. To illustrate the use of the model, a Monte Carlo simulation of single-lane traffic scenarios

  13. Driving Behaviors in Iran: A Descriptive Study Among Drivers of Mashhad City in 2014

    Science.gov (United States)

    Bazzaz, Mojtaba Mousavi; Zarifian, Ahmadreza; Emadzadeh, Maryam; Vakili, Veda

    2015-01-01

    Background: Driver-related behaviors are substantial causes for motor vehicle accidents. It has been estimated that about 95% of all accidents are due to driver-related dangerous behaviors and approximately 60% of accidents are directly caused by driving behaviors. The aim of this study was to assess driving behaviors and its possible related factors among drivers in Mashhad city, Iran. Method: In a cross-sectional design, a total number of 514 drivers in Mashhad, Iran Surveyed. Manchester driver behavior questionnaire with 50 questions evaluated dangerous driving behaviors in 4 categories “aggressive violations”, “ordinary violations”, “errors” and “lapses”. Results: In this study, the median age of drivers was 31. Besides, 58.2% of men mentioned having a history of driving accident. Our study indicated smoking and alcohol drinking as risk factors of having more accidents. Hookah abuse is a predictor of aggressive violations and errors. Conclusion: This is the first study to assess the relation of personal car and its market value with the likelihood of having accidents. Due to major influences of driving fines, cigarette smoking, alcohol consumption and addiction on violations and errors, we recommend pivotal measures to be taken by road safety practitioners regarding driving surveillance. PMID:26153202

  14. Study on driver model for hybrid truck based on driving simulator experimental results

    Directory of Open Access Journals (Sweden)

    Dam Hoang Phuc

    2018-04-01

    Full Text Available In this paper, a proposed car-following driver model taking into account some features of both the compensatory and anticipatory model representing the human pedal operation has been verified by driving simulator experiments with several real drivers. The comparison between computer simulations performed by determined model parameters with the experimental results confirm the correctness of this mathematical driver model and identified model parameters. Then the driver model is joined to a hybrid vehicle dynamics model and the moderate car following maneuver simulations with various driver parameters are conducted to investigate influences of driver parameters on vehicle dynamics response and fuel economy. Finally, major driver parameters involved in the longitudinal control of drivers are clarified. Keywords: Driver model, Driver-vehicle closed-loop system, Car Following, Driving simulator/hybrid electric vehicle (B1

  15. Driver sleepiness, fatigue, careless behavior and risk of motor vehicle crash and injury: Population based case and control study

    Directory of Open Access Journals (Sweden)

    Abdulbari Bener

    2017-10-01

    Conclusion: The current study confirmed that drivers with chronic fatigue, acute sleepiness, and careless driver behavior may significantly increases the risk of road crash which can be lead to serious injury.

  16. Towards a definition of safety for individual drivers lane behavior

    NARCIS (Netherlands)

    van Loon, R.J.

    2012-01-01

    To assess lateral control performance in drivers, lane behaviour indicators such as the mean lane position, standard deviation of lane position and time-to-line-crossing are the most frequently used measures. For lane position, the commonly accepted (qualitative) proposition is that increased lane

  17. Driver behavior and accident frequency in school zones: Assessing the impact of sign saturation.

    Science.gov (United States)

    Strawderman, Lesley; Rahman, Md Mahmudur; Huang, Yunchen; Nandi, Apurba

    2015-09-01

    Based on the models of human information processing, if a driver observes too many of the same signs, he or she may no longer pay attention to those signs. In the case of school zones, this expected effect may lead to non-compliance to posted speeds, negatively impacting safety around nearby schools. This study aims to investigate the effect of the number of nearby school zones on driver behavior (vehicle speed and compliance) and accident frequency. As a measure of the density of school zones, this study introduced and defined a new term sign saturation and presented a methodology to calculate sign saturation for school zones. Results found a significant effect of sign saturation on vehicle speed, compliance, and accident frequency. This study also examined the speeding behavior in school zones for different time of the day and day of the week. Results found that speeding was more prevalent in the early mornings and during the weekends. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. How accurately do drivers evaluate their own driving behavior? An on-road observational study.

    Science.gov (United States)

    Amado, Sonia; Arıkan, Elvan; Kaça, Gülin; Koyuncu, Mehmet; Turkan, B Nilay

    2014-02-01

    Self-assessment of driving skills became a noteworthy research subject in traffic psychology, since by knowing one's strenghts and weaknesses, drivers can take an efficient compensatory action to moderate risk and to ensure safety in hazardous environments. The current study aims to investigate drivers' self-conception of their own driving skills and behavior in relation to expert evaluations of their actual driving, by using naturalistic and systematic observation method during actual on-road driving session and to assess the different aspects of driving via comprehensive scales sensitive to different specific aspects of driving. 19-63 years old male participants (N=158) attended an on-road driving session lasting approximately 80min (45km). During the driving session, drivers' errors and violations were recorded by an expert observer. At the end of the driving session, observers completed the driver evaluation questionnaire, while drivers completed the driving self-evaluation questionnaire and Driver Behavior Questionnaire (DBQ). Low to moderate correlations between driver and observer evaluations of driving skills and behavior, mainly on errors and violations of speed and traffic lights was found. Furthermore, the robust finding that drivers evaluate their driving performance as better than the expert was replicated. Over-positive appraisal was higher among drivers with higher error/violation score and with the ones that were evaluated by the expert as "unsafe". We suggest that the traffic environment might be regulated by increasing feedback indicators of errors and violations, which in turn might increase the insight into driving performance. Improving self-awareness by training and feedback sessions might play a key role for reducing the probability of risk in their driving activity. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Validation of the Driver Stress Inventory in China: Relationship with dangerous driving behaviors.

    Science.gov (United States)

    Qu, Weina; Zhang, Qian; Zhao, Wenguo; Zhang, Kan; Ge, Yan

    2016-02-01

    Perceived stress while driving may affect how critical driving events are handled. The current study validates a Chinese version of the Driver Stress Inventory (DSI) and explores its correlation with dangerous driving behaviors and gender. A sample of 246 drivers completed the Chinese version of the DSI and the Driver Behavior Questionnaire (DBQ). We also evaluated specific sociodemographic variables and traffic violations (including speeding, violating traffic signs or markings, driving while intoxicated, running a red light, and incurring penalty points). A confirmatory factor analysis (CFA) verified the DSI's internal structure. The DSI was also validated using questionnaires related to the DBQ, self-reported traffic accidents and violations, and sociodemographic characteristics. First, all of the DSI dimensions were moderately or weakly correlated with the DBQ subscales. Second, aggression, hazard monitoring and fatigue were weakly correlated with minor accidents. Third, drivers who had sped and violated traffic signs during the previous three years reported higher aggression and thrill seeking, while drivers who had violated traffic signs or markings during the previous three years reported decreased hazard monitoring compared with non-offenders. Finally, there were significant gender differences in driver stress. The Chinese version of the DSI will be useful for classifying and diagnosing drivers who may be at an increased risk for stress reactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Continuous traffic flow modeling of driver support systems in multiclass traffic with intervehicle communication and drivers in the loop

    NARCIS (Netherlands)

    Tampere, C.; Hoogendoorn, S.P.; van Arem, Bart

    2009-01-01

    This paper presents a continuous traffic-flow model for the explorative analysis of advanced driver-assistance systems (ADASs). Such systems use technology (sensors and intervehicle communication) to support the task of the driver, who retains full control over the vehicle. Based on a review of

  1. Sleep, Dietary, and Exercise Behavioral Clusters Among Truck Drivers With Obesity: Implications for Interventions.

    Science.gov (United States)

    Olson, Ryan; Thompson, Sharon V; Wipfli, Brad; Hanson, Ginger; Elliot, Diane L; Anger, W Kent; Bodner, Todd; Hammer, Leslie B; Hohn, Elliot; Perrin, Nancy A

    2016-03-01

    The objectives of the study were to describe a sample of truck drivers, identify clusters of drivers with similar patterns in behaviors affecting energy balance (sleep, diet, and exercise), and test for cluster differences in health safety, and psychosocial factors. Participants' (n = 452, body mass index M = 37.2, 86.4% male) self-reported behaviors were dichotomized prior to hierarchical cluster analysis, which identified groups with similar behavior covariation. Cluster differences were tested with generalized estimating equations. Five behavioral clusters were identified that differed significantly in age, smoking status, diabetes prevalence, lost work days, stress, and social support, but not in body mass index. Cluster 2, characterized by the best sleep quality, had significantly lower lost workdays and stress than other clusters. Weight management interventions for drivers should explicitly address sleep, and may be maximally effective after establishing socially supportive work environments that reduce stress exposures.

  2. Quantitative analysis of the relationship between driver`s behavior and vehicle motion; Sharyo unten ni taisuru untensha no kyodo no teiryoka bunseki ni tsuite

    Energy Technology Data Exchange (ETDEWEB)

    Nakagawa, H; Matsuura, Y [Osaka Sangyo University, Osaka (Japan); Masuda, T

    1997-10-01

    In order to study the subject of driving safety about the human-vehicle interaction, driver`s maneuvering behavior was shot by CCD-cameras installed in a cabin and the motion of traveling vehicle was simultaneously taken by VTR-cameras set on the test course. These pictures were analyzed using the three-dimensional image processing system (Peak Motus system). Consequently, this system was effectively able to use for these measurements and analysis and introduced the correlation between the vehicle movement and the driver`s action. 4 refs., 12 figs., 2 tabs.

  3. Drivers of stability of climate coalitions in the STACO model

    NARCIS (Netherlands)

    Dellink, R.B.

    2011-01-01

    This paper investigates which drivers affect the formation and stability of international climate agreements (ICAs). The applied model STACO is used to project costs and benefits of an international agreement on climate change mitigation activities. The simulation results show that an

  4. Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

    NARCIS (Netherlands)

    Wang, M.

    2014-01-01

    This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

  5. Behavioral Impact of Graduated Driver Licensing on Teenage Driving Risk and Exposure1

    Science.gov (United States)

    Karaca-Mandic, Pinar; Ridgeway, Greg

    2009-01-01

    Graduated Driver Licensing (GDL) is a critical policy tool for potentially improving teenage driving while reducing teen accident exposure. While previous studies demonstrated that GDL reduces teenage involvement in fatal crashes, much remains unanswered. We explore the mechanisms through which GDL influences accident rates as well as its long term effectiveness on teen driving. In particular, we investigate; 1) whether GDL policies improve teenage driving behavior, or simply reduce teenage prevalence on the roads; 2) whether GDL exposed teens become better drivers in later years. We employ a unique data source, the State Data System, which contains all police reported accidents (fatal and non-fatal) during 1990–2005 for twelve states. We estimate a structural model that separately identifies GDL s effect on relative teenage prevalence and relative teenage riskiness. Identification of the model is driven by the relative numbers of crashes between two teenagers, two adults, or a teenager and an adult. We find that the GDL policies reduce the number of 15–17 year-old accidents by limiting the amount of teenage driving rather than by improving teenage driving. This prevalence reduction primarily occurs at night and stricter GDL policies, especially those with nighttime driving restrictions, are the most effective. Finally, we find that teen driving quality does not improve ex-post GDL exposure. PMID:19942310

  6. Ecodriving acceptance : an experimental study on anticipation behavior of truck drivers

    NARCIS (Netherlands)

    Thijssen, R.J.T.G.; Hofman, T.; Ham, J.R.C.

    2014-01-01

    In this paper, it is researched to what extend truck drivers are willing to improve their anticipation behavior. For the purpose of this research, anticipation behavior is characterized by anticipation distance: the distance to a stopping point (e.g. roundabout), at which the accelerator pedal is

  7. Prospect theory based estimation of drivers' risk attitudes in route choice behaviors.

    Science.gov (United States)

    Zhou, Lizhen; Zhong, Shiquan; Ma, Shoufeng; Jia, Ning

    2014-12-01

    This paper applied prospect theory (PT) to describe drivers' route choice behavior under Variable Message Sign (VMS), which presented visual traffic information to assist them to make route choice decisions. A quite rich empirical data from questionnaire and field spot was used to estimate parameters of PT. In order to make the parameters more realistic with drivers' attitudes, they were classified into different types by significant factors influencing their behaviors. Based on the travel time distribution of alternative routes and route choice results from questionnaire, the parameterized value function of each category was figured out, which represented drivers' risk attitudes and choice characteristics. The empirical verification showed that the estimates were acceptable and effective. The result showed drivers' risk attitudes and route choice characteristics could be captured by PT under real-time information shown on VMS. For practical application, once drivers' route choice characteristics and parameters were identified, their route choice behavior under different road conditions could be predicted accurately, which was the basis of traffic guidance measures formulation and implementation for targeted traffic management. Moreover, the heterogeneous risk attitudes among drivers should be considered when releasing traffic information and regulating traffic flow. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Perturbation and Stability Analysis of the Multi-Anticipative Intelligent Driver Model

    Science.gov (United States)

    Chen, Xi-Qun; Xie, Wei-Jun; Shi, Jing; Shi, Qi-Xin

    This paper discusses three kinds of IDM car-following models that consider both the multi-anticipative behaviors and the reaction delays of drivers. Here, the multi-anticipation comes from two ways: (1) the driver is capable of evaluating the dynamics of several preceding vehicles, and (2) the autonomous vehicles can obtain the velocity and distance information of several preceding vehicles via inter-vehicle communications. In this paper, we study the stability of homogeneous traffic flow. The linear stability analysis indicates that the stable region will generally be enlarged by the multi-anticipative behaviors and reduced by the reaction delays. The temporal amplification and the spatial divergence of velocities for local perturbation are also studied, where the results further prove this conclusion. Simulation results also show that the multi-anticipative behaviors near the bottleneck will lead to a quicker backwards propagation of oscillations.

  9. Driver Behavior During Overtaking Maneuvers from the 100-Car Naturalistic Driving Study.

    Science.gov (United States)

    Chen, Rong; Kusano, Kristofer D; Gabler, Hampton C

    2015-01-01

    Lane changes with the intention to overtake the vehicle in front are especially challenging scenarios for forward collision warning (FCW) designs. These overtaking maneuvers can occur at high relative vehicle speeds and often involve no brake and/or turn signal application. Therefore, overtaking presents the potential of erroneously triggering the FCW. A better understanding of driver behavior during lane change events can improve designs of this human-machine interface and increase driver acceptance of FCW. The objective of this study was to aid FCW design by characterizing driver behavior during lane change events using naturalistic driving study data. The analysis was based on data from the 100-Car Naturalistic Driving Study, collected by the Virginia Tech Transportation Institute. The 100-Car study contains approximately 1.2 million vehicle miles of driving and 43,000 h of data collected from 108 primary drivers. In order to identify overtaking maneuvers from a large sample of driving data, an algorithm to automatically identify overtaking events was developed. The lead vehicle and minimum time to collision (TTC) at the start of lane change events was identified using radar processing techniques developed in a previous study. The lane change identification algorithm was validated against video analysis, which manually identified 1,425 lane change events from approximately 126 full trips. Forty-five drivers with valid time series data were selected from the 100-Car study. From the sample of drivers, our algorithm identified 326,238 lane change events. A total of 90,639 lane change events were found to involve a closing lead vehicle. Lane change events were evenly distributed between left side and right side lane changes. The characterization of lane change frequency and minimum TTC was divided into 10 mph speed bins for vehicle travel speeds between 10 and 90 mph. For all lane change events with a closing lead vehicle, the results showed that drivers change

  10. Effects of passengers on bus driver celeration behavior and incident prediction.

    Science.gov (United States)

    Af Wåhlberg, A E

    2007-01-01

    Driver celeration (speed change) behavior of bus drivers has previously been found to predict their traffic incident involvement, but it has also been ascertained that the level of celeration is influenced by the number of passengers carried as well as other traffic density variables. This means that the individual level of celeration is not as well estimated as could be the case. Another hypothesized influence of the number of passengers is that of differential quality of measurements, where high passenger density circumstances are supposed to yield better estimates of the individual driver component of celeration behavior. Comparisons were made between different variants of the celeration as predictor of traffic incidents of bus drivers. The number of bus passengers was held constant, and cases identified by their number of passengers per kilometer during measurement were excluded (in 12 samples of repeated measurements). After holding passengers constant, the correlations between celeration behavior and incident record increased very slightly. Also, the selective prediction of incident record of those drivers who had had many passengers when measured increased the correlations even more. The influence of traffic density variables like the number of passengers have little direct influence on the predictive power of celeration behavior, despite the impact upon absolute celeration level. Selective prediction on the other hand increased correlations substantially. This unusual effect was probably due to how the individual propensity for high or low celeration driving was affected by the number of stops made and general traffic density; differences between drivers in this respect were probably enhanced by the denser traffic, thus creating a better estimate of the theoretical celeration behavior parameter C. The new concept of selective prediction was discussed in terms of making estimates of the systematic differences in quality of the individual driver data.

  11. Effects of personality on risky driving behavior and accident involvement for Chinese drivers.

    Science.gov (United States)

    Yang, Jiaoyan; Du, Feng; Qu, Weina; Gong, Zhun; Sun, Xianghong

    2013-01-01

    Motor vehicle accidents are the leading cause of injury-related fatalities in China and pose the most serious threat to driving safety. Driver personality is considered as an effective predictor for risky driving behavior and accident liability. Previous studies have focused on the relationship between personality and risky driving behavior, but only a few of them have explored the effects of personality variables on accident involvement. In addition, few studies have examined the effects of personality on Chinese drivers' risky driving and accident involvement. The present study aimed to examine the effects of personality variables on Chinese drivers' unsafe driving behaviors and accident involvement. Two hundred and twenty-four Chinese drivers aged 20 to 50 were required to complete questionnaires assessing their personality traits (anger, sensation-seeking, altruism, and normlessness), risky driving behaviors (aggressive violations, ordinary violations), and accident involvement (all accidents, serious accidents, at-fault accidents). Multivariate regression analyses, adjusting for gender, age, and overall mileage, were conducted to identify the personality traits related to risky driving behaviors and accident involvement. Participants' personality traits were found to be significantly correlated with both risky driving behavior and accident involvement. Specifically, the traits of anger and normlessness were effective predictors for aggressive violations. The traits of anger, sensation-seeking, normlessness, and altruism were effective predictors for ordinary violations. Moreover, altruism and normlessness were significant predictors for the total number of accidents participants had during the past 3 years. Consistent with previous studies, the present study revealed that personality traits play an important role in predicting Chinese drivers' risky driving behaviors. In addition, Chinese drivers' personality characteristics were also associated with accident

  12. Have drivers at alcohol outlets changed their behavior after the new traffic law?

    Directory of Open Access Journals (Sweden)

    Raquel B. De Boni

    2014-03-01

    Full Text Available Objective: In an attempt to reduce high levels of traffic crashes, a new legislation was approved in Brazil in 2008. This study aimed to assess behavioral change among drivers who had drunk at alcohol outlets (AO after implementation of the law. Method: A three-stage probability sampling survey was conducted in Porto Alegre, state of Rio Grande do Sul, Brazil. Individuals seen leaving AOs after drinking were approached (n=3,018. Selected drivers (n=683 answered a structured interview, were breathalyzed, and had saliva specimens collected for drug screening. Results: Overall, 60.3% (SE 4.5 of drivers reported they did not change their behavior. Among those who reported behavioral changes, most reported drinking less as their main strategy toward safer driving behavior. Variables independently associated with behavior change included having drunk at a high outlet density area (odds ratio [OR] 1.7 [1.1-2.8] and having a favorable opinion about the law (OR 4.3 [2.1-8.9]. Conclusions: Our findings suggest that awareness of the law has not been enough to promote behavioral change. As most drivers had a favorable opinion of the law and this variable was found to be the strongest predictor of behavior change, efforts to better integrate education and enforcement seem to be pivotal and might be well received by the population.

  13. High-risk behaviors and experiences with traffic law among night drivers in Curitiba, Brazil.

    Science.gov (United States)

    Ulinski, Sandra L; Moysés, Simone T; Werneck, Renata I; Moysés, Samuel J

    2016-01-08

    To explore high-risk behaviors and experiences with traffic law among night drivers in Curitiba, Brazil. Data from 398 drivers on sociodemographic parameters, high-risk behaviors, experiences with traffic law, and traffic law violations were collected through interviews conducted at sobriety checkpoints. Exploratory-descriptive and analytical statistics were used. The mean age of the participants was 32.6±11.2 years (range, 18 to 75 years). Half of the drivers reported having driven after drinking in the last year, predominantly single men aged 18 to 29 years who drive cars and drink alcohol frequently. Only 55% of the drivers who had driven after drinking in the last year self-reported some concern about being detected in a police operation. A significant association was found between sociodemographic variables and behavior, which can help tailor public interventions to a specific group of drivers: young men who exhibit high-risk behaviors in traffic, such as driving after drinking alcohol, some of whom report heavy alcohol consumption. This group represents a challenge for educational and enforcement interventions, particularly because they admit to violating current laws and have a low perception of punishment due to the low risk of being detected by the police.

  14. High-risk behaviors and experiences with traffic law among night drivers in Curitiba, Brazil

    Directory of Open Access Journals (Sweden)

    Sandra L. Ulinski

    2016-01-01

    Full Text Available Objective: To explore high-risk behaviors and experiences with traffic law among night drivers in Curitiba, Brazil. Method: Data from 398 drivers on sociodemographic parameters, high-risk behaviors, experiences with traffic law, and traffic law violations were collected through interviews conducted at sobriety checkpoints. Exploratory-descriptive and analytical statistics were used. Results: The mean age of the participants was 32.6±11.2 years (range, 18 to 75 years. Half of the drivers reported having driven after drinking in the last year, predominantly single men aged 18 to 29 years who drive cars and drink alcohol frequently. Only 55% of the drivers who had driven after drinking in the last year self-reported some concern about being detected in a police operation. Conclusions: A significant association was found between sociodemographic variables and behavior, which can help tailor public interventions to a specific group of drivers: young men who exhibit high-risk behaviors in traffic, such as driving after drinking alcohol, some of whom report heavy alcohol consumption. This group represents a challenge for educational and enforcement interventions, particularly because they admit to violating current laws and have a low perception of punishment due to the low risk of being detected by the police.

  15. Risky behavior of drivers of motorized two wheeled vehicles in India.

    Science.gov (United States)

    Dandona, Rakhi; Kumar, G Anil; Dandona, Lalit

    2006-01-01

    Motorized two-wheeled vehicles (MTV) account for a large proportion of road traffic in India and the riders of these vehicles have a high risk of road traffic injuries. We report on the availability of drivers licenses, use of a helmet, driver behavior, and condition of vehicles for MTV drivers in Hyderabad, a city in India Drivers of a MTV aged >16 years were interviewed at petrol filling stations There were 4,183 MTV drivers who participated in the study. Four hundred sixty one (11%; 95% CI 9.7-12.3%) drivers had not obtained a drivers license and 798 (21.4%) had obtained a license without taking the mandatory driving test. Two thousand nine hundred twenty (69.8%; 95% CI 67.9-71.7%) drivers reported no/very occasional use of a helmet, the significant predictors of which included that those driving borrowed a MTV (odds ratio 7.90; 95% CI 3.40-18.40) or driving moped/scooterette/scooter as compared with motorcycle (3.32; 2.76-3.98), lower education (3.10; 2.66-3.61), age >45 years (2.41; 1.63-3.57), and males (1.57; 1.16-2.13). Two thousand five hundred and eight (59.9%) drivers reported committing a traffic law violation at least once within the last 3 months. Overall, 1,222 (29.2%) drivers reported ever being caught by traffic police for a traffic law violation with data on violations available for 1,205 of these drivers, of whom 680 (56.4%) paid a fine, 310 (25.7%) paid by bribe, and 215 (17.8%) made no payment. The proportion of those who did not make payment for committed violation was significantly higher among females (46.8%) than males (16.3%). Two thousand fifty two (49%) of all MTVs had no rearview mirror These data suggest the need to enact and enforce policy interventions for improving the drivers license system, mandatory use of a helmet, effective traffic law enforcement, and ensuring good vehicle condition to reduce the risk factors that potentially contribute to mortality and morbidity in road traffic crashes in MTV drivers in Indian cities.

  16. University - industry collaborations: models, drivers and cultures.

    Science.gov (United States)

    Ehrismann, Dominic; Patel, Dhavalkumar

    2015-01-01

    The way academic institutions and pharmaceutical companies have been approaching collaborations has changed significantly in recent years. A multitude of interaction models were tested and critical factors that drive successful collaborations have been proposed. Based on this experience the current consensus in the pharmaceutical industry is to pursue one of two strategies: an open innovation approach to source discoveries wherever they occur, or investing selectively into scientific partnerships that churn out inventions that can be translated from bench to bedside internally. While these strategies may be intuitive, to form and build sustainable relationships between academia and large multinational healthcare enterprises is proving challenging. In this article we explore some of the more testing aspects of these collaborations, approaches that various industrial players have taken and provide our own views on the matter. We found that understanding and respecting each other's organisational culture and combining the intellectual and technological assets to answer big scientific questions accelerates and improves the quality of every collaboration. Upon discussing the prevailing cooperation models in the university - industry domain, we assert that science-driven collaborations where risks and rewards are shared equally without a commercial agenda in mind are the most impactful.

  17. Effects of countdown timers on driver behavior after the yellow onset at Chinese intersections.

    Science.gov (United States)

    Long, Kejun; Han, Lee D; Yang, Qiang

    2011-10-01

    Few studies have focused on the effect of countdown timers at signalized intersections in China, where such timers are widely deployed for their perceived benefits of increased safety and capacity. This study examines the effect of countdown timers on driver behavior during the yellow interval. Signal phasing and traffic operations were videotaped at 4 comparable signalized intersections under normal conditions. Microscopic details were extracted manually at 25 Hz to yield 24 h of data on onset time of the yellow, onset time of the red, driver location and actions after the onset of the yellow, red light-running violations, etc. For comparable intersections with and without countdown timers, driver behavior measured by driver decision (stop or go) and vehicle entry time (when the vehicle crosses the stop line) were analyzed using binary logistical regression (BLR) and a nonparametric test, respectively. The results suggest that countdown timers can indeed influence driver behaviors, in terms of decisions to stop or cross the intersection as well as the distribution of vehicle entry times. There was a strong correlation between the presence of countdown timers and an increase in red light violations. Countdown timers may lead to increased entrance into the intersection during the later portions of the yellow and even the red. This alarming finding calls for further research as well as for serious consideration before the field deployment of countdown timers.

  18. Driver Behavioral Changes through Interactions with an Automatic Brake System for Collision Avoidance

    Science.gov (United States)

    Itoh, Makoto; Fujiwara, Yusuke; Inagaki, Toshiyuki

    This paper discusses driver's behavioral changes as a result of driver's use of an automatic brake system for preventing a rear-end collision from occurring. Three types of automatic brake systems are investigated in this study. Type 1 brake system applies a strong automatic brake when a collision is very imminent. Type 2 brake system initiates brake operation softly when a rear-end crash may be anticipated. Types 1 and 2 are for avoidance of a collision. Type 3 brake system, on the other hand, applies a strong automatic brake to reduce the damage when a collision can not be avoided. An experiment was conducted with a driving simulator in order to analyze the driver's possible behavioral changes. The results showed that the time headway (THW) during car following phase was reduced by use of an automatic brake system of any type. The inverse of time to collision (TTC), which is an index of the driver's brake timing, increased by use of Type 1 brake system when the deceleration rate of the lead vehicle was relatively low. However, the brake timing did not change when the drivers used Type 2 or 3 brake system. As a whole, dangerous behavioral changes, such as overreliance on a brake system, were not observed for either type of brake system.

  19. Stress-related psychosocial factors at work, fatigue, and risky driving behavior in bus rapid transport (BRT) drivers.

    Science.gov (United States)

    Useche, Sergio A; Ortiz, Viviola Gómez; Cendales, Boris E

    2017-07-01

    There is consistent scientific evidence that professional drivers constitute an occupational group that is highly exposed to work related stressors. Furthermore, several recent studies associate work stress and fatigue with unsafe and counterproductive work behaviors. This study examines the association between stress-related work conditions of Bus Rapid Transport (BRT) drivers and risky driving behaviors; and examines whether fatigue is a mechanism that mediates the association between the two. A sample of 524 male Bus Rapid Transit (BRT) operators were drawn from four transport companies in Bogotá, Colombia. The participants answered a survey which included an adapted version of the Driver Behavior Questionnaire (DBQ) for BRT operators, as well as the Effort-Reward Imbalance and Job Content Questionnaires, the Subjective Fatigue subscale of the Checklist Individual Strength (CIS) and the Need for Recovery after Work Scale (NFR). Utilizing Structural Equation Models (SEM) it was found that risky driving behaviors in BRT operators could be predicted through job strain, effort-reward imbalance and social support at work. It was also found that fatigue and need for recovery fully mediate the associations between job strain and risky driving, and between social support and risky driving, but not the association between effort/reward imbalance (ERI) and risky driving. The results of this study suggest that a) stress related working conditions (Job Strain, Social Support and ERI) are relevant predictors of risky driving in BRT operators, and b) that fatigue is the mechanism which links another kind of stress related to working conditions (job strain and low social support) with risky driving. The mechanism by which ERI increases risky driving in BRT operators remains unexplained. This research suggests that in addition to the individual centered stress-reduction occupational programs, fatigue management interventions aimed to changing some working conditions may reduce

  20. HIV infection, genital symptoms and sexual risk behavior among Indian truck drivers from a large transportation company in South India

    Directory of Open Access Journals (Sweden)

    Annie Dude

    2009-01-01

    Full Text Available Background: Sentinel surveillance conducted in the high Human Immuno-deficiency Virus (HIV prevalent state of Andhra Pradesh includes sub-populations thought to be at high-risk for HIV, but has not included truck drivers. Novel HIV prevention programs targeting this population increasingly adopt public - private partnership models. There have been no targeted studies of HIV prevalence and risk behavior among truck drivers belonging to the private sector in India. Methods: A sample of 189 truck drivers, aged between 15 and 56, were recruited from Gati Limited′s large trucking depot in Hyderabad, India. A quantitative survey instrument was conducted along with blood collection for HIV 1/2 testing. Multivariate regression models were utilized to determine predictors of HIV infection and risk behavior. Results: 2.1% of subjects were infected with HIV. Older age was protective against self-reported genital symptoms (OR = 0.77; P = 0.03, but these were more likely among those truck drivers with greater income (OR = 1.05; P = 0.02, and those who spent more time away from home (OR = 25.7; P = 0.001. Men with higher incomes also reported significantly more sex partners (OLS coefficient = 0.016 more partners / 100 rupees in monthly income, P = 0.04, as did men who spent a great deal of time away from home (OLS coefficient = 1.30, P = 0.002. Drivers were more likely to report condom use with regular partners if they had ever visited a female sex worker (OR = 6.26; P = 0.002, but married drivers exhibited decreased use of condoms with regular partners (OR = 0.14, P = 0.008. Men who had higher levels of knowledge regarding HIV and HIV preventative practices were also more likely to use condoms with regular partners (OR = 1.22, P = 0.03. Conclusion: Time away from home, urban residence, income, and marital status were the strongest correlates of genital symptoms for Sexually Transmitted Infections (STI and risk behaviors, although none were consistent

  1. Risky driving behaviors for road traffic accident among drivers in Mekele city, Northern Ethiopia

    Directory of Open Access Journals (Sweden)

    Hassen Abrahim

    2011-12-01

    Full Text Available Abstract Background Due to its perception as a disease of development, road traffic accident and related injuries tend to be under recognized as a major health problem in developing countries. However, majority of the world's fatalities on the roads occur in low income and middle income countries. Since the main cause of road traffic accident is attributed to human risky behaviors, it is important to identify significant factors for risky behaviors of drivers. Methods A quantitative cross-sectional study with a sample size of 350 drivers was conducted in April 2011. The study was conducted among Taxi, Bajaj (three tire vehicles and private owned car drivers. After proportion to size allocation for Taxi (75, Baja (103 and private owned car (172 drivers, we used systematic random sampling method to identify illegible study subjects. Data was collected with face to face interview using a pretested questioner. Univariate, bivariate and multivariate analysis was done using SPSS version 16. Results The mean age of the respondents was 28.7 (SD 9.9. Majority were 339 (96.9% males. Significant number of the study subjects 233 (66.6% had risky driving behaviors. More than a quarter 100 (28.6% had less knowledge about basic traffic signs. Majority of drivers 181 (51.7% had negative attitude towards risky driving behaviors. Significant percent of them 148 (42.3% had a habit of using mobile phone while driving vehicle and 28 (9.7% had experience of driving after drinking alcohol. All the Bajaj, 97(62.6% house car and 58(37.4% taxi unfasten their seat belt while driving. Majority 303 (86.6% followed the recommended speed limit of driving. About 66 (18.9% of them had experience of punishment or warning by traffic polices in the previous 1 year and 77 (22% ever had car accident while driving. Conclusions Drivers of secondary education and with high average monthly income were more likely to have risky driving behavior. Having supportive attitude towards risky

  2. Inferring ecological and behavioral drivers of African elephant movement using a linear filtering approach.

    Science.gov (United States)

    Boettiger, Alistair N; Wittemyer, George; Starfield, Richard; Volrath, Fritz; Douglas-Hamilton, Iain; Getz, Wayne M

    2011-08-01

    Understanding the environmental factors influencing animal movements is fundamental to theoretical and applied research in the field of movement ecology. Studies relating fine-scale movement paths to spatiotemporally structured landscape data, such as vegetation productivity or human activity, are particularly lacking despite the obvious importance of such information to understanding drivers of animal movement. In part, this may be because few approaches provide the sophistication to characterize the complexity of movement behavior and relate it to diverse, varying environmental stimuli. We overcame this hurdle by applying, for the first time to an ecological question, a finite impulse-response signal-filtering approach to identify human and natural environmental drivers of movements of 13 free-ranging African elephants (Loxodonta africana) from distinct social groups collected over seven years. A minimum mean-square error (MMSE) estimation criterion allowed comparison of the predictive power of landscape and ecological model inputs. We showed that a filter combining vegetation dynamics, human and physical landscape features, and previous movement outperformed simpler filter structures, indicating the importance of both dynamic and static landscape features, as well as habit, on movement decisions taken by elephants. Elephant responses to vegetation productivity indices were not uniform in time or space, indicating that elephant foraging strategies are more complex than simply gravitation toward areas of high productivity. Predictions were most frequently inaccurate outside protected area boundaries near human settlements, suggesting that human activity disrupts typical elephant movement behavior. Successful management strategies at the human-elephant interface, therefore, are likely to be context specific and dynamic. Signal processing provides a promising approach for elucidating environmental factors that drive animal movements over large time and spatial

  3. Traffic flow impacts of adaptive cruise control deactivation and (Re)activation with cooperative driver behavior

    NARCIS (Netherlands)

    Klunder, G.; Li, M.; Minderhoud, M.

    2009-01-01

    In 2006 in the Netherlands, a field operational test was carried out to study the effect of adaptive cruise control (ACC) and lane departure warning on driver behavior and traffic flow in real traffic. To estimate the effect for larger penetration rates, simulations were needed. For a reliable

  4. Study of unsafe behaviors among city bus drivers in Hamadan, 2011

    Directory of Open Access Journals (Sweden)

    2012-01-01

    Conclusion: Because of high percent of unsafe acts and considering importance of its consequences in drivers, reducing unsafe acts trough investment and utilization of behavioral safety principles is required. In this regard, holding educational careers are suggested to increasing driver’s awareness.

  5. Planning for a Nondriving Future: Behaviors and Beliefs Among Middle-Aged and Older Drivers.

    Science.gov (United States)

    Harmon, Annie C; Babulal, Ganesh; Vivoda, Jonathon M; Zikmund-Fisher, Brian J; Carr, David B

    2018-01-01

    Despite the reality of older adults living many years after driving cessation, few prepare for the eventuality; empirically, planning for a nondriving future has not been directly quantified or explored. The following study quantifies 1) the extent of current drivers' planning, 2) specific planning behaviors, 3) beliefs about benefits of planning, 4) drivers' intention to plan more for future transportation needs, and 5) group differences associated with planning. In a predominantly female, black, urban sample of current drivers ages 53-92, fewer than half (42.1%) had planned at all for a nondriving future, with correspondingly low levels of planning behaviors reported. However, over 80% believed planning would help them meet their needs post-cessation and transition emotionally to being a nondriver. Most (85%) intended to plan more in the future as well, indicating further potential openness to the topic. Drivers who planned were older, drove less frequently, limited their driving to nearby places, reported less difficulty believing they would become a nondriver, and expected to continue driving three years less than non-planners. These findings suggest that drivers' perceived nearness to driving cessation impacts planning for future transportation needs, and existing perceived benefits of planning may provide leverage to motivate action.

  6. Prediction of Chinese Drivers' Intentions to Park Illegally in Emergency Lanes: An Application of the Theory of Planned Behavior.

    Science.gov (United States)

    Zheng, Yubing; Ma, Yang; Guo, Lixin; Cheng, Jianchuan; Zhang, Yunlong

    2018-06-21

    Illegal parking in emergency lanes (paved highway shoulders) is becoming a serious road safety issue in China. The aim of this study was: 1) to examine the utility of the theory of planned behavior (TPB) extended with descriptive norm, past behavior, facilitating and deterring circumstances, sensation seeking and invulnerability in predicting Chinese drivers' intentions in illegal emergency lane parking; 2) to investigate whether respondents' demographic characteristics would impact their views towards the behavior and predictive patterns of intentions; 3) to identify significant predictors of intentions. In this cross-sectional study, eligible respondents were all qualified Chinese drivers. A self-administered questionnaire was employed to collect data including demographic information, descriptive norm, past behavior, facilitating and deterring circumstances, sensation seeking and scenario-based invulnerability combined with TPB constructs. Descriptive statistics, MANOVAs and a series of hierarchical multiple linear regression analyses were conducted in SPSS. A total of 435 qualified drivers (234 males and 201 females) with a mean age of 35.2 years (S.D.=10.3) were included in analysis. The descriptive analysis showed that most participants reported weak intentions (M = 2.35) to park illegally in emergency lanes with negative attitude (M = 3.19), low perceived support (M = 2.91) and high control (M = 5.08) over the behavior. The model succeeded in explaining 64% of the variance in intentions for the whole sample, and principal TPB components accounted for 21% of variance in intentions after demographic variables were controlled. MANOVAs revealed that significant differences of respondents' opinions towards illegal emergency lane parking were only found between better-educated drivers (with college education background) and less-educated ones. Separate regression analyses revealed that predictive pattern of better-educated participants also

  7. Human behavioral contributions to climate change: psychological and contextual drivers.

    Science.gov (United States)

    Swim, Janet K; Clayton, Susan; Howard, George S

    2011-01-01

    We are facing rapid changes in the global climate, and these changes are attributable to human behavior. Humans produce this global impact through our use of natural resources, multiplied by the vast increase in population seen in the past 50 to 100 years. Our goal in this article is to examine the underlying psychosocial causes of human impact, primarily through patterns of reproduction and consumption. We identify and distinguish individual, societal, and behavioral predictors of environmental impact. Relevant research in these areas (as well as areas that would be aided by greater attention by psychologists) are reviewed. We conclude by highlighting ethical issues that emerge when considering how to address human behavioral contributions to climate change.

  8. Driver`s behavior and the motion of motorized wheelchair when driving over rough surfaces; Dansa nado fuseichi sokoji no dendo kurumaisu no undo to join no kyodo

    Energy Technology Data Exchange (ETDEWEB)

    Enomoto, A; Yokomori, M; Yamaguchi, S [Meijo University, Aichi (Japan)

    1997-10-01

    We analyzed about the motion of motorized wheelchairs and the driver`s behavior when passing over the small obstacles in place of the rough surface road or the gateway of house and road by experiment. The tested two type wheelchairs are the front wheel drive and the rear wheel drive. The lean angle of head and the pulse rate of driver, the feeling for stability and the yaw angle and the roll angle of the wheelchair bodies, and the deflection angle of front wheels of rear drive. 4 refs., 11 figs., 1 tab.

  9. Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework

    Directory of Open Access Journals (Sweden)

    Krzysztof Drachal

    2018-05-01

    Full Text Available This article presents results from modelling spot oil prices by Dynamic Model Averaging (DMA. First, based on a literature review and availability of data, the following oil price drivers have been selected: stock prices indices, stock prices volatility index, exchange rates, global economic activity, interest rates, supply and demand indicators and inventories level. Next, they have been included as explanatory variables in various DMA models with different initial parameters. Monthly data between January 1986 and December 2015 has been analyzed. Several variations of DMA models have been constructed, because DMA requires the initial setting of certain parameters. Interestingly, DMA has occurred to be robust to setting different values to these parameters. It has also occurred that the quality of prediction is the highest for the model with the drivers solely connected with the stock markets behavior. Drivers connected with macroeconomic fundamental indicators have not been found so important. This observation can serve as an argument favoring the hypothesis of the increasing financialization of the oil market, at least in the short-term period. The predictions from other, slightly different modelling variations based on DMA methodology, have happened to be consistent with each other in general. Many constructed models have outperformed alternative forecasting methods. It has also been found that normalization of the initial data, although not necessary for DMA from the theoretical point of view, significantly improves the quality of prediction.

  10. Human Behavioral Contributions to Climate Change: Psychological and Contextual Drivers

    Science.gov (United States)

    Swim, Janet K.; Clayton, Susan; Howard, George S.

    2011-01-01

    We are facing rapid changes in the global climate, and these changes are attributable to human behavior. Humans produce this global impact through our use of natural resources, multiplied by the vast increase in population seen in the past 50 to 100 years. Our goal in this article is to examine the underlying psychosocial causes of human impact,…

  11. Can providing feedback on driving behavior and training on parental vigilant care affect male teen drivers and their parents?

    Science.gov (United States)

    Farah, Haneen; Musicant, Oren; Shimshoni, Yaara; Toledo, Tomer; Grimberg, Einat; Omer, Haim; Lotan, Tsippy

    2014-08-01

    This study focuses on investigating the driving behavior of young novice male drivers during the first year of driving (three months of accompanied driving and the following nine months of solo driving). The study's objective is to examine the potential of various feedback forms on driving to affect young drivers' behavior and to mitigate the transition from accompanied to solo driving. The study examines also the utility of providing parents with guidance on how to exercise vigilant care regarding their teens' driving. Driving behavior was evaluated using data collected by In-Vehicle Data Recorders (IVDR), which document events of extreme g-forces measured in the vehicles. IVDR systems were installed in 242 cars of the families of young male drivers, however, only 217 families of young drivers aged 17-22 (M=17.5; SD=0.8) completed the one year period. The families were randomly allocated into 4 groups: (1) Family feedback: In which all the members of the family were exposed to feedback on their own driving and on that of the other family members; (2) Parental training: in which in addition to the family feedback, parents received personal guidance on ways to enhance vigilant care regarding their sons' driving; (3) Individual feedback: In which family members received feedback only on their own driving behavior (and were not exposed to the data on other family members); (4) CONTROL: Group that received no feedback at all. The feedback was provided to the different groups starting from the solo period, thus, the feedback was not provided during the supervised period. The data collected by the IVDRs was first analyzed using analysis of variance in order to compare the groups with respect to their monthly event rates. Events' rates are defined as the number of events in a trip divided by its duration. This was followed by the development and estimation of random effect negative binomial models that explain the monthly event rates of young drivers and their parents

  12. MOTIVATION AND MOTIVES - DRIVER AND REASON OF CONSUMER'S BUYING BEHAVIOR

    OpenAIRE

    TICHINDELEAN Mihai; VINEREAN Simona

    2013-01-01

    The purpose of the paper is to understand and measure consumer's motives as part of the complex mental structure which has as result a certain buying behavior. To achieve this goal, the authors structured the paper in two parts: the first part contains a literature review regarding the concepts of motivation and motives, while the second part tries to measure and explain several dimensions of buying motives by using a statistical analysis tool - exploratory factor analysis.

  13. Thirty-day self-reported risky driving behaviors of ADHD and non-ADHD drivers.

    Science.gov (United States)

    Rosenbloom, Tova; Wultz, Boaz

    2011-01-01

    The present study aims to compare differences in reported risky driving behaviors of drivers - males and females - having and not having Attention Deficit Hyperactivity Disorder (ADHD), by using a checklist of driving behaviors based on the Driving Behavior Questionnaire (DBQ). Unlike the studies which employ the DBQ by asking the subjects to fill the questionnaire once, in this present study, the participants were asked to report their behaviors on a daily basis for 30 consequent days. The checklist included two factors of risky driving behavior: Violation and Faults. Thirty-eight drivers - 10 males and 9 females with ADHD, and 9 males and 10 females without ADHD (N-ADHD) as control groups - participated in the study. The results showed that the mean of the unsafe behaviors of ADHD was higher, i.e., less safe driving, compared to that of N-ADHD. However, a statistically significant effect was found only between male ADHD and male N-ADHD for the Faults. In order to check the effect of the length of the study, the 30 days duration of the research was divided into three consecutive periods. The reported driving habits of the female ADHD showed safer behaviors than those of the males. Unlike the findings of N-ADHD of both genders, which showed a tendency towards safer driving reports in the three periods, both genders of the ADHD showed higher rates of Faults, i.e., a decrease in safety driving reports, in the three periods. The findings suggest that ADHD drivers differ from the N-ADHD drivers in making driving mistakes, i.e., Faults, due to their lack of sustained attention, but not in making Violations. However, some of the results in the present study were not very strong. Possible explanations for this as well as methodological considerations are discussed, and further research is suggested. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. IMPACTS OF GROUP-BASED SIGNAL CONTROL POLICY ON DRIVER BEHAVIOR AND INTERSECTION SAFETY

    Directory of Open Access Journals (Sweden)

    Keshuang TANG

    2008-01-01

    Full Text Available Unlike the typical stage-based policy commonly applied in Japan, the group-based control (often called movement-based in the traffic control industry in Japan refers to such a control pattern that the controller is capable of separately allocating time to each signal group instead of stage based on traffic demand. In order to investigate its applicability at signalized intersections in Japan, an intersection located in Yokkaichi City of Mie Prefecture was selected as an experimental application site by the Japan Universal Traffic Management Society (UTMS. Based on the data collected at the intersection before and after implementing the group-based control policy respectively, this study evaluated the impacts of such a policy on driver behavior and intersection safety. To specify those impacts, a few models utilizing cycle-based data were first developed to interpret the occurrence probability and rate of red-light-running (RLR. Furthermore, analyses were performed on the yellow-entry time (Ye of the last cleared vehicle and post encroachment time (PET during the phase switching. Conclusions supported that the group-based control policy, along with certain other factors, directly or indirectly influenced the RLR behavior of through and right-turn traffics. Meanwhile, it has potential safety benefits as well, indicated by the declined Ye and increased PET values.

  15. Modelling benthic biophysical drivers of ecosystem structure and biogeochemical response

    Science.gov (United States)

    Stephens, Nicholas; Bruggeman, Jorn; Lessin, Gennadi; Allen, Icarus

    2016-04-01

    The fate of carbon deposited at the sea floor is ultimately decided by biophysical drivers that control the efficiency of remineralisation and timescale of carbon burial in sediments. Specifically, these drivers include bioturbation through ingestion and movement, burrow-flushing and sediment reworking, which enhance vertical particulate transport and solute diffusion. Unfortunately, these processes are rarely satisfactorily resolved in models. To address this, a benthic model that explicitly describes the vertical position of biology (e.g., habitats) and biogeochemical processes is presented that includes biological functionality and biogeochemical response capturing changes in ecosystem structure, benthic-pelagic fluxes and biodiversity on inter-annual timescales. This is demonstrated by the model's ability to reproduce temporal variability in benthic infauna, vertical pore water nutrients and pelagic-benthic solute fluxes compared to in-situ data. A key advance is the replacement of bulk parameterisation of bioturbation by explicit description of the bio-physical processes responsible. This permits direct comparison with observations and determination of key parameters in experiments. Crucially, the model resolves the two-way interaction between sediment biogeochemistry and ecology, allowing exploration of the benthic response to changing environmental conditions, the importance of infaunal functional traits in shaping benthic ecological structure and the feedback the resulting bio-physical processes exert on pore water nutrient profiles. The model is actively being used to understand shelf sea carbon cycling, the response of the benthos to climatic change, food provision and other societal benefits.

  16. Examination of drivers' cell phone use behavior at intersections by using naturalistic driving data.

    Science.gov (United States)

    Xiong, Huimin; Bao, Shan; Sayer, James; Kato, Kazuma

    2015-09-01

    Many driving simulator studies have shown that cell phone use while driving greatly degraded driving performance. In terms of safety analysis, many factors including drivers, vehicles, and driving situations need to be considered. Controlled or simulated studies cannot always account for the full effects of these factors, especially situational factors such as road condition, traffic density, and weather and lighting conditions. Naturalistic driving by its nature provides a natural and realistic way to examine drivers' behaviors and associated factors for cell phone use while driving. In this study, driving speed while using a cell phone (conversation or visual/manual tasks) was compared to two baselines (baseline 1: normal driving condition, which only excludes driving while using a cell phone, baseline 2: driving-only condition, which excludes all types of secondary tasks) when traversing an intersection. The outcomes showed that drivers drove slower when using a cell for both conversation and visual/manual (VM) tasks compared to baseline conditions. With regard to cell phone conversations, drivers were more likely to drive faster during the day time compared to night time driving and drive slower under moderate traffic compared to under sparse traffic situations. With regard to VM tasks, there was a significant interaction between traffic and cell phone use conditions. The maximum speed with VM tasks was significantly lower than that with baseline conditions under sparse traffic conditions. In contrast, the maximum speed with VM tasks was slightly higher than that with baseline driving under dense traffic situations. This suggests that drivers might self-regulate their behavior based on the driving situations and demand for secondary tasks, which could provide insights on driver distraction guidelines. With the rapid development of in-vehicle technology, the findings in this research could lead the improvement of human-machine interface (HMI) design as well

  17. Cognitive Modeling of Social Behaviors

    Science.gov (United States)

    Clancey, William J.; Sierhuis, Maarten; Damer. Bruce; Brodsky, Boris

    2004-01-01

    The driving theme of cognitive modeling for many decades has been that knowledge affects how and which goals are accomplished by an intelligent being (Newell 1991). But when one examines groups of people living and working together, one is forced to recognize that whose knowledge is called into play, at a particular time and location, directly affects what the group accomplishes. Indeed, constraints on participation, including roles, procedures, and norms, affect whether an individual is able to act at all (Lave & Wenger 1991; Jordan 1992; Scribner & Sachs 1991). To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual &nd as ways of carrying out activities (Clancey 1997a, 2002b). This requires for the psychologist a shift from only modeling goals and tasks - why people do what they do - to modeling behavioral patterns-what people do-as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). This analysis is particular inspired by activity theory (Leont ev 1979). While acknowledging that knowledge (relating goals and operations) is fundamental for intelligent behavior, activity theory claims that a broader driver is the person s motives and conceptualization of activities. Such understanding of human interaction is normative (i.e., viewed with respect to social standards), affecting how knowledge is called into play and applied in practice. Put another way, how problems are discovered and framed, what methods are chosen, and indeed who even cares or has the authority to act, are all

  18. Understanding driver behavior at grade crossings through signal detection theory.

    Science.gov (United States)

    2013-01-01

    This report uses signal detection theory (SDT) to model motorists decisionmaking strategies at grade crossings in order to understand the factors that influence such decisions and to establish a framework for evaluating the impact of proposed coun...

  19. Understanding driver behavior at grade crossings through signal detection theory.

    Science.gov (United States)

    2013-01-31

    This report uses signal detection theory (SDT) to model motorists decisionmaking strategies at grade crossings in order to understand the factors that influence such decisions and to establish a framework for evaluating the impact of proposed coun...

  20. Drivers׳ merging behavior data in highway work zones

    Directory of Open Access Journals (Sweden)

    Mahmoud Shakouri

    2016-03-01

    Full Text Available There have been growing research interests in finding a suitable work zone layout to improve work zone safety and traffic efficiency. This paper contains data supporting the research article entitled: Effects of work zone configurations and traffic density on performance variables and subjective workload (Shakouri et al., 2014 [1]. A full factorial experiment was conducted to compare the efficiency of two work zone configurations by using a driving simulator with two levels of work zone configuration, two levels of traffic density and three levels of sign placement as fixed factors. Seven female and 23 male participants completed the experiment. In this paper we present the data relating to demographic information of participants, driving simulator data and subjective workload evaluation of participants for each work zone. Keywords: Work zone, Merging behavior, Subjective workload, Safety

  1. Refueling Behavior of Flexible Fuel Vehicle Drivers in the Federal Fleet

    Energy Technology Data Exchange (ETDEWEB)

    Daley, R.; Nangle, J.; Boeckman, G.; Miller, M.

    2014-05-01

    Federal fleets are a frequent subject of legislative and executive efforts to lead a national transition to alternative fuels and advanced vehicle technologies. Section 701 of the Energy Policy Act of 2005 requires that all dual-fueled alternative fuel vehicles in the federal fleet be operated on alternative fuel 100% of the time when they have access to it. However, in Fiscal Year (FY) 2012, drivers of federal flex fuel vehicles (FFV) leased through the General Services Administration refueled with E85 24% of the time when it was available--falling well short of the mandate. The U.S. Department of Energy's National Renewable Energy Laboratory completed a 2-year Laboratory Directed Research and Development project to identify the factors that influence the refueling behavior of federal FFV drivers. The project began with two primary hypotheses. First, information scarcity increases the tendency to miss opportunities to purchase E85. Second, even with perfect information, there are limits to how far drivers will go out of their way to purchase E85. This paper discusses the results of the project, which included a June 2012 survey of federal fleet drivers and an empirical analysis of actual refueling behavior from FY 2009 to 2012. This research will aid in the design and implementation of intervention programs aimed at increasing alternative fuel use and reducing petroleum consumption.

  2. I’ll Show You the Way: Risky Driver Behavior When “Following a Friend”

    Directory of Open Access Journals (Sweden)

    Jaimie McNabb

    2017-05-01

    Full Text Available Previous research examining social influences on driving behavior has primarily focused on the effects of passengers and surrounding vehicles (e.g., speed contagion. Of current interest was the interaction between drivers that occurs in a “following a friend” scenario, i.e., the driver of one vehicle (the leader knows how to get to the desired destination while the driver of a second vehicle (the follower does not. Sixteen participants drove through a simulated city in a driving simulator under three conditions: (i a baseline condition in which they could choose their own route, (ii a navigation system condition in which they were given audible route instructions, and (iii a “follow a friend” condition in which they required to follow a simulated vehicle. In the follow a friend condition, drivers engaged in significantly more risky behaviors (in comparison to the other conditions such as making more erratic and higher speed turns and lane changes, maintaining overall higher speed, as well as maintaining a shorter time headway when following a lead vehicle. These effects suggest a relationship to time pressure caused by a fear of getting lost.

  3. Sociodemographic factors associated with aggressive driving behaviors of 3-wheeler taxi drivers in Sri Lanka.

    Science.gov (United States)

    Akalanka, Ediriweera Chintana; Fujiwara, Takeo; Desapriya, Ediriweera; Peiris, Dinithi C; Scime, Giulia

    2012-01-01

    Little is known about the nature and scope of aggressive driving in developing countries. The objective of this study is to specifically examine the sociodemographic factors associated with aggressive driving behavior among 3-wheeler taxi drivers in Sri Lanka. Convenience samples of 3-wheeler taxi drivers from Rathnapura, Ahaliyagoda, Sri Lanka were surveyed from June to August 2006. Analyses included bivariate and multivariate logistic regression. Drivers with less than high school education were 3.5 times more likely to drive aggressively (odds ratio [OR] = 3.46; 95% confidence interval [CI] = 1.08, 11.1). Single drivers were 9 times more likely to run red lights (OR = 8.74; 95% CI = 2.18, 35.0), and being single was a major risk factor for drunk driving (OR = 4.80; 95% CI = 1.23, 18.7). Furthermore, high school completers were 4 times more likely to bribe a policeman (OR = 4.27; 95% CI = 1.23, 14.9) when caught violating the road rules. Aggressive driving and risk-taking behavior are amenable to policy initiatives, and preventive programs targeted at key groups could be used to improve road safety in Sri Lanka. This study demonstrates that aggressive driving behavior is associated with sociodemographic factors, including the level of education, marital status, and other socioeconomic factors. Hence, economic factors should be addressed to find solutions to traffic-related issues. It will be the government's and policy makers' responsibility to try and understand the economic factors behind risky road behavior and bribe-taking behavior prior to legislating or enforcing new laws.

  4. Driving while black: a comparison of the beliefs, concerns, and behaviors of black and white Maryland drivers.

    Science.gov (United States)

    Debnam, Katrina J; Beck, Kenneth H

    2011-12-01

    The National Highway Traffic Safety Administration suggests that given the changing demographics of the United States it is important to examine motor vehicle statistics by race and ethnicity. The current study sought to explore differences in traffic safety concerns and driving behaviors between black and white drivers. An annual, anonymous, random-digit-dial telephone survey was used to collect data between 2003 and 2009 from Maryland drivers. Drivers (N = 5503) were assessed regarding their driving behaviors and perceived risk of receiving a traffic violation. Results showed that black drivers perceived a greater likelihood of being stopped for driving under the influence (DUI), for not wearing a seat belt and for speeding than white drivers. These differences were found among drivers with or without a history of being ticketed. Black drivers were also more likely to report a variety of risky driving behaviors than white drivers. However, black drivers were not more likely to report receiving a ticket or citation in the last month after controlling for demographic factors, risky driving behaviors, and geographic region of the state, where traffic enforcement may vary. Findings indicate that black drivers are not more likely to be ticketed, despite perceptual biases that may exist among some drivers. These differences appear to be explained by demographic as well as regional factors. These results highlight the need for more research to understand the potential differences in driving behaviors between racial and ethnic groups. More research is also needed to develop countermeasures for racial and ethnic groups most at risk for motor vehicle violations and crashes.

  5. A qualitative exploration of self-regulation behaviors among older drivers.

    Science.gov (United States)

    Donorfio, Laura K M; Mohyde, Maureen; Coughlin, Joseph; D'Ambrosio, Lisa

    2008-01-01

    While much of the research on aging and driving has focused on sensory and motor changes, little is known about older drivers and the actual self-regulation adjustments they employ to continue driving safely. This research looks at how older drivers have made changes to driving patterns and behaviors that have allowed them to continue to drive without compromising their perceived safety, independence, and quality of life. Nine focus groups were held with older men and women aged 58 to 89 years. Some of the major themes that emerged were the following: older adults are very aware of age-related changes to driving; they perceive that self-regulation behaviors change with age; and they view transportation alternatives as limited or nonexistent. Policy implications include developing functional transit programs for older adults and car manufacturer training workshops to educate older adults on the safety features of newly purchased automobiles.

  6. Drivers' Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving.

    Science.gov (United States)

    Du, Mingbo; Mei, Tao; Liang, Huawei; Chen, Jiajia; Huang, Rulin; Zhao, Pan

    2016-01-15

    This paper describes a real-time motion planner based on the drivers' visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers' visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers' visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms.

  7. Multiple logistic regression model of signalling practices of drivers on urban highways

    Science.gov (United States)

    Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

    2015-05-01

    Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

  8. Driver behavior and workload in an on-road automated vehicle

    NARCIS (Netherlands)

    Stapel, J.C.J.; Mullakkal Babu, F.A.; Happee, R.

    2017-01-01

    Driver mental underload is an important concern in the operational safety of automated driving. In this study, workload was evaluated subjectively (NASA RTLX) and objectively (auditory detection-response task) on Dutch public highways (~150km) in a Tesla Model S comparing manual and supervised

  9. Driver Behavior and Performance with Augmented Reality Pedestrian Collision Warning: An Outdoor User Study.

    Science.gov (United States)

    Kim, Hyungil; Gabbard, Joseph L; Anon, Alexandre Miranda; Misu, Teruhisa

    2018-04-01

    This article investigates the effects of visual warning presentation methods on human performance in augmented reality (AR) driving. An experimental user study was conducted in a parking lot where participants drove a test vehicle while braking for any cross traffic with assistance from AR visual warnings presented on a monoscopic and volumetric head-up display (HUD). Results showed that monoscopic displays can be as effective as volumetric displays for human performance in AR braking tasks. The experiment also demonstrated the benefits of conformal graphics, which are tightly integrated into the real world, such as their ability to guide drivers' attention and their positive consequences on driver behavior and performance. These findings suggest that conformal graphics presented via monoscopic HUDs can enhance driver performance by leveraging the effectiveness of monocular depth cues. The proposed approaches and methods can be used and further developed by future researchers and practitioners to better understand driver performance in AR as well as inform usability evaluation of future automotive AR applications.

  10. Incorporating driver distraction in car-following models : Applying the TCI to the IDM

    NARCIS (Netherlands)

    Hoogendoorn, R.G.; van Arem, B.; Hoogendoorn, S.P.

    2013-01-01

    ITS can play a significant role in the improvement of traffic flow, traffic safety and greenhouse gas emissions. However, the implementation of Advanced Driver Assistance Systems may lead to adaptation effects in longitudinal driving behavior following driver distraction. It was however not yet

  11. A Pilot Study Verifying How the Curve Information Impacts on the Driver Performance with Cognition Model

    Directory of Open Access Journals (Sweden)

    Xiaohua Zhao

    2013-01-01

    Full Text Available Drivers' misjudgment is a significant issue for the curve safety. It is considered as a more influential factor than other traffic environmental conditions for inducing risk. The research suggested that the cognition theory could explain the process of drivers’ behavior at curves. In this simulator experiment, a principle cognition model was built to examine the rationality of this explanation. The core of this pilot study was using one of the driving decision strategies for braking at curves to verify the accuracy of the cognition model fundamentally. Therefore, the experiment designed three treatments of information providing modes. The result of the experiment presented that the warning information about curves in advance can move the position of first braking away from curves. This phenomenon is consistent with the model’s inference. Thus, the conclusion of this study indicates that the process of the drivers' behavior at curves can be explained by the cognition theory and represented by cognition model. In addition, the model’s characteristics and working parameters can be acquired by doing other research. Then based on the model it can afford the advice for giving the appropriate warning information that may avoid the driver’s mistake.

  12. Road traffic accidents and self-reported Portuguese car driver's attitudes, behaviors, and opinions: Are they related?

    Science.gov (United States)

    Bon de Sousa, Teresa; Santos, Carolina; Mateus, Ceu; Areal, Alain; Trigoso, Jose; Nunes, Carla

    2016-10-02

    This study aims to characterize Portuguese car drivers in terms of demographic characteristics, driving experience, and attitudes, opinions, and behaviors concerning road traffic safety. Furthermore, associations between these characteristics and self-reported involvement in a road traffic accident as a driver in the last 3 years were analyzed. A final goal was to develop a final predictive model of the risk of suffering a road traffic accident. A cross-sectional analytic study was developed, based on a convenience sample of 612 car drivers. A questionnaire was applied by trained interviewers, embracing various topics related to road safety such as driving under the influence of alcohol or drugs, phone use while driving, speeding, use of advanced driver assistance systems, and the transport infrastructure and environment (European Project SARTRE 4, Portuguese version). From the 52 initial questions, 19 variables were selected through principal component analysis. Then, and in addition to the usual descriptive measures, logistic binary regression models were used in order to describe associations and to develop a predictive model of being involved in a road traffic accident. Of the 612 car drivers, 37.3% (228) reported being involved in a road traffic accident with damage or injury in the past 3 years. In this group, the majority were male, older than 65, with no children, not employed, and living in an urban area. In the multivariate model, several factors were identified: being widowed (vs. single; odds ratio [OR] = 3.478, 95% confidence interval [95% CI], 1.159-10.434); living in a suburban area (vs. a rural area; OR = 5.023, 95% CI, 2.260-11.166); having been checked for alcohol once in the last 3 years (vs. not checked; OR = 3.124, 95% CI, 2.040-4,783); and seldom drinking an energetic beverage such as coffee when tired (vs. always do; OR = 6.822, 95% CI, 2.619-17.769) all suffered a higher risk of being involved in a car accident. The results obtained with

  13. Driver drowsiness detection using behavioral measures and machine learning techniques: A review of state-of-art techniques

    CSIR Research Space (South Africa)

    Ngxande, Mkhuseli

    2017-11-01

    Full Text Available This paper presents a literature review of driver drowsiness detection based on behavioral measures using machine learning techniques. Faces contain information that can be used to interpret levels of drowsiness. There are many facial features...

  14. Effect of changing driving conditions on driver behavior towards design of a safe and efficient traffic system.

    Science.gov (United States)

    2013-12-01

    This simulation-based study explores the effects of different work zone configurations, varying distances : between traffic signs, traffic density and individual differences on drivers behavior. Conventional Lane : Merge (CLM) and Joint Lane Merge...

  15. Towards Behavioral Reflexion Models

    Science.gov (United States)

    Ackermann, Christopher; Lindvall, Mikael; Cleaveland, Rance

    2009-01-01

    Software architecture has become essential in the struggle to manage today s increasingly large and complex systems. Software architecture views are created to capture important system characteristics on an abstract and, thus, comprehensible level. As the system is implemented and later maintained, it often deviates from the original design specification. Such deviations can have implication for the quality of the system, such as reliability, security, and maintainability. Software architecture compliance checking approaches, such as the reflexion model technique, have been proposed to address this issue by comparing the implementation to a model of the systems architecture design. However, architecture compliance checking approaches focus solely on structural characteristics and ignore behavioral conformance. This is especially an issue in Systems-of- Systems. Systems-of-Systems (SoS) are decompositions of large systems, into smaller systems for the sake of flexibility. Deviations of the implementation to its behavioral design often reduce the reliability of the entire SoS. An approach is needed that supports the reasoning about behavioral conformance on architecture level. In order to address this issue, we have developed an approach for comparing the implementation of a SoS to an architecture model of its behavioral design. The approach follows the idea of reflexion models and adopts it to support the compliance checking of behaviors. In this paper, we focus on sequencing properties as they play an important role in many SoS. Sequencing deviations potentially have a severe impact on the SoS correctness and qualities. The desired behavioral specification is defined in UML sequence diagram notation and behaviors are extracted from the SoS implementation. The behaviors are then mapped to the model of the desired behavior and the two are compared. Finally, a reflexion model is constructed that shows the deviations between behavioral design and implementation. This

  16. Influences of motorcycle rider and driver characteristics and road environment on red light running behavior at signalized intersections.

    Science.gov (United States)

    Jensupakarn, Auearree; Kanitpong, Kunnawee

    2018-04-01

    In Thailand, red light running is considered as one of the most dangerous behaviors at intersection. Red light running (RLR) behavior is the failure to obey the traffic control signal. However, motorcycle riders and car drivers who are running through red lights could be influenced by human factors or road environment at intersection. RLR could be advertent or inadvertent behavior influenced by many factors. Little research study has been done to evaluate the contributing factors influencing the red-light violation behavior. This study aims to determine the factors influencing the red light running behavior including human characteristics, physical condition of intersection, traffic signal operation, and traffic condition. A total of 92 intersections were observed in Chiang Mai, Nakhon Ratchasima, and Chonburi, the major provinces in each region of Thailand. In addition, the socio-economic characteristics of red light runners were obtained from self-reported questionnaire survey. The Binary Logistic Regression and the Multiple Linear Regression models were used to determine the characteristics of red light runners and the factors influencing rates of red light running respectively. The results from this study can help to understand the characteristics of red light runners and factors affecting them to run red lights. For motorcycle riders and car drivers, age, gender, occupation, driving license, helmet/seatbelt use, and the probability to be penalized when running the red light significantly affect RLR behavior. In addition, the results indicated that vehicle travelling direction, time of day, existence of turning lane, number of lanes, lane width, intersection sight distance, type of traffic signal pole, type of traffic signal operation, length of yellow time interval, approaching speed, distance from intersection warning sign to stop line, and pavement roughness significantly affect RLR rates. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. The effect of stress and personality on dangerous driving behavior among Chinese drivers.

    Science.gov (United States)

    Ge, Yan; Qu, Weina; Jiang, Caihong; Du, Feng; Sun, Xianghong; Zhang, Kan

    2014-12-01

    The relationship between stress and road safety has been studied for many years, but the effect of global stress and its joint effect with personality on driving behavior have received little attention in previous studies. This study aimed to elucidate the impact of global stress and various personality traits on driving behavior. 242 drivers completed the Perceived Stress Scale-10 (PSS-10), the Dula Dangerous Driving Index (DDDI), and several personality trait scales related to anger, sensation seeking, and altruism. The results showed that perceived stress and sensation seeking were significantly correlated with the four subcategories of dangerous driving behavior, namely, negative cognitive/emotional driving (NCED), aggressive driving (AD), risky driving (RD), and drunk driving (DD). Moreover, anger was positively correlated with negative cognitive/emotional driving, aggressive driving, and risky driving, and altruism was negatively correlated with aggressive driving and drunk driving. Hierarchical multiple regressions were applied to analyze the mediating effect of personality traits, and the results showed that anger mediated the relationship between stress and dangerous driving behavior and that this mediating role was especially strong for negative cognitive/emotional driving and aggressive driving. Collectively, the results showed that stress is an important factor that can affect people's driving behavior but that personality traits mediate the effect of stress on driving behavior. The findings from this study regarding the relationship among stress, anger, and dangerous driving behavior could be applied in the development of intervention programs for stress and anger management in order to improve drivers' ability to manage emotional thoughts and adjust their behavior on the road. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. The role of driver nodes in managing epileptic seizures: Application of Kuramoto model.

    Science.gov (United States)

    Mohseni, Ali; Gharibzadeh, Shahriar; Bakouie, Fatemeh

    2017-04-21

    Synchronization is an important global phenomenon which could be found in a wide range of complex systems such as brain or electronic devices. However, in some circumstances the synchronized states are not desirable for the system and should be suppressed. For example, excessively synchronized activities in the brain network could be the root of neuronal disorders like epileptic seizures. According to the controllability theory of the complex networks, a minimum set of driver nodes has the ability to control the entire system. In this study, we examine the role of driver nodes in suppressing the excessive synchronization in a generalized Kuramoto model, which consists of two types of oscillators: contrarian and regular ones. We used two different structural topologies: Barabási-Albert scale-free (BASF) network and Caenorhabditis elegans (C.elegans) neuronal network. Our results show that contrarian driver nodes have the sufficient ability to break the synchronized level of the systems. In this case, the system coherency level is not fully suppressed that is avoiding dysfunctions of normal brain functions which require the neuronal synchronized activities. Moreover, in this case, the oscillators grouped in two distinct synchronized clusters that could be an indication of chaotic behavior of the system known as resting-state activity of the brain. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Associations of repeated high alcohol use with unsafe driving behaviors, traffic offenses, and traffic crashes among young drivers: Findings from the New Zealand Drivers Study.

    Science.gov (United States)

    Begg, Dorothy; Brookland, Rebecca; Connor, Jennie

    2017-02-17

    The objective of this study was to describe self-reported high alcohol use at each of the 3 licensing stages of graduated driver licensing and its relationship to drink-driving behaviors, intentional risky driving, aggressive driving, alcohol traffic offenses, non-alcohol traffic offenses, and traffic crashes. The New Zealand Drivers Study (NZDS) is a multistage, prospective cohort study of newly licensed drivers interviewed at all 3 stages of the graduated driver licensing system: learner (baseline), restricted (intermediate), and full license. At each stage, alcohol use was self-reported using the Alcohol Use Disorders Identification Test (AUDIT-C), with high alcohol use defined as a score of ≥4 for males and ≥3 for females. Sociodemographic and personality data were obtained at the baseline interview. Alcohol-related, intentional risky, and aggressive driving behaviors were self-reported following each license stage. Traffic crashes and offenses were identified from police records. Crashes were also self-reported. Twenty-six percent (n = 397) reported no high alcohol use, 22% at one license stage, 30% at 2 stages, and 22% at 3 stages. Poisson regression results (unadjusted and adjusted) showed that the number of stages where high alcohol use was reported was significantly associated with each of the outcomes. For most outcomes, and especially the alcohol-involved outcomes, the relative risk increased with the number of stages of high alcohol use. We found that high alcohol use was common among young newly licensed drivers and those who repeatedly reported high alcohol use were at a significantly higher risk of unsafe driving behaviors. Recently introduced zero blood alcohol concentration (BAC) should help to address this problem, but other strategies are required to target persistent offenders.

  20. Risky driving behavior and road traffic crashes among young Asian Australian drivers: findings from the DRIVE study.

    Science.gov (United States)

    Boufous, Soufiane; Ivers, Rebecca; Senserrick, Teresa; Norton, Robyn; Stevenson, Mark; Chen, Huei-Yang; Lam, Lawrence T

    2010-06-01

    To examine differences in risky driving behavior and likelihood of traffic crash according to the country of birth of recently licensed young drivers. The groups examined include those born in Australia, those born in Asia, and those born in other countries. The DRIVE study is a prospective cohort study of drivers aged 17-24 years holding their first-year provisional driver license in New South Wales, Australia. Information obtained from 20,822 participants who completed a baseline questionnaire was linked to police-reported traffic crashes. Self-reported risky driving behaviors and police-reported traffic crashes in young drivers. Young drivers who were born in Asian countries were less likely to report engaging in risky driving behaviors than their Australian-born counterparts. The proportion of participants reporting a high level of risky driving was 31.5 percent (95% confidence intervale [CI], 30.8-32.1) among Australian-born drivers compared to 25.6 percent (95% CI, 23.1-28.2) among Asian-born drivers and 30.4 percent (95% CI, 28.4-32.5) among those born in other regions. Asian-born participants had half the risk of a crash as a driver than their Australian-born counterparts (relative risk [RR] 0.55; 95% CI, 0.41-0.75) after adjusting for a number of demographic factors and driving and risk-taking behaviors. The comparative risk was even lower among those aged 17 years (RR 0.29; 95% CI, 0.29-0.75). Risk estimates for people born in other regions did not differ to those for Australian-born respondents. The study highlights the lower level of risky driving and significantly reduced crash risk for Australian drivers born in Asian countries relative to those born locally. Further research is needed to examine factors underlying this reduced risk and the impact of the length of residence in the host country.

  1. Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

    Science.gov (United States)

    Nash, C. J.; Cole, D. J.

    2018-05-01

    A recent review of the literature has indicated that sensory dynamics play an important role in the driver-vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver's sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.

  2. Multijam Solutions in Traffic Models with Velocity-Dependent Driver Strategies

    DEFF Research Database (Denmark)

    Carter, Paul; Christiansen, Peter Leth; Gaididei, Yuri B.

    2014-01-01

    The optimal-velocity follow-the-leader model is augmented with an equation that allows each driver to adjust their target headway according to the velocity difference between the driver and the car in front. In this more detailed model, which is investigated on a ring, stable and unstable multipu...

  3. Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

    Science.gov (United States)

    Alexander, Susan E.; Potter, Christopher S.; Coughlan, Joseph C.; Klooster, Steven A.; Lerdau, Manuel T.; Chatfield, Robert B.; Peterson, David L. (Technical Monitor)

    1996-01-01

    Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

  4. Description and manual for the use of DRIVER - an interactive modelling aid

    CSIR Research Space (South Africa)

    Furniss, PR

    1977-09-01

    Full Text Available The modelling aid DRIVER is described. It permits the interactive manipulation of the parameters and variables of difference models which are implemented as FORTRAN subroutines. Relationships in the model can be expressed as arbitrary functions. A...

  5. Young driver distraction: state of the evidence and directions for behavior change programs.

    Science.gov (United States)

    Buckley, Lisa; Chapman, Rebekah L; Sheehan, Mary

    2014-05-01

    Adolescent drivers are overrepresented in distraction-related motor vehicle crashes. A number of potential reasons for such an elevated risk include driving inexperience, high adoption of communication technology, increased peer involvement, and tendency to take risks, which render young drivers particularly vulnerable. Major legislative efforts in Graduated Licensing Systems that include passenger restrictions have shown positive effects. Restrictions on cell phone use are also being introduced; however, it is challenging to enforce such regulations. This article argues that such contextual, legislative interventions are an essential prevention strategy, but there is an unfilled need to introduce behavior change programs that may target adolescents, parents, and friends. A theoretical framework is applied in which risk and protective factors are identified from research within the contexts of community and jurisdiction. In the literature on distraction, social context and normative influences are key elements used to inform program design for adolescent drivers, with parental monitoring informing interventions targeting parents. Following from this assessment of the message content assessment, the design of strategies to deliver the messages is reviewed. In the current literature, school-based programs, simulations, and Web-delivered programs have been evaluated with supplementary strategies delivered by physicians and parents. Such developments are still at an early stage of development, and ultimately will need controlled implementation and evaluation studies. Of course, there is no likely single approach to prevent adolescent driver distraction. Complementary approaches such as the further development of technological interventions to manage phone use are needed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  6. A cellular automata model for traffic flow based on kinetics theory, vehicles capabilities and driver reactions

    Science.gov (United States)

    Guzmán, H. A.; Lárraga, M. E.; Alvarez-Icaza, L.; Carvajal, J.

    2018-02-01

    In this paper, a reliable cellular automata model oriented to faithfully reproduce deceleration and acceleration according to realistic reactions of drivers, when vehicles with different deceleration capabilities are considered is presented. The model focuses on describing complex traffic phenomena by coding in its rules the basic mechanisms of drivers behavior, vehicles capabilities and kinetics, while preserving simplicity. In particular, vehiclés kinetics is based on uniform accelerated motion, rather than in impulsive accelerated motion as in most existing CA models. Thus, the proposed model calculates in an analytic way three safe preserving distances to determine the best action a follower vehicle can take under a worst case scenario. Besides, the prediction analysis guarantees that under the proper assumptions, collision between vehicles may not happen at any future time. Simulations results indicate that all interactions of heterogeneous vehicles (i.e., car-truck, truck-car, car-car and truck-truck) are properly reproduced by the model. In addition, the model overcomes one of the major limitations of CA models for traffic modeling: the inability to perform smooth approach to slower or stopped vehicles. Moreover, the model is also capable of reproducing most empirical findings including the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Like most CA models, integer values are used to make the model run faster, which makes the proposed model suitable for real time traffic simulation of large networks.

  7. Personality of young drivers in Oman: Relationship to risky driving behaviors and crash involvement among Sultan Qaboos University students.

    Science.gov (United States)

    Al Azri, Mohammed; Al Reesi, Hamed; Al-Adawi, Samir; Al Maniri, Abdullah; Freeman, James

    2017-02-17

    Drivers' behaviors such as violations and errors have been demonstrated to predict crash involvement among young Omani drivers. However, there is a dearth of studies linking risky driving behaviors to the personality of young drivers. The aim of the present study was to assess such traits within a sample of young Omani drivers (as measured through the behavioral inhibition system [BIS] and the behavioral activation system [BAS]) and determine links with aberrant driving behaviors and self-reported crash involvement. A cross-sectional study was conducted at the Sultan Qaboos University that targeted all licensed Omani's undergraduate students. A total of 529 randomly selected students completed the self-reported questionnaire that included an assessment of driving behaviors (e.g., Driver Behaviour Questionnaire, DBQ) as well as the BIS/BAS measures. A total of 237 participants (44.8%) reported involvement in at least one crash since being licensed. Young drivers with lower BIS-Anxiety scores and higher BAS-Fun Seeking tendencies as well as male drivers were more likely to report driving violations. Statistically significant gender differences were observed on all BIS and BAS subscales (except for BAS-Fun) and the DBQ subscales, because males reported higher trait scores. Though personality traits were related to aberrant driving behaviors at the bivariate level, the constructs were not predictive of engaging in violations or errors. Furthermore, consistent with previous research, a supplementary multivariate logistic regression analysis revealed that only driving experience was predictive of crash involvement. The findings highlight that though personality traits influence self-reported driving styles (and differ between the genders), the relationship with crash involvement is not as clear. This article further outlines the key findings of the study in regards to understanding core psychological constructs that increase crash risk.

  8. A Stochastic LWR Model with Consideration of the Driver's Individual Property

    International Nuclear Information System (INIS)

    Tang Tieqiao; Wang Yunpeng; Yu Guizhen; Huang Haijun

    2012-01-01

    In this paper, we develop a stochastic LWR model based on the influences of the driver's individual property on his/her perceived density and speed deviation. The numerical results show that the driver's individual property has great effects on traffic flow only when the initial density is moderate, i.e., at this time, oscillating traffic flow will occur and the oscillating phenomena in the traffic system consisting of the conservative and aggressive drivers is more serious than that in the traffic system consisting of the conservative (aggressive) drivers.

  9. Driver's behavioral adaptation to adaptive cruise control (ACC): the case of speed and time headway.

    Science.gov (United States)

    Bianchi Piccinini, Giulio Francesco; Rodrigues, Carlos Manuel; Leitão, Miguel; Simões, Anabela

    2014-06-01

    The Adaptive Cruise Control is an Advanced Driver Assistance System (ADAS) that allows maintaining given headway and speed, according to settings pre-defined by the users. Despite the potential benefits associated to the utilization of ACC, previous studies warned against negative behavioral adaptations that might occur while driving with the system activated. Unfortunately, up to now, there are no unanimous results about the effects induced by the usage of ACC on speed and time headway to the vehicle in front. Also, few studies were performed including actual users of ACC among the subjects. This research aimed to investigate the effect of the experience gained with ACC on speed and time headway for a group of users of the system. In addition, it explored the impact of ACC usage on speed and time headway for ACC users and regular drivers. A matched sample driving simulator study was planned as a two-way (2×2) repeated measures mixed design, with the experience with ACC as between-subjects factor and the driving condition (with ACC and manually) as within-subjects factor. The results show that the usage of ACC brought a small but not significant reduction of speed and, especially, the maintenance of safer time headways, being the latter result greater for ACC users, probably as a consequence of their experience in using the system. The usage of ACC did not cause any negative behavioral adaptations to the system regarding speed and time headway. Based on this research work, the Adaptive Cruise Control showed the potential to improve road safety for what concerns the speed and the time headway maintained by the drivers. The speed of the surrounding traffic and the minimum time headway settable through the ACC seem to have an important effect on the road safety improvement achievable with the system. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Disentangling the drivers of coarse woody debris behavior and carbon gas emissions during fire

    Science.gov (United States)

    Zhao, Weiwei; van der Werf, Guido R.; van Logtestijn, Richard S. P.; van Hal, Jurgen R.; Cornelissen, Johannes H. C.

    2016-04-01

    The turnover of coarse woody debris, a key terrestrial carbon pool, plays fundamental roles in global carbon cycling. Biological decomposition and fire are two main fates for dead wood turnover. Compared to slow decomposition, fire rapidly transfers organic carbon from the earth surface to the atmosphere. Both a-biotic environmental factors and biotic wood properties determine coarse wood combustion and thereby its carbon gas emissions during fire. Moisture is a key inhibitory environmental factor for fire. The properties of dead wood strongly affect how it burns either directly or indirectly through interacting with moisture. Coarse wood properties vary between plant species and between various decay stages. Moreover, if we put a piece of dead wood in the context of a forest fuel bed, the soil and wood contact might also greatly affect their fire behavior. Using controlled laboratory burns, we disentangled the effects of all these driving factors: tree species (one gymnosperms needle-leaf species, three angiosperms broad-leaf species), wood decay stages (freshly dead, middle decayed, very strongly decayed), moisture content (air-dried, 30% moisture content in mass), and soil-wood contact (on versus 3cm above the ground surface) on dead wood flammability and carbon gas efflux (CO2 and CO released in grams) during fire. Wood density was measured for all coarse wood samples used in our experiment. We found that compared to other drivers, wood decay stages have predominant positive effects on coarse wood combustion (for wood mass burned, R2=0.72 when air-dried and R2=0.52 at 30% moisture content) and associated carbon gas emissions (for CO2andCO (g) released, R2=0.55 when air-dried and R2=0.42 at 30% moisture content) during fire. Thus, wood decay accelerates wood combustion and its CO2 and CO emissions during fire, which can be mainly attributed to the decreasing wood density (for wood mass burned, R2=0.91 when air-dried and R2=0.63 at 30% moisture content) as wood

  11. Assessing characteristics related to the use of seatbelts and cell phones by drivers: application of a bivariate probit model.

    Science.gov (United States)

    Russo, Brendan J; Kay, Jonathan J; Savolainen, Peter T; Gates, Timothy J

    2014-06-01

    The effects of cell phone use and safety belt use have been an important focus of research related to driver safety. Cell phone use has been shown to be a significant source of driver distraction contributing to substantial degradations in driver performance, while safety belts have been demonstrated to play a vital role in mitigating injuries to crash-involved occupants. This study examines the prevalence of cell phone use and safety belt non-use among the driving population through direct observation surveys. A bivariate probit model is developed to simultaneously examine the factors that affect cell phone and safety belt use among motor vehicle drivers. The results show that several factors may influence drivers' decision to use cell phones and safety belts, and that these decisions are correlated. Understanding the factors that affect both cell phone use and safety belt non-use is essential to targeting policy and programs that reduce such behavior. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Continuous monitoring the vehicle dynamics and driver behavior using navigation systems

    Science.gov (United States)

    Ene, George

    2017-10-01

    In all fields cost is very important and the increasing amount of data that are needed for active safety systems, like ADAS, lead to implementation of some complex and powerful unit for processing raw data. In this manner is necessary a cost-effective method to estimate the maximum available tire road friction during acceleration and braking by continuous monitoring the vehicle dynamics and driver behavior. The method is based on the hypothesis that short acceleration and braking periods can indicate vehicle dynamics, and thus the available tire road friction coefficient, and also human behavior and his limits. Support for this hypothesis is found in the literature and is supported by the result of experiments conducted under different conditions and seasons.

  13. FRAMEWORK OF TAILORMADE DRIVING SUPPORT SYSTEMS AND NEURAL NETWORK DRIVER MODEL

    Directory of Open Access Journals (Sweden)

    Toshiya HIROSE, M.S.

    2004-01-01

    Nowadays, tailormade medical treatment is receiving much attention in the field of medical care. It is also desirable for driving support systems to reflect the driving characteristics of individuals as much as possible, begin monitoring the driver when a driver starts driving and calculates the driver model, and supports them with a model that makes the driver feel quite normal. That is the construction of Tailormade Driving Support Systems (TDSS. This research proposes a concept and a framework of TDSS, and presents a driver model that uses a neural network to build the system. As for the feasibility of this system, the research selects braking as a typical constituent element, and illustrates and reviews the results of experiments and simulations.

  14. Associating Crash Avoidance Maneuvers with Driver Attributes and Accident Characteristics: A Mixed Logit Model Approach

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    as from the key role of the ability of drivers to perform effective corrective maneuvers for the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that accommodates correlations across alternatives and heteroscedasticity. Data...

  15. A spring-mass-damper system dynamics-based driver-vehicle integrated model for representing heterogeneous traffic

    Science.gov (United States)

    Munigety, Caleb Ronald

    2018-04-01

    The traditional traffic microscopic simulation models consider driver and vehicle as a single unit to represent the movements of drivers in a traffic stream. Due to this very fact, the traditional car-following models have the driver behavior related parameters, but ignore the vehicle related aspects. This approach is appropriate for homogeneous traffic conditions where car is the major vehicle type. However, in heterogeneous traffic conditions where multiple vehicle types are present, it becomes important to incorporate the vehicle related parameters exclusively to account for the varying dynamic and static characteristics. Thus, this paper presents a driver-vehicle integrated model hinged on the principles involved in physics-based spring-mass-damper mechanical system. While the spring constant represents the driver’s aggressiveness, the damping constant and the mass component take care of the stability and size/weight related aspects, respectively. The proposed model when tested, behaved pragmatically in representing the vehicle-type dependent longitudinal movements of vehicles.

  16. Work stress, fatigue and risk behaviors at the wheel: Data to assess the association between psychosocial work factors and risky driving on Bus Rapid Transit drivers

    Directory of Open Access Journals (Sweden)

    Sergio Useche

    2017-12-01

    Full Text Available This Data in Brief (DiB article presents a hierarchical multiple linear regression model that examine the associations between psychosocial work factors and risk behaviors at the wheel in Bus Rapid Transit (BRT drivers (n=524. The data were collected using a structured self-administrable questionnaire made of measurements of wok stress (job strain and effort- reward imbalance, fatigue (need for recovery and chronic fatigue, psychological distress and demographics (professional driving experience, hours driven per day and days working per week. The data contains 4 parts: descriptive statistics, bivariate correlations between the study variables and a regression model predicting risk behaviors at the wheel and the entire study dataset. For further information, it is convenient to read the full article entitled “Stress-related Psychosocial Factors at Work, Fatigue, and Risky Driving Behavior in Bus Rapid Transport (BRT Drivers”, published in Accident Analysis & Prevention. Keywords: Professional drivers, Work stress, Fatigue, Psychological distress, Risk behaviors, Bus Rapid Transport, BRT

  17. Steering disturbance rejection using a physics-based neuromusculoskeletal driver model

    Science.gov (United States)

    Mehrabi, Naser; Sharif Razavian, Reza; McPhee, John

    2015-10-01

    The aim of this work is to develop a comprehensive yet practical driver model to be used in studying driver-vehicle interactions. Drivers interact with their vehicle and the road through the steering wheel. This interaction forms a closed-loop coupled human-machine system, which influences the driver's steering feel and control performance. A hierarchical approach is proposed here to capture the complexity of the driver's neuromuscular dynamics and the central nervous system in the coordination of the driver's upper extremity activities, especially in the presence of external disturbance. The proposed motor control framework has three layers: the first (or the path planning) plans a desired vehicle trajectory and the required steering angles to perform the desired trajectory; the second (or the musculoskeletal controller) actuates the musculoskeletal arm to rotate the steering wheel accordingly; and the final layer ensures the precision control and disturbance rejection of the motor control units. The physics-based driver model presented here can also provide insights into vehicle control in relaxed and tensed driving conditions, which are simulated by adjusting the driver model parameters such as cognition delay and muscle co-contraction dynamics.

  18. Continuous traffic flow modeling of driver support systems in multiclass traffic with inter-vehicle communication and drivers in the loop

    NARCIS (Netherlands)

    Tampere, C.M.J.; Hoogendoorn, S.P.; Arem, B. van

    2009-01-01

    This paper presents a continuous traffic-flow model for the explorative analysis of advanced driver-assistance systems (ADASs). Such systems use technology (sensors and intervehicle communication) to support the task of the driver, who retains full control over the vehicle. Based on a review of

  19. The role of personality traits and driving experience in self-reported risky driving behaviors and accident risk among Chinese drivers.

    Science.gov (United States)

    Tao, Da; Zhang, Rui; Qu, Xingda

    2017-02-01

    The purpose of this study was to explore the role of personality traits and driving experience in the prediction of risky driving behaviors and accident risk among Chinese population. A convenience sample of drivers (n=511; mean (SD) age=34.2 (8.8) years) completed a self-report questionnaire that was designed based on validated scales for measuring personality traits, risky driving behaviors and self-reported accident risk. Results from structural equation modeling analysis demonstrated that the data fit well with our theoretical model. While showing no direct effects on accident risk, personality traits had direct effects on risky driving behaviors, and yielded indirect effects on accident risk mediated by risky driving behaviors. Both driving experience and risky driving behaviors directly predicted accident risk and accounted for 15% of its variance. There was little gender difference in personality traits, risky driving behaviors and accident risk. The findings emphasized the importance of personality traits and driving experience in the understanding of risky driving behaviors and accident risk among Chinese drivers and provided new insight into the design of evidence-based driving education and accident prevention interventions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Integration of a driving simulator and a traffic simulator case study: Exploring drivers' behavior in response to variable message signs

    Directory of Open Access Journals (Sweden)

    Mansoureh Jeihani

    2017-12-01

    Full Text Available For the first time, a driving simulator has been integrated with a traffic simulator at the network level to allow subjects to drive in a fairly realistic environment with a realistic traffic flow and density. A 10 mi2 (25 km2 network was developed in a driving simulator and then exported to a traffic simulator. About 30 subjects drove the simulator under different traffic and driving conditions and variable message sign (VMS information, both with and without integration. Route guidance was available for the subjects. The challenges of the integration process are explained and its advantages investigated. The study concluded that traffic density, VMS reliability and compliance behavior are higher when driving and traffic simulators are integrated. To find factors affecting route diversion, researchers applied a binary logistic regression model. The results indicated that the original chosen route, displayed VMS information, subjects' attitude toward VMS information helpfulness, and their level of exposure to VMS affect route diversion. In addition, a multinomial logistic regression model was employed to investigate important factors in route choice. The results revealed that there is a significant correlation with driver route choice behavior and their actual travel time, the need for GPS, VMS exposure and also the designed scenarios. It should be noted that the paper was peer-reviewed by TRB and presented at the TRB Annual Meeting, Washington, D.C., January 2016. Keywords: Integration, Variable message sign, Compliance behavior, Driving simulator, Traffic simulator, Discrete choice analysis

  1. Predictors of Self-reported Crashes among Iranian Drivers: Exploratory Analysis of an Extended Driver Behavior Questionnaire

    Directory of Open Access Journals (Sweden)

    Amin Mohamadi Hezaveh

    2018-02-01

    Full Text Available More than 16,500 people lose their lives each year due to traffic crashes in Iran, which reflects one of the highest road traffic fatality rates in the world. The aim of the present study is to investigate the factors structure of an extended Driver Behaviour Questionnaire (DBQ and to examine the gender differences in the extracted factors among Iranian drivers. Further, the study tested the association between DBQ factors, demographic characteristics, and self-reported crashes. Based on Iranian driving culture, an extended (36 items Internet-based version of the DBQ was distributed among Iranian drivers. The results of Exploratory Factor Analysis based on a sample of 632 Iranians identified a five-factor solution named “Speeding and Pushing Violations”, “Lapses and Errors”, “Violations Causing Inattention”, “Aggressive Violations” and “Traffic Violations” which account for 44.7 percent of the total variance. The results also revealed that females were more prone to Lapses and Errors, whereas males reported more violations than females. Logistic regression analysis identified Violations Causing Inattention, Speeding and Pushing Violations as predictors of self-reported crashes in a three-year period. The results were discussed in line with road traffic safety countermeasures suitable for the Iranian context.

  2. The driver as archetype for driver assistance systems? A driver-model based approach for the development of situation-adaptive DAS; Der Fahrer als Vorbild fuer Fahrerassistenzsysteme? Ein Fahrermodellbasierter Ansatz zur Entwicklung von situationsadaptiven FAS

    Energy Technology Data Exchange (ETDEWEB)

    Benmimoun, A. [Inst. fuer Kraftfahrwesen, RWTH-Aachen, Aachen (Germany)

    2004-07-01

    A new approach for the development of advanced driver assistance systems is presented. The keynote of this new approach is to use the driver model of the traffic simulation tool PELOPS as a control algorithm and to apply it to a vehicle. The fact, that the human driving behaviour is the starting point of the development, is the main advantage of this new approach. Thus important aspects for the development of driver assistance systems like a situation-adaptive and reliable control, understandable behaviour and the consideration of driver-individual parameters are integrated in the controller design from the beginning. An application example of the new approach is shown. (orig.)

  3. Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

    Science.gov (United States)

    Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

    2014-01-01

    Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.

  4. Stages of driving behavior change within the Transtheoretical Model (TM).

    Science.gov (United States)

    Kowalski, Kristina; Jeznach, Anna; Tuokko, Holly Anna

    2014-09-01

    Many older adults voluntarily restrict their driving or stop driving of their own accord. Driving behavior change may occur in stages, as predicted by the Transtheoretical Model of Behavior Change (TM). This study explored the process of older driver behavior change within the TM framework using interviews/focus groups with drivers and former drivers aged 71-94 years. Within those groups of drivers, driving behavior was divided into two classes: those who changed their driving with age and those who did not. Those who changed their driving as they aged included people gradually imposing restrictions ("gradual restrictors") and those making plans in anticipation of stopping driving ("preparers"). Participants who did not change their driving included those who employed lifelong driving restrictions ("consistent") and those who made no changes ("non-changers"). Preliminary support for TM within the driving context was found; however, further exploration of driving behavior change within this framework is warranted. It is important to continue to investigate the factors that might influence driving behavior in older adults. By promoting self-regulation in individuals, it may be possible to help older adults continue to drive, thereby improving older adult's mobility and quality of life. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

  5. A Qualitative Study of Migrant-related Stressors, Psychosocial Outcomes and HIV Risk Behavior among Truck Drivers in Zambia

    Science.gov (United States)

    Ncube, Nomagugu; Simona, Simona J.; Kansankala, Brian; Sinkala, Emmanuel; Raidoo, Jasmin

    2017-01-01

    Truck drivers are part of mobile populations which have been noted as a key population at risk of HIV in Zambia. This study was aimed at 1) determining Potentially Traumatic Events (PTEs), labor migrant-related stressors, psychosocial problems and HIV risk behaviors among truck drivers in Zambia and 2) examining the relationship between PTEs, migrant-related stressors, psychosocial outcomes and HIV sexual risk behavior among truck drivers in Zambia. We conducted fifteen semi-structured interviews with purposively sampled male truck drivers at trucking companies in Lusaka, Zambia. Findings indicate that truck drivers experience multiple stressors and potentially traumatic incidences, including delays and long waiting hours at borders, exposure to crime and violence, poverty, stress related to resisting temptation of sexual interactions with sex workers or migrant women, and job-related safety concerns. Multiple psychosocial problems such as intimate partner violence, loneliness, anxiety and depression-like symptoms were noted. Transactional sex, coupled with inconsistent condom use were identified as HIV sexual risk behaviors. Findings suggest the critical need to develop HIV prevention interventions which account for mobility, potentially traumatic events, psychosocial problems, and the extreme fear of HIV testing among this key population. PMID:27681145

  6. Estimating Value of Congestion and of Reliability from Observation of Route Choice Behavior of Car Drivers

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Rasmussen, Thomas Kjær; Nielsen, Otto Anker

    2014-01-01

    In recent years, a consensus has been reached about the relevance of calculating the value of congestion and the value of reliability for better understanding and therefore better prediction of travel behavior. The current study proposed a revealed preference approach that used a large amount...... both congestion and reliability terms. Results illustrated that the value of time and the value of congestion were significantly higher in the peak period because of possible higher penalties for drivers being late and consequently possible higher time pressure. Moreover, results showed...... that the marginal rate of substitution between travel time reliability and total travel time did not vary across periods and traffic conditions, with the obvious caveat that the absolute values were significantly higher for the peak period. Last, results showed the immense potential of exploiting the growing...

  7. A parametric duration model of the reaction times of drivers distracted by mobile phone conversations.

    Science.gov (United States)

    Haque, Md Mazharul; Washington, Simon

    2014-01-01

    The use of mobile phones while driving is more prevalent among young drivers-a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q advanced driving simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver's peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21-26 years old and split evenly by gender. Drivers' reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver's age, license type (provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted

  8. Behavioral adaptation of young and older drivers to an intersection crossing advisory system

    NARCIS (Netherlands)

    Dotzauer, Mandy; de Waard, Dick; Caljouw, Simone R.; Poehler, Gloria; Brouwer, Wiebo H.

    An advanced driver assistance system (ADAS) provided information about the right of way regulation and safety to cross an upcoming intersection. Effects were studied in a longer-term study involving 18 healthy older drivers between the ages of 65 and 82 years and 18 healthy young drivers between the

  9. Influence of traffic situation on a driver`s visual behavior; Kotsu jokyo ga shinin kodo ni oyobosu eikyo

    Energy Technology Data Exchange (ETDEWEB)

    Kisumi, E; Hara, t [Mitsubishi Motors Corp., Tokyo (Japan)

    1997-10-01

    When a driver performs an in-car visual task, that task must be time-shared with the driving task. Therefore, his/her glances would be divided between the forward view and the in-car visual display in accordance with traffic situation. In order to investigate the influence of traffic situation on glance duration distribution, an experiment for in-car visual task was conducted using Mitsubishi`s flat-belt driving simulator. As a result, a glance duration tends to shorten as driving task demands increase, such as driving at high speed, being overtaken, etc., and a glance cycle tends to shorten under the same situation. 5 refs., 8 figs., 1 tab.

  10. Field tests and machine learning approaches for refining algorithms and correlations of driver's model parameters.

    Science.gov (United States)

    Tango, Fabio; Minin, Luca; Tesauri, Francesco; Montanari, Roberto

    2010-03-01

    This paper describes the field tests on a driving simulator carried out to validate the algorithms and the correlations of dynamic parameters, specifically driving task demand and drivers' distraction, able to predict drivers' intentions. These parameters belong to the driver's model developed by AIDE (Adaptive Integrated Driver-vehicle InterfacE) European Integrated Project. Drivers' behavioural data have been collected from the simulator tests to model and validate these parameters using machine learning techniques, specifically the adaptive neuro fuzzy inference systems (ANFIS) and the artificial neural network (ANN). Two models of task demand and distraction have been developed, one for each adopted technique. The paper provides an overview of the driver's model, the description of the task demand and distraction modelling and the tests conducted for the validation of these parameters. A test comparing predicted and expected outcomes of the modelled parameters for each machine learning technique has been carried out: for distraction, in particular, promising results (low prediction errors) have been obtained by adopting an artificial neural network.

  11. ISG hybrid powertrain: a rule-based driver model incorporating look-ahead information

    Science.gov (United States)

    Shen, Shuiwen; Zhang, Junzhi; Chen, Xiaojiang; Zhong, Qing-Chang; Thornton, Roger

    2010-03-01

    According to European regulations, if the amount of regenerative braking is determined by the travel of the brake pedal, more stringent standards must be applied, otherwise it may adversely affect the existing vehicle safety system. The use of engine or vehicle speed to derive regenerative braking is one way to avoid strict design standards, but this introduces discontinuity in powertrain torque when the driver releases the acceleration pedal or applies the brake pedal. This is shown to cause oscillations in the pedal input and powertrain torque when a conventional driver model is adopted. Look-ahead information, together with other predicted vehicle states, are adopted to control the vehicle speed, in particular, during deceleration, and to improve the driver model so that oscillations can be avoided. The improved driver model makes analysis and validation of the control strategy for an integrated starter generator (ISG) hybrid powertrain possible.

  12. Driver-centred vehicle automation: using network analysis for agent-based modelling of the driver in highly automated driving systems.

    Science.gov (United States)

    Banks, Victoria A; Stanton, Neville A

    2016-11-01

    To the average driver, the concept of automation in driving infers that they can become completely 'hands and feet free'. This is a common misconception, however, one that has been shown through the application of Network Analysis to new Cruise Assist technologies that may feature on our roads by 2020. Through the adoption of a Systems Theoretic approach, this paper introduces the concept of driver-initiated automation which reflects the role of the driver in highly automated driving systems. Using a combination of traditional task analysis and the application of quantitative network metrics, this agent-based modelling paper shows how the role of the driver remains an integral part of the driving system implicating the need for designers to ensure they are provided with the tools necessary to remain actively in-the-loop despite giving increasing opportunities to delegate their control to the automated subsystems. Practitioner Summary: This paper describes and analyses a driver-initiated command and control system of automation using representations afforded by task and social networks to understand how drivers remain actively involved in the task. A network analysis of different driver commands suggests that such a strategy does maintain the driver in the control loop.

  13. What if it Suddenly Fails? Behavioral Aspects of Advanced Driver Assistant Systems on the Example of Local Danger Alerts

    NARCIS (Netherlands)

    Mahr, Angela; Cao, Y.; Theune, Mariet; Dimitrova-Krause, Veronika; Schwartz, Tim; Müller, Christian; Coelho, Helder; Studer, Rudi; Wooldridge, Michael

    2010-01-01

    Many researchers argue, in assessing the benefits of Advanced Driver Assistance Systems (ADAS) it has to be taken into account that any gains in terms of security may be again reduced by the fact they affect the drivers’ behavior. In this paper, we present results of a driving simulation study in

  14. Us and me : team identification and individual differentiation as complementary drivers of team members' citizenship and creative behaviors

    NARCIS (Netherlands)

    Janssen, O.; Huang, X

    The authors investigate team identification and individual differentiation as complementary drivers of team members' citizenship and creative behavior. As hypothesized, the results of a survey among 157 middle-management team members show team identification to be positively related to citizenship

  15. Who is a dangerous driver? Socio-demographic and personal determinants of risky traffic behavior

    Directory of Open Access Journals (Sweden)

    Aleksandra Peplińska

    2015-08-01

    Full Text Available Background The aim of this study was to search for comprehensive socio-demographic and personal (personality and temperamental determinants of risky on-the-road behavior. Based on the results of previous studies, we assumed that the main predictors of dangerous traffic behavior include: internal locus of control, sensation seeking, risk seeking and risk acceptance, as well as high self-esteem, a low level of reactivity combined with a high level of endurance and activity (which together determine a strong need for stimulation and a preference for hedonistic values; and among socio-demographic variables – age, gender, education and duration of having a driving license. Participants and procedure The study included a group of 380 participants, aged between 19 and 61 years (Me = 24. In order to verify the hypothesis, a battery of research tools measuring personality and temperamental variables was adopted, namely: the Formal Characteristics of Behavior – Temperament Questionnaire, Rotter I-E Scale, Risk Acceptance Scale, Stimulating-Instrumental Risk Inventory, Scheler Value Scale, Zuckerman Sensation Seeking Scale and Rosenberg Self-Esteem Scale. Results The dangerous driver syndrome was found to be promoted by high levels of experience and sensation seeking, low levels of tolerance to boredom and monotony, high need for stimulating risk and high risk acceptance, high self-esteem, a preference for hedonistic values coupled with aversion towards moral values, as well as low sensory sensitivity, and was especially visible among older men with short driving experience. Conclusions It can be concluded that both socio-demographic and psychological variables, such as temperament and personality, are significant predictors of dangerous traffic behavior.

  16. Indicators of health behavior of drivers and riders in the countryside of Northeastern Brazil

    Directory of Open Access Journals (Sweden)

    Ellany Gurgel Cosme do Nascimento

    2017-05-01

    Full Text Available Objective: to verify habits and behavior of the drivers and their correlation to the usage of safety equipment.  Method: cross-sectional study using a household survey of an explanatory nature. Community health workers conducted interviews in 3,482  of Caraúbas, state of Rio Grande do Norte.  Results: there is a low adherence to wearing traffic safety equipment, specifically seatbelt and helmet, and the population does not understand the continuous usage as a healthy behavior. The association with socioeconomic variables shows the evidence of groups possibly more vulnerable to accidents than others. Stands out the low adherence of safety equipment while moving around the city, possibly due to the misunderstanding of the risks, justified by the short distances of the rides and the not policed streets.  Conclusion: The increase of the powered mobility due to the improvement of the population’s income, the low adherence of the seatbelt and helmet and the ineffectiveness of the government oversight make the situation a serious public health problem.

  17. A path-following driver/vehicle model with optimized lateral dynamic controller

    Directory of Open Access Journals (Sweden)

    Behrooz Mashadi

    Full Text Available Reduction in traffic congestion and overall number of accidents, especially within the last decade, can be attributed to the enormous progress in active safety. Vehicle path following control with the presence of driver commands can be regarded as one of the important issues in vehicle active safety systems development and more realistic explanation of vehicle path tracking problem. In this paper, an integrated driver/DYC control system is presented that regulates the steering angle and yaw moment, considering driver previewed path. Thus, the driver previewed distance, the heading error and the lateral deviation between the vehicle and desired path are used as inputs. Then, the controller determines and applies a corrective steering angle and a direct yaw moment to make the vehicle follow the desired path. A PID controller with optimized gains is used for the control of integrated driver/DYC system. Genetic Algorithm as an intelligent optimization method is utilized to adapt PID controller gains for various working situations. Proposed integrated driver/DYC controller is examined on lane change manuvers andthe sensitivity of the control system is investigated through the changes in the driver model and vehicle parameters. Simulation results show the pronounced effectiveness of the controller in vehicle path following and stability.

  18. Taxi drivers' views on risky driving behavior in Tehran: a qualitative study using a social marketing approach.

    Science.gov (United States)

    Shams, Mohsen; Shojaeizadeh, Davoud; Majdzadeh, Reza; Rashidian, Arash; Montazeri, Ali

    2011-05-01

    The use of the social marketing approach for public health issues is increasing. This approach uses marketing concepts borrowed from the principles of commercial marketing to promote beneficial health behaviors. In this qualitative study, four focus groups involving 42 participants were used in consumer research to explore taxi drivers' views on the driving situation and the determinants of risky driving behaviors in Tehran, as well as to gather their ideas for developing a social marketing program to reduce risky driving behaviors among taxi drivers in Tehran, Iran. Participants were asked to respond to questions that would guide the development of a marketing mix, or four Ps (product, price, place and promotion). The discussions determined that the program product should involve avoiding risky driving behaviors through increased attention to driving. They pointed out that developing and communicating with a well-designed persuasive message meant to draw their attention to driving could affect their driving behaviors. In addition, participants identified price, place and promotion strategies. They offered suggestions for marketing nonrisky driving to the target audience. The focus group discussions generated important insights into the values and the motivations that affect consumers' decisions to adopt the product. The focus group guided the development of a social marketing program to reduce risky driving behaviors in taxi drivers in Tehran, Iran. Copyright © 2010 Elsevier Ltd. All rights reserved.

  19. Bus crash severity in the United-States: The role of driver behavior, service type, road factors and environmental conditions

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    current study investigates the underlying risk factors of bus accident severity in the United States. A generalized ordered logit model is estimated in order to account for the ordered nature of severity, while allowing the violation of the proportional odds assumption across severity categories. Data...... for the analysis are retrieved from the General Estimates System (GES) database for the years 2005-2009. Results show that accident severity increases: (i) for young bus drivers under the age of 25; (ii) for drivers beyond the age of 55, and most prominently for drivers over 65 years old; (iii) for female drivers......Recent years have witnessed a growing interest in improving bus safety operations worldwide. While in the United States buses are considered relatively safe, the number of bus accidents is far from being negligible, triggering the introduction of the Motor-coach Enhanced Safety Act of 2011.The...

  20. Identification of mutated driver pathways in cancer using a multi-objective optimization model.

    Science.gov (United States)

    Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng

    2016-05-01

    New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. State all-driver distracted driving laws and high school students'  texting while driving behavior.

    Science.gov (United States)

    Qiao, Nan; Bell, Teresa Maria

    2016-01-01

    Texting while driving is highly prevalent among adolescents and young adults in the United States. Texting while driving can significantly increase the risk of road crashes and is associated with other risky driving behaviors. Most states have enacted distracted driving laws to prohibit texting while driving. This study examines effects of different all-driver distracted driving laws on texting while driving among high school students. High school student data were extracted from the 2013 National Youth Risk Behavior Survey. Distracted driving law information was collected from the National Conference of State Legislatures. The final sample included 6,168 high school students above the restricted driving age in their states and with access to a vehicle. Logistic regression was applied to estimate odds ratios of laws on texting while driving. All-driver text messaging bans with primary enforcement were associated with a significant reduction in odds of texting while driving among high school students (odds ratio = 0.703; 95% confidence interval, 0.513-0.964), whereas all-driver phone use bans with primary enforcement did not have a significant association with texting while driving (odds ratio = 0.846; 95% confidence interval, 0.501-1.429). The findings indicate that all-driver distracted driving laws that specifically target texting while driving as opposed to all types of phone use are effective in reducing the behavior among high school students.

  2. Hand-held cell phone use while driving legislation and observed driver behavior among population sub-groups in the United States.

    Science.gov (United States)

    Rudisill, Toni M; Zhu, Motao

    2017-05-12

    Cell phone use behaviors are known to vary across demographic sub-groups and geographic locations. This study examined whether universal hand-held calling while driving bans were associated with lower road-side observed hand-held cell phone conversations across drivers of different ages (16-24, 25-59, ≥60 years), sexes, races (White, African American, or other), ruralities (suburban, rural, or urban), and regions (Northeast, Midwest, South, and West). Data from the 2008-2013 National Occupant Protection Use Survey were merged with states' cell phone use while driving legislation. The exposure was presence of a universal hand-held cell phone ban at time of observation. Logistic regression was used to assess the odds of drivers having a hand-held cell phone conversation. Sub-groups differences were assessed using models with interaction terms. When universal hand-held cell phone bans were effective, hand-held cell phone conversations were lower across all driver demographic sub-groups and regions. Sub-group differences existed among the sexes (p-value, phone bans, the adjusted odds ratio (aOR) of a driver hand-held phone conversation was 0.34 [95% confidence interval (CI): 0.28, 0.41] for females versus 0.47 (CI 0.40, 0.55) for males and 0.31 (CI 0.25, 0.38) for drivers in Western states compared to 0.47 (CI 0.30, 0.72) in the Northeast and 0.50 (CI 0.38, 0.66) in the South. The presence of universal hand-held cell phone bans were associated lower hand-held cell phone conversations across all driver sub-groups and regions. Hand-held phone conversations were particularly lower among female drivers and those from Western states when these bans were in effect. Public health interventions concerning hand-held cell phone use while driving could reasonably target all drivers.

  3. Hand-held cell phone use while driving legislation and observed driver behavior among population sub-groups in the United States

    Directory of Open Access Journals (Sweden)

    Toni M. Rudisill

    2017-05-01

    Full Text Available Abstract Background Cell phone use behaviors are known to vary across demographic sub-groups and geographic locations. This study examined whether universal hand-held calling while driving bans were associated with lower road-side observed hand-held cell phone conversations across drivers of different ages (16–24, 25–59, ≥60 years, sexes, races (White, African American, or other, ruralities (suburban, rural, or urban, and regions (Northeast, Midwest, South, and West. Methods Data from the 2008–2013 National Occupant Protection Use Survey were merged with states’ cell phone use while driving legislation. The exposure was presence of a universal hand-held cell phone ban at time of observation. Logistic regression was used to assess the odds of drivers having a hand-held cell phone conversation. Sub-groups differences were assessed using models with interaction terms. Results When universal hand-held cell phone bans were effective, hand-held cell phone conversations were lower across all driver demographic sub-groups and regions. Sub-group differences existed among the sexes (p-value, <0.0001 and regions (p-value, 0.0003. Compared to states without universal hand-held cell phone bans, the adjusted odds ratio (aOR of a driver hand-held phone conversation was 0.34 [95% confidence interval (CI: 0.28, 0.41] for females versus 0.47 (CI 0.40, 0.55 for males and 0.31 (CI 0.25, 0.38 for drivers in Western states compared to 0.47 (CI 0.30, 0.72 in the Northeast and 0.50 (CI 0.38, 0.66 in the South. Conclusions The presence of universal hand-held cell phone bans were associated lower hand-held cell phone conversations across all driver sub-groups and regions. Hand-held phone conversations were particularly lower among female drivers and those from Western states when these bans were in effect. Public health interventions concerning hand-held cell phone use while driving could reasonably target all drivers.

  4. Age, gender, mileage and the DBQ: The validity of the Driver Behavior Questionnaire in different driver groups

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Hakamies-Blomqvist, Liisa; Møller, Mette

    2013-01-01

    behavior using the original DBQ (Reason, J.T., Manstead, A., Stradling, S.G., Baxter, J., Campbell, K., 1990. Errors and violations on the road – a real distinction. Ergonomics, 33 (10/11), 1315–1332) to test the factorial validity and reliability of the instrument across different subgroups of Danish...

  5. Modeling merging behavior at lane drops : [tech transfer summary].

    Science.gov (United States)

    2015-02-01

    A better understanding of the merging behavior of drivers will lead : to the development of better lane-drop traffic-control plans and : strategies, which will provide better guidance to drivers for safer : merging.

  6. The Train Driver Recovery Problem - a Set Partitioning Based Model and Solution Method

    DEFF Research Database (Denmark)

    Rezanova, Natalia Jurjevna; Ryan, David

    2010-01-01

    The need to recover a train driver schedule occurs during major disruptions in the daily railway operations. Based on data from the Danish passenger railway operator DSB S-tog A/S, a solution method to the train driver recovery problem (TDRP) is developed. The TDRP is formulated as a set...... branching strategy using the depth-first search of the Branch & Bound tree. The LP relaxation of the TDRP possesses strong integer properties. We present test scenarios generated from the historical real-life operations data of DSB S-tog A/S. The numerical results show that all but one tested instances...... partitioning problem. We define a disruption neighbourhood by identifying a small set of drivers and train tasks directly affected by the disruption. Based on the disruption neighbourhood, the TDRP model is formed and solved. If the TDRP solution provides a feasible recovery for the drivers within...

  7. A Model for Traffic Accidents Prediction Based on Driver Personality Traits Assessment

    Directory of Open Access Journals (Sweden)

    Marjana Čubranić-Dobrodolac

    2017-12-01

    Full Text Available The model proposed in this paper uses four psychological instruments for assessing driver behaviour and personality traits aiming to find a relationship between the considered constructs and the occurrence of traffic accidents. A Barratt Impulsiveness Scale (BIS-11 was used for the assessment of impulsivity, Aggressive Driving Behaviour Questionnaire (ADBQ for assessing the aggressiveness while driving, Manchester Driver Attitude Questionnaire (DAQ and the Questionnaire for self-assessment of driving ability. Besides these instruments, the participants filled out an extensive demographic survey. Within the statistical analysis, in addition to the descriptive indicators, correlation coefficients were calculated and four hierarchical regression analyses were performed to determine the predictive power of personality traits on the occurrence of traffic accidents. Further, to confirm the results and to obtain additional information about the relationship between the considered variables, the structural equation modelling and binary logistic regression have been implemented. A sample of this research covered 305 drivers, of which there were 100 bus drivers and 102 truck drivers, as well as 103 drivers of privately owned vehicles. The results indicate that BIS-11 and ADBQ questionnaires show the best predictive power which means that impulsivity and aggressiveness as personality traits have the greatest influence on the occurrence of traffic accidents. This research could be useful in many fields, such as the design of selection procedures for professional drivers, development of programs for the prevention of traffic accidents and violations of law, rehabilitation of drivers who have been deprived of the driving license, etc.

  8. Driver behavior at highway-railroad grade crossings : a literature review from 1990-2006

    Science.gov (United States)

    2008-10-01

    Accidents at grade crossings continue to be the leading cause of fatalities in the railroad industry. A large proportion of these accidents are the result of driver error. The purpose of this report is to review research that addresses driver behavio...

  9. Global and Regional Ecosystem Modeling: Databases of Model Drivers and Validation Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Olson, R.J.

    2002-03-19

    Understanding global-scale ecosystem responses to changing environmental conditions is important both as a scientific question and as the basis for making policy decisions. The confidence in regional models depends on how well the field data used to develop the model represent the region of interest, how well the environmental model driving variables (e.g., vegetation type, climate, and soils associated with a site used to parameterize ecosystem models) represent the region of interest, and how well regional model predictions agree with observed data for the region. To assess the accuracy of global model forecasts of terrestrial carbon cycling, two Ecosystem Model-Data Intercomparison (EMDI) workshops were held (December 1999 and April 2001). The workshops included 17 biogeochemical, satellite-driven, detailed process, and dynamic vegetation global model types. The approach was to run regional or global versions of the models for sites with net primary productivity (NPP) measurements (i.e., not fine-tuned for specific site conditions) and analyze the model-data differences. Extensive worldwide NPP data were assembled with model driver data, including vegetation, climate, and soils data, to perform the intercomparison. This report describes the compilation of NPP estimates for 2,523 sites and 5,164 0.5{sup o}-grid cells under the Global Primary Production Data Initiative (GPPDI) and the results of the EMDI review and outlier analysis that produced a refined set of NPP estimates and model driver data. The EMDI process resulted in 81 Class A sites, 933 Class B sites, and 3,855 Class C cells derived from the original synthesis of NPP measurements and associated driver data. Class A sites represent well-documented study sites that have complete aboveground and below ground NPP measurements. Class B sites represent more numerous ''extensive'' sites with less documentation and site-specific information available. Class C cells represent estimates of

  10. Understanding social and behavioral drivers and impacts of air quality sensor use.

    Science.gov (United States)

    Hubbell, Bryan J; Kaufman, Amanda; Rivers, Louie; Schulte, Kayla; Hagler, Gayle; Clougherty, Jane; Cascio, Wayne; Costa, Dan

    2018-04-15

    Lower-cost air quality sensors (hundreds to thousands of dollars) are now available to individuals and communities. This technology is undergoing a rapid and fragmented evolution, resulting in sensors that have uncertain data quality, measure different air pollutants and possess a variety of design attributes. Why and how individuals and communities choose to use sensors is arguably influenced by social context. For example, community experiences with environmental exposures and health effects and related interactions with industry and government can affect trust in traditional air quality monitoring. To date, little social science research has been conducted to evaluate why or how sensors, and sensor data, are used by individuals and communities, or how the introduction of sensors changes the relationship between communities and air quality managers. This commentary uses a risk governance/responsible innovation framework to identify opportunities for interdisciplinary research that brings together social scientists with air quality researchers involved in developing, testing, and deploying sensors in communities. Potential areas for social science research include communities of sensor users; drivers for use of sensors and sensor data; behavioral, socio-political, and ethical implications of introducing sensors into communities; assessing methods for communicating sensor data; and harnessing crowdsourcing capabilities to analyze sensor data. Social sciences can enhance understanding of perceptions, attitudes, behaviors, and other human factors that drive levels of engagement with and trust in different types of air quality data. New transdisciplinary research bridging social sciences, natural sciences, engineering, and design fields of study, and involving citizen scientists working with professionals from a variety of backgrounds, can increase our understanding of air sensor technology use and its impacts on air quality and public health. Published by Elsevier B.V.

  11. Estimation of occupational and nonoccupational nitrogen dioxide exposure for Korean taxi drivers using a microenvironmental model

    International Nuclear Information System (INIS)

    Son, Busoon; Yang, Wonho; Breysse, Patrick; Chung, Taewoong; Lee, Youngshin

    2004-01-01

    Occupational and nonoccupational personal nitrogen dioxide (NO 2 ) exposures were measured using passive samplers for 31 taxi drivers in Asan and Chunan, Korea. Exposures were also estimated using a microenvironmental time-weighted average model based on indoor, outdoor and inside the taxi area measurements. Mean NO 2 indoor and outdoor concentrations inside and outside the taxi drivers' houses were 24.7±10.7 and 23.3±8.3 ppb, respectively, with a mean indoor to outdoor NO 2 ratio of 1.1. Mean personal NO 2 exposure of taxi drivers was 30.3±9.7 ppb. Personal NO 2 exposures for drivers were more strongly correlated with interior vehicle NO 2 levels (r=0.89) rather than indoor residential NO 2 levels (r=0.74) or outdoor NO 2 levels (r=0.71). The main source of NO 2 exposure for taxi drivers was considered to be occupational driving. Interestingly, the NO 2 exposures for drivers' using LPG-fueled vehicles (26.3±1.3 ppb) were significantly lower than those (38.1±1.3 ppb) using diesel-fueled vehicle (P 2 exposure with indoor and outdoor NO 2 levels of the residence, and interior vehicle NO 2 levels (P 2 levels because they drive diesel-using vehicles outdoors in Korea

  12. Uncertainty in predictions of forest carbon dynamics: separating driver error from model error.

    Science.gov (United States)

    Spadavecchia, L; Williams, M; Law, B E

    2011-07-01

    We present an analysis of the relative magnitude and contribution of parameter and driver uncertainty to the confidence intervals on estimates of net carbon fluxes. Model parameters may be difficult or impractical to measure, while driver fields are rarely complete, with data gaps due to sensor failure and sparse observational networks. Parameters are generally derived through some optimization method, while driver fields may be interpolated from available data sources. For this study, we used data from a young ponderosa pine stand at Metolius, Central Oregon, and a simple daily model of coupled carbon and water fluxes (DALEC). An ensemble of acceptable parameterizations was generated using an ensemble Kalman filter and eddy covariance measurements of net C exchange. Geostatistical simulations generated an ensemble of meteorological driving variables for the site, consistent with the spatiotemporal autocorrelations inherent in the observational data from 13 local weather stations. Simulated meteorological data were propagated through the model to derive the uncertainty on the CO2 flux resultant from driver uncertainty typical of spatially extensive modeling studies. Furthermore, the model uncertainty was partitioned between temperature and precipitation. With at least one meteorological station within 25 km of the study site, driver uncertainty was relatively small ( 10% of the total net flux), while parameterization uncertainty was larger, 50% of the total net flux. The largest source of driver uncertainty was due to temperature (8% of the total flux). The combined effect of parameter and driver uncertainty was 57% of the total net flux. However, when the nearest meteorological station was > 100 km from the study site, uncertainty in net ecosystem exchange (NEE) predictions introduced by meteorological drivers increased by 88%. Precipitation estimates were a larger source of bias in NEE estimates than were temperature estimates, although the biases partly

  13. Research on Evaluation Model for Secondary Task Driving Safety Based on Driver Eye Movements

    Directory of Open Access Journals (Sweden)

    Lisheng Jin

    2014-01-01

    Full Text Available This study was designed to gain insight into the influence of performing different types of secondary task while driving on driver eye movements and to build a safety evaluation model for secondary task driving. Eighteen young drivers were selected and completed the driving experiment on a driving simulator. Measures of fixations, saccades, and blinks were analyzed. Based on measures which had significant difference between the baseline and secondary tasks driving conditions, the evaluation index system was built. Method of principal component analysis (PCA was applied to analyze evaluation indexes data in order to obtain the coefficient weights of indexes and build the safety evaluation model. Based on evaluation scores, the driving safety was grouped into five levels (very high, high, average, low, and very low using K-means clustering algorithm. Results showed that secondary task driving severely distracts the driver and the evaluation model built in this study could estimate driving safety effectively under different driving conditions.

  14. MACRO MODEL OF SEAT BELT USE BY CAR DRIVERS AND PASSENGERS

    Directory of Open Access Journals (Sweden)

    Kazimierz JAMROZ

    2013-12-01

    Full Text Available The article presents some problems of seat belt use by car drivers and passengers. It looks in particular at seat belt use and effectiveness in selected countries. Next, factors of seat belt use are presented and methodology of model development. A macro model of seat belt use is presented based on data from around fifty countries from different continents.

  15. Study on behavior of car and driver in the very small commuter car made of FRP during collision using scale model. Under the consideration of thorax deformation of driver using airbag; FRP sei mokei ni yoru FRP sei chokeiryo jissha shototsuji no kuruma to join no anzensei ni kansuru kenkyu. Kyobu henkei tokusei wo yusuru join ni taisuru air gab no koka

    Energy Technology Data Exchange (ETDEWEB)

    Sakai, H; Morisawa, M; Yoshino, T [Musashi Institute of Technology, Tokyo (Japan); Sato, T [Keio University, Tokyo (Japan); Ishizuki, H [Satake Co., Tokyo (Japan)

    1997-10-01

    In this study, after having performed simulation which took up scale models substituting for full scale model of commuter car made of FRP, we carried out collision tests to barrier. Here, we made enquiries about the occupant safety by changing the collision speed and the deformation characteristics of the seat belt, during head-on barrier collision using one-fifth scale models. We sought for the occupant`s safe combinations among the deformation characteristics of airbag and the thorax deformation. In this case, the degree of the occupants injury were estimated using HIC values, 3msecG and maximum deformation of the thorax. 7 refs., 5 figs.

  16. The Intention in Speeding Behavior between Low and High Intended Young Driver in Urban University

    Directory of Open Access Journals (Sweden)

    Mohamad Ghazali Masuri,

    2016-01-01

    Full Text Available The number of road traffic accidents among young adult aged under 25 years old is an alarming issue in Malaysia. A five pages self-reported questionnaire was distributed to 384 young drivers' to investigate their intention in speeding while driving. Results have shown, the intention to speed among low and high intended based line group revealed a significant difference when it was compared with four types of scenario. Correct stimulation while driving could help drivers to change their intention to speed. This stimulation may be able to reduce the drivers' potential to involve with an accident and will save peoples' life.

  17. Aligning drivers, contract, and management of IT-outsourcing relationships: a type-dependent model

    DEFF Research Database (Denmark)

    Arenfeldt, Katrine; Corty Dam, Amalie; Fenger, Kim Harder

    2017-01-01

    In today’s competitive business environment, information technology outsourcing has become a wide-spread reality across all industries and sectors. Researchers have investigated this complex phenomenon from various angles, and established a sound knowledge base regarding the drivers, management......, and success factors related to IT outsourcing. However, little is known about the relationship between outsourcing drivers and goals on the one hand, and contractual and managerial aspects on the other hand. To overcome this gap, this study presents a synthesized conceptual model of existing literature...... that relates aspects of contractual governance and relationship management to three generic types of IT outsourcing, based on their underlying drivers: task-based, process-based, and partnership-based outsourcing. Our model identifies the specific contractual and managerial factors relevant for each type...

  18. Optimizing Cruising Routes for Taxi Drivers Using a Spatio-Temporal Trajectory Model

    Directory of Open Access Journals (Sweden)

    Liang Wu

    2017-11-01

    Full Text Available Much of the taxi route-planning literature has focused on driver strategies for finding passengers and determining the hot spot pick-up locations using historical global positioning system (GPS trajectories of taxis based on driver experience, distance from the passenger drop-off location to the next passenger pick-up location and the waiting times at recommended locations for the next passenger. The present work, however, considers the average taxi travel speed mined from historical taxi GPS trajectory data and the allocation of cruising routes to more than one taxi driver in a small-scale region to neighboring pick-up locations. A spatio-temporal trajectory model with load balancing allocations is presented to not only explore pick-up/drop-off information but also provide taxi drivers with cruising routes to the recommended pick-up locations. In simulation experiments, our study shows that taxi drivers using cruising routes recommended by our spatio-temporal trajectory model can significantly reduce the average waiting time and travel less distance to quickly find their next passengers, and the load balancing strategy significantly alleviates road loads. These objective measures can help us better understand spatio-temporal traffic patterns and guide taxi navigation.

  19. Motivational Interviewing support for a behavioral health internet intervention for drivers with type 1 diabetes

    Directory of Open Access Journals (Sweden)

    Karen S. Ingersoll

    2015-05-01

    Full Text Available While Internet interventions can improve health behaviors, their impact is limited by program adherence. Supporting program adherence through telephone counseling may be useful, but there have been few direct tests of the impact of support. We describe a Telephone Motivational Interviewing (MI intervention targeting adherence to an Internet intervention for drivers with Type 1 Diabetes, DD.com, and compare completion of intervention benchmarks by those randomized to DD.com plus MI vs. DD.com only. The goal of the pre-intervention MI session was to increase the participant's motivation to complete the Internet intervention and all its assignments, while the goal of the post-treatment MI session was to plan for maintaining changes made during the intervention. Sessions were semi-structured and partially scripted to maximize consistency. MI Fidelity was coded using a standard coding system, the MITI. We examined the effects of MI support vs. no support on number of days from enrollment to program benchmarks. Results show that MI sessions were provided with good fidelity. Users who received MI support completed some program benchmarks such as Core 4 (t176 df = −2.25; p < .03 and 11 of 12 monthly driving diaries significantly sooner, but support did not significantly affect time to intervention completion (t177 df = −1.69; p < .10 or rates of completion. These data suggest that there is little benefit to therapist guidance for Internet interventions including automated email prompts and other automated minimal supports, but that a booster MI session may enhance collection of follow-up data.

  20. Driver behavior in car-to-pedestrian incidents: An application of the Driving Reliability and Error Analysis Method (DREAM).

    Science.gov (United States)

    Habibovic, Azra; Tivesten, Emma; Uchida, Nobuyuki; Bärgman, Jonas; Ljung Aust, Mikael

    2013-01-01

    To develop relevant road safety countermeasures, it is necessary to first obtain an in-depth understanding of how and why safety-critical situations such as incidents, near-crashes, and crashes occur. Video-recordings from naturalistic driving studies provide detailed information on events and circumstances prior to such situations that is difficult to obtain from traditional crash investigations, at least when it comes to the observable driver behavior. This study analyzed causation in 90 video-recordings of car-to-pedestrian incidents captured by onboard cameras in a naturalistic driving study in Japan. The Driving Reliability and Error Analysis Method (DREAM) was modified and used to identify contributing factors and causation patterns in these incidents. Two main causation patterns were found. In intersections, drivers failed to recognize the presence of the conflict pedestrian due to visual obstructions and/or because their attention was allocated towards something other than the conflict pedestrian. In incidents away from intersections, this pattern reoccurred along with another pattern showing that pedestrians often behaved in unexpected ways. These patterns indicate that an interactive advanced driver assistance system (ADAS) able to redirect the driver's attention could have averted many of the intersection incidents, while autonomous systems may be needed away from intersections. Cooperative ADAS may be needed to address issues raised by visual obstructions. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. A brief peripheral motion contrast threshold test predicts older drivers' hazardous behaviors in simulated driving.

    Science.gov (United States)

    Henderson, Steven; Woods-Fry, Heather; Collin, Charles A; Gagnon, Sylvain; Voloaca, Misha; Grant, John; Rosenthal, Ted; Allen, Wade

    2015-05-01

    Our research group has previously demonstrated that the peripheral motion contrast threshold (PMCT) test predicts older drivers' self-report accident risk, as well as simulated driving performance. However, the PMCT is too lengthy to be a part of a battery of tests to assess fitness to drive. Therefore, we have developed a new version of this test, which takes under two minutes to administer. We assessed the motion contrast thresholds of 24 younger drivers (19-32) and 25 older drivers (65-83) with both the PMCT-10min and the PMCT-2min test and investigated if thresholds were associated with measures of simulated driving performance. Younger participants had significantly lower motion contrast thresholds than older participants and there were no significant correlations between younger participants' thresholds and any measures of driving performance. The PMCT-10min and the PMCT-2min thresholds of older drivers' predicted simulated crash risk, as well as the minimum distance of approach to all hazards. This suggests that our tests of motion processing can help predict the risk of collision or near collision in older drivers. Thresholds were also correlated with the total lane deviation time, suggesting a deficiency in processing of peripheral flow and delayed detection of adjacent cars. The PMCT-2min is an improved version of a previously validated test, and it has the potential to help assess older drivers' fitness to drive. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Automan : A psychologically based model of a human driver

    NARCIS (Netherlands)

    Quispel, L; Warris, S; Heemskerk, A; Mulder, LJM; van Wolffelaar, PC; Maarse, FJ; Akkerman, AE; Brand, AN; Mulder, LJM

    2003-01-01

    This paper describes the design of an autonomous agent for controlling vehicles in a traffic simulator. This agent is based on recent developments in artificial intelligence, autonomous robotics and cognitive psychology. The goal of the agent is to simulate realistic driving behavior. The agent is

  3. In-depth analysis of drivers' merging behavior and rear-end crash risks in work zone merging areas.

    Science.gov (United States)

    Weng, Jinxian; Xue, Shan; Yang, Ying; Yan, Xuedong; Qu, Xiaobo

    2015-04-01

    This study investigates the drivers' merging behavior and the rear-end crash risk in work zone merging areas during the entire merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. With the merging traffic data from a work zone site in Singapore, a mixed probit model is developed to describe the merging behavior, and two surrogate safety measures including the time to collision (TTC) and deceleration rate to avoid the crash (DRAC) are adopted to compute the rear-end crash risk between the merging vehicle and its neighboring vehicles. Results show that the merging vehicle has a bigger probability of completing a merging maneuver quickly under one of the following situations: (i) the merging vehicle moves relatively fast; (ii) the merging lead vehicle is a heavy vehicle; and (iii) there is a sizable gap in the adjacent through lane. Results indicate that the rear-end crash risk does not monotonically increase as the merging vehicle speed increases. The merging vehicle's rear-end crash risk is also affected by the vehicle type. There is a biggest increment of rear-end crash risk if the merging lead vehicle belongs to a heavy vehicle. Although the reduced remaining distance to work zone could urge the merging vehicle to complete a merging maneuver quickly, it might lead to an increased rear-end crash risk. Interestingly, it is found that the rear-end crash risk could be generally increased over the elapsed time after the merging maneuver being triggered. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. TARDEC FIXED HEEL POINT (FHP): DRIVER CAD ACCOMMODATION MODEL VERIFICATION REPORT

    Science.gov (United States)

    2017-11-09

    Public Release Disclaimer: Reference herein to any specific commercial company, product , process, or service by trade name, trademark, manufacturer , or...not actively engaged HSI until MSB or the Engineering Manufacturing and Development (EMD) Phase, resulting in significant design and cost changes...and shall not be used for advertising or product endorsement purposes. TARDEC Fixed Heel Point (FHP): Driver CAD Accommodation Model Verification

  5. Model and Design of a Power Driver for Piezoelectric Stack Actuators

    Directory of Open Access Journals (Sweden)

    Chiaberge M

    2010-01-01

    Full Text Available A power driver has been developed to control piezoelectric stack actuators used in automotive application. An FEM model of the actuator has been implemented starting from experimental characterization of the stack and mechanical and piezoelectric parameters. Experimental results are reported to show a correct piezoelectric actuator driving method and the possibility to obtain a sensorless positioning control.

  6. Understanding the structural drivers governing glass-water interactions in borosilicate based model bioactive glasses.

    Science.gov (United States)

    Stone-Weiss, Nicholas; Pierce, Eric M; Youngman, Randall E; Gulbiten, Ozgur; Smith, Nicholas J; Du, Jincheng; Goel, Ashutosh

    2018-01-01

    borosilicate based model melt-quenched bioactive glass system has been studied to depict the impact of thermal history on its molecular structure and dissolution behavior in water. It has been shown that the methodology of quenching of the glass melt impacts the dissolution rate of the studied glasses by 1.5×-3× depending on the changes induced in their molecular structure due to variation in thermal history. Further, a recommendation has been made to study dissolution behavior of bioactive glasses using surface area of the sample - to - volume of solution (SA/V) approach instead of the currently followed mass of sample - to - volume of solution approach. The structural and chemical dissolution data obtained from bioactive glasses following the approach presented in this paper can be used to develop the structural descriptors and potential energy functions over a broad range of bioactive glass compositions. Realizing the goal of designing third generation bioactive glasses requires a thorough understanding of the complex sequence of reactions that control their rate of degradation (in physiological fluids) and the structural drivers that control them. In this article, we have highlighted some major experimental challenges and choices that need to be carefully navigated in order to unearth the mechanisms governing the chemical dissolution behavior of borosilicate based bioactive glasses. The proposed experimental approach allows us to gain a new level of conceptual understanding about the composition-structure-property relationships in these glass systems, which can be applied to attain a significant leap in designing borosilicate based bioactive glasses with controlled dissolution rates tailored for specific patient and disease states. Copyright © 2017 Acta Materialia Inc. All rights reserved.

  7. Associating crash avoidance maneuvers with driver attributes and accident characteristics: a mixed logit model approach.

    Science.gov (United States)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that represents the selection among 5 emergency lateral and speed control maneuvers (i.e., "no avoidance maneuvers," "braking," "steering," "braking and steering," and "other maneuvers) while accommodating correlations across maneuvers and heteroscedasticity. Data for the analysis were retrieved from the General Estimates System (GES) crash database for the year 2009 by considering drivers for which crash avoidance maneuvers are known. The results show that (1) the nature of the critical event that made the crash imminent greatly influences the choice of crash avoidance maneuvers, (2) women and elderly have a relatively lower propensity to conduct crash avoidance maneuvers, (3) drowsiness and fatigue have a greater negative marginal effect on the tendency to engage in crash avoidance maneuvers than alcohol and drug consumption, (4) difficult road conditions increase the propensity to perform crash avoidance maneuvers, and (5) visual obstruction and artificial illumination decrease the probability to carry out crash avoidance maneuvers. The results emphasize the need for public awareness campaigns to promote safe driving style for senior drivers and warning about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing

  8. Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control

    NARCIS (Netherlands)

    Croon, E.M. de; Blonk, R.W.B.; Zwart, B.C.H. de; Frings-Dresen, M.H.W.; Broersen, J.P.J.

    2002-01-01

    Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands on fatigue and job dissatisfaction in Dutch lorry drivers. From 1181 lorry drivers self reported information was

  9. A rear-end collision risk assessment model based on drivers' collision avoidance process under influences of cell phone use and gender-A driving simulator based study.

    Science.gov (United States)

    Li, Xiaomeng; Yan, Xuedong; Wu, Jiawei; Radwan, Essam; Zhang, Yuting

    2016-12-01

    Driver's collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the driver's performance on road. This study aimed to investigate the manner and extent to which cell phone use and driver's gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicle's sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and driver's gender. The cell phone use and driver's gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in

  10. Omnichannel Customer Behavior: Key Drivers of Technology Acceptance and Use and Their Effects on Purchase Intention

    Science.gov (United States)

    Juaneda-Ayensa, Emma; Mosquera, Ana; Sierra Murillo, Yolanda

    2016-01-01

    The advance of the Internet and new technologies over the last decade has transformed the retailing panorama. More and more channels are emerging, causing consumers to change their habits and shopping behavior. An omnichannel strategy is a form of retailing that, by enabling real interaction, allows customers to shop across channels anywhere and at any time, thereby providing them with a unique, complete, and seamless shopping experience that breaks down the barriers between channels. This paper aims to identify the factors that influence omnichannel consumers' behavior through their acceptance of and intention to use new technologies during the shopping process. To this end, an original model was developed to explain omnichannel shopping behavior based on the variables used in the UTAUT2 model and two additional factors: personal innovativeness and perceived security. The model was tested with a sample of 628 Spanish customers of the store Zara who had used at least two channels during their most recent shopping journey. The results indicate that the key determinants of purchase intention in an omnichannel context are, in order of importance: personal innovativeness, effort expectancy, and performance expectancy. The theoretical and managerial implications are discussed. PMID:27516749

  11. Omnichannel Customer Behavior: Key Drivers of Technology Acceptance and Use and Their Effects on Purchase Intention

    Directory of Open Access Journals (Sweden)

    Ana Mosquera

    2016-07-01

    Full Text Available The advance of the Internet and new technologies over the last decade has transformed the retailing panorama. More and more channels are emerging, causing consumers to change their habits and shopping behavior. An omnichannel strategy is a form of retailing that, by enabling real interaction, allows customers to shop across channels anywhere and at any time, thereby providing them with a unique, complete, and seamless shopping experience that breaks down the barriers between channels. This paper aims to identify the factors that influence omnichannel consumers’ behavior through their acceptance of and intention to use new technologies during the shopping process. To this end, an original model was developed to explain omnichannel shopping behavior based on the variables used in the UTAUT2 model and two additional factors: personal innovativeness and perceived security. The model was tested with a sample of 628 Spanish customers of the store Zara who had used at least two channels during their most recent shopping journey. The results indicate that the key determinants of purchase intention in an omnichannel context are, in order of importance: personal innovativeness, effort expectancy, and performance expectancy. The theoretical and managerial implications are discussed.

  12. Omnichannel Customer Behavior: Key Drivers of Technology Acceptance and Use and Their Effects on Purchase Intention.

    Science.gov (United States)

    Juaneda-Ayensa, Emma; Mosquera, Ana; Sierra Murillo, Yolanda

    2016-01-01

    The advance of the Internet and new technologies over the last decade has transformed the retailing panorama. More and more channels are emerging, causing consumers to change their habits and shopping behavior. An omnichannel strategy is a form of retailing that, by enabling real interaction, allows customers to shop across channels anywhere and at any time, thereby providing them with a unique, complete, and seamless shopping experience that breaks down the barriers between channels. This paper aims to identify the factors that influence omnichannel consumers' behavior through their acceptance of and intention to use new technologies during the shopping process. To this end, an original model was developed to explain omnichannel shopping behavior based on the variables used in the UTAUT2 model and two additional factors: personal innovativeness and perceived security. The model was tested with a sample of 628 Spanish customers of the store Zara who had used at least two channels during their most recent shopping journey. The results indicate that the key determinants of purchase intention in an omnichannel context are, in order of importance: personal innovativeness, effort expectancy, and performance expectancy. The theoretical and managerial implications are discussed.

  13. Driver braking behavior analysis to improve autonomous emergency braking systems in typical Chinese vehicle-bicycle conflicts.

    Science.gov (United States)

    Duan, Jingliang; Li, Renjie; Hou, Lian; Wang, Wenjun; Li, Guofa; Li, Shengbo Eben; Cheng, Bo; Gao, Hongbo

    2017-11-01

    Bicycling is one of the fundamental modes of transportation especially in developing countries. Because of the lack of effective protection for bicyclists, vehicle-bicycle (V-B) accident has become a primary contributor to traffic fatalities. Although AEB (Autonomous Emergency Braking) systems have been developed to avoid or mitigate collisions, they need to be further adapted in various conflict situations. This paper analyzes the driver's braking behavior in typical V-B conflicts of China to improve the performance of Bicyclist-AEB systems. Naturalistic driving data were collected, from which the top three scenarios of V-B accidents in China were extracted, including SCR (a bicycle crossing the road from right while a car is driving straight), SCL (a bicycle crossing the road from left while a car is driving straight) and SSR (a bicycle swerving in front of the car from right while a car is driving straight). For safety and data reliability, a driving simulator was employed to reconstruct these three scenarios and some 25 licensed drivers were recruited for braking behavior analysis. Results revealed that driver's braking behavior was significantly influenced by V-B conflict types. Pre-decelerating behaviors were found in SCL and SSR conflicts, whereas in SCR the subjects were less vigilant. The brake reaction time and brake severity in lateral V-B conflicts (SCR and SCL) was shorter and higher than that in longitudinal conflicts (SSR). The findings improve their applications in the Bicyclist-AEB and test protocol enactment to enhance the performance of Bicyclist-AEB systems in mixed traffic situations especially for developing countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Gas Turbine Engine Behavioral Modeling

    OpenAIRE

    Meyer, Richard T; DeCarlo, Raymond A.; Pekarek, Steve; Doktorcik, Chris

    2014-01-01

    This paper develops and validates a power flow behavioral model of a gas tur- bine engine with a gas generator and free power turbine. “Simple” mathematical expressions to describe the engine’s power flow are derived from an understand- ing of basic thermodynamic and mechanical interactions taking place within the engine. The engine behavioral model presented is suitable for developing a supervisory level controller of an electrical power system that contains the en- gine connected to a gener...

  15. Behavior genetics: Bees as model

    International Nuclear Information System (INIS)

    Nates Parra, Guiomar

    2011-01-01

    The honeybee Apis mellifera (Apidae) is a model widely used in behavior because of its elaborate social life requiring coordinate actions among the members of the society. Within a colony, division of labor, the performance of tasks by different individuals, follows genetically determined physiological changes that go along with aging. Modern advances in tools of molecular biology and genomics, as well as the sequentiation of A. mellifera genome, have enabled a better understanding of honeybee behavior, in particular social behavior. Numerous studies show that aspects of worker behavior are genetically determined, including defensive, hygienic, reproductive and foraging behavior. For example, genetic diversity is associated with specialization to collect water, nectar and pollen. Also, control of worker reproduction is associated with genetic differences. In this paper, I review the methods and the main results from the study of the genetic and genomic basis of some behaviors in bees.

  16. A new coupled map car-following model considering drivers' steady desired speed

    International Nuclear Information System (INIS)

    Zhou Tong; Sun Di-Hua; Li Hua-Min; Liu Wei-Ning

    2014-01-01

    Based on the pioneering work of Konishi et al., in consideration of the influence of drivers' steady desired speed effect on the traffic flow, we develop a new coupled map car-following model in the real world. By use of the control theory, the stability condition of our model is derived. The validity of the present theoretical scheme is verified via numerical simulation, confirming the correctness of our theoretical analysis. (general)

  17. Estimating Neutral Atmosphere Drivers using a Physical Model

    Science.gov (United States)

    2009-03-30

    Araujo-Pradere, M. Fedrizzi, 2007, Memory effects in the ionosphere storm response. EGU General Assembly , Vienna, Austria Codrescu, M., T.J. Fuller...Strickland, D, 2007: Application of thermospheric general circulation models for space weather operations. J. Adv. Space Res., edited by Schmidtke

  18. Modelling intelligent behavior

    Science.gov (United States)

    Green, H. S.; Triffet, T.

    1993-01-01

    An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

  19. Model analysis of the effects of atmospheric drivers on storage water use in Scots pine

    Directory of Open Access Journals (Sweden)

    H. Verbeeck

    2007-08-01

    Full Text Available Storage water use is an indirect consequence of the interplay between different meteorological drivers through their effect on water flow and water potential in trees. We studied these microclimatic drivers of storage water use in Scots pine (Pinus sylvestris L. growing in a temperate climate. The storage water use was modeled using the ANAFORE model, integrating a dynamic water flow and – storage model with a process-based transpiration model. The model was calibrated and validated with sap flow measurements for the growing season of 2000 (26 May–18 October.

    Because there was no severe soil drought during the study period, we were able to study atmospheric effects. Incoming radiation and vapour pressure deficit (VPD were the main atmospheric drivers of storage water use. The general trends of sap flow and storage water use are similar, and follow more or less the pattern of incoming radiation. Nevertheless, considerable differences in the day-to-day pattern of sap flow and storage water use were observed. VPD was determined to be one of the main drivers of these differences. During dry atmospheric conditions (high VPD storage water use was reduced. This reduction was higher than the reduction in measured sap flow. Our results suggest that the trees did not rely more on storage water during periods of atmospheric drought, without severe soil drought. The daily minimum tree water content was lower in periods of high VPD, but the reserves were not completely depleted after the first day of high VPD, due to refilling during the night.

    Nevertheless, the tree water content deficit was a third important factor influencing storage water use. When storage compartments were depleted beyond a threshold, storage water use was limited due to the low water potential in the storage compartments. The maximum relative contribution of storage water to daily transpiration was also constrained by an increasing tree water content

  20. Inferring Passenger Denial Behavior of Taxi Drivers from Large-Scale Taxi Traces.

    Directory of Open Access Journals (Sweden)

    Sihai Zhang

    Full Text Available How to understand individual human actions is a fundamental question to modern science, which drives and incurs many social, technological, racial, religious and economic phenomena. Human dynamics tries to reveal the temporal pattern and internal mechanism of human actions in letter or electronic communications, from the perspective of continuous interactions among friends or acquaintances. For interactions between stranger to stranger, taxi industry provide fruitful phenomina and evidence to investigate the action decisions. In fact, one striking disturbing events commonly reported in taxi industry is passenger refusing or denial, whose reasons vary, including skin color, blind passenger, being a foreigner or too close destination, religion reasons and anti specific nationality, so that complaints about taxi passenger refusing have to be concerned and processed carefully by local governments. But more universal factors for this phenomena are of great significance, which might be fulfilled by big data research to obtain novel insights in this question. In this paper, we demonstrate the big data analytics application in revealing novel insights from massive taxi trace data, which, for the first time, validates the passengers denial in taxi industry and estimates the denial ratio in Beijing city. We first quantify the income differentiation facts among taxi drivers. Then we find out that choosing the drop-off places also contributes to the high income for taxi drivers, compared to the previous explanation of mobility intelligence. Moreover, we propose the pick-up, drop-off and grid diversity concepts and related diversity analysis suggest that, high income taxi drivers will deny passengers in some situations, so as to choose the passengers' destination they prefer. Finally we design an estimation method for denial ratio and infer that high income taxi drivers will deny passengers with 8.52% likelihood in Beijing. Our work exhibits the power of big

  1. Leveraging accelerated testing of LED drivers to model the reliability of two-stage and multi-channel drivers

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Lynn; Perkins, Curtis; Smith, Aaron; Clark, Terry; Mills, Karmann

    2017-05-30

    The next wave of LED lighting technology is likely to be tunable white lighting (TWL) devices which can adjust the colour of the emitted light between warm white (~ 2700 K) and cool white (~ 6500 K). This type of lighting system uses LED assemblies of two or more colours each controlled by separate driver channels that independently adjust the current levels to achieve the desired lighting colour. Drivers used in TWL devices are inherently more complex than those found in simple SSL devices, due to the number of electrical components in the driver required to achieve this level of control. The reliability of such lighting systems can only be studied using accelerated stress tests (AST) that accelerate the aging process to time frames that can be accommodated in laboratory testing. This paper describes AST methods and findings developed from AST data that provide insights into the lifetime of the main components of one-channel and multi-channel LED devices. The use of AST protocols to confirm product reliability is necessary to ensure that the technology can meet the performance and lifetime requirements of the intended application.

  2. Driving simulator validation of driver behavior with limited safe vantage points for data collection in work zones.

    Science.gov (United States)

    Bham, Ghulam H; Leu, Ming C; Vallati, Manoj; Mathur, Durga R

    2014-06-01

    This study is aimed at validating a driving simulator (DS) for the study of driver behavior in work zones. A validation study requires field data collection. For studies conducted in highway work zones, the availability of safe vantage points for data collection at critical locations can be a significant challenge. A validation framework is therefore proposed in this paper, demonstrated using a fixed-based DS that addresses the issue by using a global positioning system (GPS). The validation of the DS was conducted using objective and subjective evaluations. The objective validation was divided into qualitative and quantitative evaluations. The DS was validated by comparing the results of simulation with the field data, which were collected using a GPS along the highway and video recordings at specific locations in a work zone. The constructed work zone scenario in the DS was subjectively evaluated with 46 participants. The objective evaluation established the absolute and relative validity of the DS. The mean speeds from the DS data showed excellent agreement with the field data. The subjective evaluation indicated realistic driving experience by the participants. The use of GPS showed that continuous data collected along the highway can overcome the challenges of unavailability of safe vantage points especially at critical locations. Further, a validated DS can be used for examining driver behavior in complex situations by replicating realistic scenarios. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Effectiveness of a Program Using a Vehicle Tracking System, Incentives, and Disincentives to Reduce the Speeding Behavior of Drivers with ADHD

    Science.gov (United States)

    Markham, Paula T.; Porter, Bryan E.; Ball, J. D.

    2013-01-01

    Objective: In this article, the authors investigated the effectiveness of a behavior modification program using global positioning system (GPS) vehicle tracking devices with contingency incentives and disincentives to reduce the speeding behavior of drivers with ADHD. Method: Using an AB multiple-baseline design, six participants drove a 5-mile…

  4. Effect of an Educational Program Based on the Health Belief Model to Reduce Cell Phone Usage During Driving in Taxi drivers

    Directory of Open Access Journals (Sweden)

    Babak Moeini

    2014-09-01

    Full Text Available Introduction: Cell phone usage during driving has become a threat to traffic safety. This study aimed to determine the effectiveness of an educational program based on the health belief model to reduce cell phone usage during driving in taxi drivers of Tuyserkan. Materials and Methods: In this quasi-experimental study, 110 taxi drivers younger than 35 years were randomly divided into two experimental and control groups in Tuyserkan, Iran. Data was collected using a questionnaire including the health belief model constructs, knowledge, behaviors of using cell phone and demographic variables. The questionnaires were self-reported. Intervention was three sessions applied in the experimental group. Both groups were followed for two months after the intervention. Finally, data analysis was performed using SPSS- 19 by Chi-square, Independent T-test, Paired T-test and McNemar. Results: The mean scores for the constructs of health belief model (perceived susceptibility, severity, barriers, perceived benefits, self-efficacy and cues to action, knowledge and desired behaviors about the use of cell phone during driving showed no significant differences between the two groups before the intervention. After the educational intervention, significant differences were observed in experimental group compared to control group. After educational intervention, cell phone usage reduced by 35.14% in the experimental group. Conclusion: An educational intervention based on the health belief model could reduce cell phone usage during driving in taxi drivers.

  5. Comparison of Microscopic Drivers' Probabilistic Lane-changing Models With Real Traffic Microscopic Data

    Directory of Open Access Journals (Sweden)

    Seyyed Mohammad Sadat Hoseini

    2011-07-01

    Full Text Available The difficulties of microscopic-level simulation models to accurately reproduce real traffic phenomena stem not only from the complexity of calibration and validation operations, but also from the structural inadequacies of the sub-models themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty in gathering accurate field data. This paper studies the traffic behaviour of individual drivers utilizing vehicle trajectory data extracted from digital images collected from freeways in Iran. These data are used to evaluate the four proposed microscopic traffic models. One of the models is based on the traffic regulations in Iran and the three others are probabilistic models that use a decision factor for calculating the probability of choosing a position on the freeway by a driver. The decision factors for three probabilistic models are increasing speed, decreasing risk of collision, and increasing speed combined with decreasing risk of collision. The models are simulated by a cellular automata simulator and compared with the real data. It is shown that the model based on driving regulations is not valid, but that other models appear useful for predicting the driver’s behaviour on freeway segments in Iran during noncongested conditions.

  6. Behavior model for performance assessment

    International Nuclear Information System (INIS)

    Brown-VanHoozer, S. A.

    1999-01-01

    Every individual channels information differently based on their preference of the sensory modality or representational system (visual auditory or kinesthetic) we tend to favor most (our primary representational system (PRS)). Therefore, some of us access and store our information primarily visually first, some auditorily, and others kinesthetically (through feel and touch); which in turn establishes our information processing patterns and strategies and external to internal (and subsequently vice versa) experiential language representation. Because of the different ways we channel our information, each of us will respond differently to a task--the way we gather and process the external information (input), our response time (process), and the outcome (behavior). Traditional human models of decision making and response time focus on perception, cognitive and motor systems stimulated and influenced by the three sensory modalities, visual, auditory and kinesthetic. For us, these are the building blocks to knowing how someone is thinking. Being aware of what is taking place and how to ask questions is essential in assessing performance toward reducing human errors. Existing models give predications based on time values or response times for a particular event, and may be summed and averaged for a generalization of behavior(s). However, by our not establishing a basic understanding of the foundation of how the behavior was predicated through a decision making strategy process, predicative models are overall inefficient in their analysis of the means by which behavior was generated. What is seen is the end result

  7. Behavior model for performance assessment.

    Energy Technology Data Exchange (ETDEWEB)

    Borwn-VanHoozer, S. A.

    1999-07-23

    Every individual channels information differently based on their preference of the sensory modality or representational system (visual auditory or kinesthetic) we tend to favor most (our primary representational system (PRS)). Therefore, some of us access and store our information primarily visually first, some auditorily, and others kinesthetically (through feel and touch); which in turn establishes our information processing patterns and strategies and external to internal (and subsequently vice versa) experiential language representation. Because of the different ways we channel our information, each of us will respond differently to a task--the way we gather and process the external information (input), our response time (process), and the outcome (behavior). Traditional human models of decision making and response time focus on perception, cognitive and motor systems stimulated and influenced by the three sensory modalities, visual, auditory and kinesthetic. For us, these are the building blocks to knowing how someone is thinking. Being aware of what is taking place and how to ask questions is essential in assessing performance toward reducing human errors. Existing models give predications based on time values or response times for a particular event, and may be summed and averaged for a generalization of behavior(s). However, by our not establishing a basic understanding of the foundation of how the behavior was predicated through a decision making strategy process, predicative models are overall inefficient in their analysis of the means by which behavior was generated. What is seen is the end result.

  8. [The use of biological age on mental work capacity model in accelerated aging assessment of professional lorry-drivers].

    Science.gov (United States)

    Bashkireva, A S

    2012-01-01

    The studies of biological age, aging rate, mental work capacity in professional drivers were conducted. The examination revealed peculiarities of system organization of functions determining the mental work capacity levels. Dynamics of the aging process of professional driver's organism in relation with calendar age and driving experience were shown using the biological age model. The results point at the premature decrease of the mental work capacity in professional drivers. It was proved, that premature age-related changes of physiologic and psychophysiologic indices in drivers are just "risk indicators", while long driving experience is a real risk factor, accelerating the aging process. The "risk group" with manifestations of accelerating aging was observed in 40-49-year old drivers with 15-19 years of professional experience. The expediency of using the following methods for the age rate estimation according to biologic age indices and necessity of prophylactic measures for premature and accelerated aging prevention among working population was demonstrated.

  9. Machine learning methods for locating re-entrant drivers from electrograms in a model of atrial fibrillation

    Science.gov (United States)

    McGillivray, Max Falkenberg; Cheng, William; Peters, Nicholas S.; Christensen, Kim

    2018-04-01

    Mapping resolution has recently been identified as a key limitation in successfully locating the drivers of atrial fibrillation (AF). Using a simple cellular automata model of AF, we demonstrate a method by which re-entrant drivers can be located quickly and accurately using a collection of indirect electrogram measurements. The method proposed employs simple, out-of-the-box machine learning algorithms to correlate characteristic electrogram gradients with the displacement of an electrogram recording from a re-entrant driver. Such a method is less sensitive to local fluctuations in electrical activity. As a result, the method successfully locates 95.4% of drivers in tissues containing a single driver, and 95.1% (92.6%) for the first (second) driver in tissues containing two drivers of AF. Additionally, we demonstrate how the technique can be applied to tissues with an arbitrary number of drivers. In its current form, the techniques presented are not refined enough for a clinical setting. However, the methods proposed offer a promising path for future investigations aimed at improving targeted ablation for AF.

  10. Behavior Modeling -- Foundations and Applications

    DEFF Research Database (Denmark)

    This book constitutes revised selected papers from the six International Workshops on Behavior Modelling - Foundations and Applications, BM-FA, which took place annually between 2009 and 2014. The 9 papers presented in this volume were carefully reviewed and selected from a total of 58 papers...

  11. Modelling of agricultural combination driver behaviour from the aspect of safety of movement

    Directory of Open Access Journals (Sweden)

    Jan Szczepaniak

    2014-06-01

    Full Text Available Statistics show that the travel of agricultural machinery to a work area and their movement during labour is the source of many serious accidents. The most dangerous in consequences prove to be those that occur during transport and associated with maneuvering tractors and machinery (about 30% of all fatal accidents. It can be assumed that at least some of these accidents were caused indirectly by the specific design features of agricultural machines which adversely affect the driveability. The single- and multi-loop structures of the driver-vehicle system models are formulated to study the contributions of various preview and prediction strategies to the path tracking and dynamic performance of the articulated vehicle. In the presented study the compensatory model of driver utilizes the lateral acceleration of the tractor, roll angle of trailer sprung mass and the articulation rate as the internal motion feedback variables. The control model of steering of an agricultural set has been implemented in the Matlab/Simulink environment. The model has been constructed with the use of stochastic methods and operational transmittances describing the various components of the system. The model operational transmittances has been estimated using Box-Jenkins and continuous-time process models from input-output data. The model has been tested using experimental data from road investigation of the agricultural set.

  12. Driver feedback mobile APP

    Energy Technology Data Exchange (ETDEWEB)

    Soriguera Marti, F.; Miralles Miquel, E.

    2016-07-01

    This paper faces the human factor in driving and its consequences for road safety. It presents the concepts behind the development of a smartphone app capable of evaluating drivers’ performance. The app provides feedback to the driver in terms of a grade (between 0 and 10) depending on the aggressiveness and risks taken while driving. These are computed from the cumulative probability distribution function of the jerks (i.e. the time derivative of acceleration), which are measured using the smartphones’ accelerometer. Different driving contexts (e.g. urban, freeway, congestion, etc.) are identified applying cluster analysis to the measurements, and treated independently. Using regression analysis, the aggressiveness indicator is related to the drivers' safety records and to the probability of having an accident, through the standard DBQ - Driving Behavior Questionnaire. Results from a very limited pilot test show a strong correlation between the 99th percentile of the jerk measurements and the DBQ results. A linear model is fitted. This allows quantifying the safe driving behavior only from smartphone measurements. Finally, this indicator is translated into a normalized grade and feedback to the driver. This feedback will challenge the driver to train and to improve his performance. The phone will be blocked while driving and will incorporate mechanisms to prevent bad practices, like competition in aggressive driving. The app is intended to contribute to the improvement of road safety, one of the major public health problems, by tackling the human factor which is the trigger of the vast majority of traffic accidents. Making explicit and quantifying risky behaviors is the first step towards a safer driving. (Author)

  13. Quantifying geographic variation in the climatic drivers of midcontinent wetlands with a spatially varying coefficient model.

    Science.gov (United States)

    Roy, Christian

    2015-01-01

    The wetlands in the Prairie Pothole Region and in the Great Plains are notorious for their sensitivity to weather variability. These wetlands have been the focus of considerable attention because of their ecological importance and because of the expected impact of climate change. Few models in the literature, however, take into account spatial variation in the importance of wetland drivers. This is surprising given the importance spatial heterogeneity in geomorphology and climatic conditions have in the region. In this paper, I use spatially-varying coefficients to assess the variation in ecological drivers in a number of ponds observed over a 50-year period (1961-2012). I included the number of ponds observed the year before on a log scale, the log of total precipitation, and mean maximum temperature during the four previous seasons as explanatory variables. I also included a temporal component to capture change in the number of ponds due to anthropogenic disturbance. Overall, fall and spring precipitation were most important in pond abundance in the west, whereas winter and summer precipitation were the most important drivers in the east. The ponds in the east of the survey area were also more dependent on pond abundance during the previous year than those in the west. Spring temperature during the previous season influenced pond abundance; while the temperature during the other seasons had a limited effect. The ponds in the southwestern part of the survey area have been increasing independently of climatic conditions, whereas the ponds in the northeast have been steadily declining. My results underline the importance of accounting the spatial heterogeneity in environmental drivers, when working at large spatial scales. In light of my results, I also argue that assessing the impacts of climate change on wetland abundance in the spring, without more accurate climatic forecasting, will be difficult.

  14. Quantifying geographic variation in the climatic drivers of midcontinent wetlands with a spatially varying coefficient model.

    Directory of Open Access Journals (Sweden)

    Christian Roy

    Full Text Available The wetlands in the Prairie Pothole Region and in the Great Plains are notorious for their sensitivity to weather variability. These wetlands have been the focus of considerable attention because of their ecological importance and because of the expected impact of climate change. Few models in the literature, however, take into account spatial variation in the importance of wetland drivers. This is surprising given the importance spatial heterogeneity in geomorphology and climatic conditions have in the region. In this paper, I use spatially-varying coefficients to assess the variation in ecological drivers in a number of ponds observed over a 50-year period (1961-2012. I included the number of ponds observed the year before on a log scale, the log of total precipitation, and mean maximum temperature during the four previous seasons as explanatory variables. I also included a temporal component to capture change in the number of ponds due to anthropogenic disturbance. Overall, fall and spring precipitation were most important in pond abundance in the west, whereas winter and summer precipitation were the most important drivers in the east. The ponds in the east of the survey area were also more dependent on pond abundance during the previous year than those in the west. Spring temperature during the previous season influenced pond abundance; while the temperature during the other seasons had a limited effect. The ponds in the southwestern part of the survey area have been increasing independently of climatic conditions, whereas the ponds in the northeast have been steadily declining. My results underline the importance of accounting the spatial heterogeneity in environmental drivers, when working at large spatial scales. In light of my results, I also argue that assessing the impacts of climate change on wetland abundance in the spring, without more accurate climatic forecasting, will be difficult.

  15. Evaluation of a Risk Awareness Perception Training Program on Novice Teen Driver Behavior at Left-Turn Intersections.

    Science.gov (United States)

    McDonald, Catherine C; Kandadai, Venk; Loeb, Helen; Seacrist, Thomas; Lee, Yi-Ching; Bonfiglio, Dana; Fisher, Donald L; Winston, Flaura K

    Collisions at left turn intersections are among the most prevalent types of teen driver serious crashes, with inadequate surveillance as a key factor. Risk awareness perception training (RAPT) has shown effectiveness in improving hazard anticipation for latent hazards. The goal of this study was to determine if RAPT version 3 (RAPT-3) improved intersection turning behaviors among novice teen drivers when the hazards were not latent and frequent glancing to multiple locations at the intersection was needed. Teens aged 16-18 with ≤180 days of licensure were randomly assigned to: 1) an intervention group (n=18) that received RAPT-3 (Trained); or 2) a control group (n=19) that received no training (Untrained). Both groups completed RAPT-3 Baseline Assessment and the Trained group completed RAPT-3 Training and RAPT-3 Post Assessment. Training effects were evaluated on a driving simulator. Simulator ( gap selection errors and collisions ) and eye tracker ( traffic check errors) metrics from six left-turn stop sign controlled intersections in the Simulated Driving Assessment (SDA) were analyzed. The Trained group scored significantly higher in RAPT-3 Post Assessment than RAPT-3 Baseline Assessment (psign controlled intersections where the hazards were not latent. Our findings point to further research to better understand the challenges teens have with left turn intersections.

  16. Drivers for liquidation and transfer in small firms : Theory of Planned Behavior and firm conditions

    NARCIS (Netherlands)

    H. Leory; Lex van Teeffelen

    2009-01-01

    Recently Leroy et al. (2008) tested if the Theory of Planned Behavior (TPB) predicts exit behavior of entrepreneurs: liquidation or transfer. He added the purchasers view to the TPB: firm viability and intangible assets. We retested Leroy et al. hypotheses on a more refined dataset of 136 firms in

  17. The effects of lane width, shoulder width, and road cross-sectional reallocation on drivers' behavioral adaptations.

    Science.gov (United States)

    Mecheri, Sami; Rosey, Florence; Lobjois, Régis

    2017-07-01

    Previous research has shown that lane-width reduction makes drivers operate vehicles closer to the center of the road whereas hard-shoulder widening induces a position farther away from the road's center. The goal of the present driving-simulator study was twofold. First, it was aimed at further investigating the respective effects of lane and shoulder width on in-lane positioning strategies, by examining vehicle distance from the center of the lane. The second aim was to assess the impact on safety of three possible cross-sectional reallocations of the width of the road (i.e., three lane-width reductions with concomitant shoulder widening at a fixed cross-sectional width) as compared to a control road. The results confirmed that lane-width reduction made participants drive closer to the road's center. However, in-lane position was affected differently by lane narrowing, depending on the traffic situation. In the absence of oncoming traffic, lane narrowing gave rise to significant shifts in the car's distance from the lane's center toward the edge line, whereas this distance remained similar across lane widths during traffic periods. When the shoulders were at least 0.50m wide, participants drove farther away from both the road center and the lane center. Road reallocation operations resulted in vehicles positioned farther away from the edge of the road and less swerving behavior, without generating higher driving speeds. Finally, it is argued that road-space reallocation may serve as a good low-cost tool for providing a recovery area for steering errors, without impairing drivers' behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Modeling and analyses for an extended car-following model accounting for drivers' situation awareness from cyber physical perspective

    Science.gov (United States)

    Chen, Dong; Sun, Dihua; Zhao, Min; Zhou, Tong; Cheng, Senlin

    2018-07-01

    In fact, driving process is a typical cyber physical process which couples tightly the cyber factor of traffic information with the physical components of the vehicles. Meanwhile, the drivers have situation awareness in driving process, which is not only ascribed to the current traffic states, but also extrapolates the changing trend. In this paper, an extended car-following model is proposed to account for drivers' situation awareness. The stability criterion of the proposed model is derived via linear stability analysis. The results show that the stable region of proposed model will be enlarged on the phase diagram compared with previous models. By employing the reductive perturbation method, the modified Korteweg de Vries (mKdV) equation is obtained. The kink-antikink soliton of mKdV equation reveals theoretically the evolution of traffic jams. Numerical simulations are conducted to verify the analytical results. Two typical traffic Scenarios are investigated. The simulation results demonstrate that drivers' situation awareness plays a key role in traffic flow oscillations and the congestion transition.

  19. The development of collective personality: the ontogenetic drivers of behavioral variation across groups

    Directory of Open Access Journals (Sweden)

    Sarah E Bengston

    2014-12-01

    Full Text Available For the past decade, the study of personality has become a topic on the frontier of behavioral ecology. However, most studies have focused on exploring inter-individual behavioral variation in solitary animals, and few account for the role that social interactions may have on the development of an individual’s personality. Moreover, a social group may exhibit collective personality: an emergent behavioral phenotype displayed at the group-level, which is not necessarily the sum or average of individual personalities within that group. The social environment, in many cases, can determine group success, which then influences the relative success of all the individuals in that group. In addition, group-level personality may itself evolve, subject to the same selection pressures as individual-level behavioral variation, when the group is a unit under selection. Therefore, we reason that understanding how collective personalities emerge and change over time will be imperative to understanding individual- and group-level behavioral evolution.Personality is considered to be fixed over an individual’s lifetime. However, behavior may shift throughout development, particularly during adolescence. Therefore, juvenile behavior should not be compared with adult behavior when assessing personality. Similarly, as conditions within a group and/or the local environment can shift, group behavior may similarly fluctuate as it matures. We discuss potential within-group factors, such as group initiation, group maturation, genetic make-up of the group, and the internal social environment, and external factors, such as well as how local environment may play a role in generating group-level personalities. There are a variety of studies that explore group development or quantify group personality, but few that integrate both processes. Therefore, we conclude by discussing potential ways to evaluate development of collective personality, and propose several focal

  20. Who is a dangerous driver? Socio-demographic and personal determinants of risky traffic behavior

    OpenAIRE

    Aleksandra Peplińska; Magdalena Wyszomirska-Góra; Piotr Połomski; Marcin Szulc

    2015-01-01

    Background The aim of this study was to search for comprehensive socio-demographic and personal (personality and temperamental) determinants of risky on-the-road behavior. Based on the results of previous studies, we assumed that the main predictors of dangerous traffic behavior include: internal locus of control, sensation seeking, risk seeking and risk acceptance, as well as high self-esteem, a low level of reactivity combined with a high level of endurance and activity (which together...

  1. Daytime behavior of Pteropus vampyrus in a natural habitat: the driver of viral transmission.

    Science.gov (United States)

    Hengjan, Yupadee; Pramono, Didik; Takemae, Hitoshi; Kobayashi, Ryosuke; Iida, Keisuke; Ando, Takeshi; Kasmono, Supratikno; Basri, Chaerul; Fitriana, Yuli Sulistya; Arifin, Eko M Z; Ohmori, Yasushige; Maeda, Ken; Agungpriyono, Srihadi; Hondo, Eiichi

    2017-06-29

    Flying foxes, the genus Pteropus, are considered viral reservoirs. Their colonial nature and long flight capability enhance their ability to spread viruses quickly. To understand how the viral transmission occurs between flying foxes and other animals, we investigated daytime behavior of the large flying fox (Pteropus vampyrus) in the Leuweung Sancang conservation area, Indonesia, by using instantaneous scan sampling and all-occurrence focal sampling. The data were obtained from 0700 to 1700 hr, during May 11-25, 2016. Almost half of the flying foxes (46.9 ± 10.6% of all recorded bats) were awake and showed various levels of activity during daytime. The potential behaviors driving disease transmission, such as self-grooming, mating/courtship and aggression, peaked in the early morning. Males were more active and spent more time on sexual activities than females. There was no significant difference in time spent for negative social behaviors between sexes. Positive social behaviors, especially maternal cares, were performed only by females. Sexual activities and negative/positive social behaviors enable fluid exchange between bats and thus facilitate intraspecies transmission. Conflicts for living space between the flying foxes and the ebony leaf monkey (Trachypithecus auratus) were observed, and this caused daily roosting shifts of flying foxes. The ecological interactions between bats and other wildlife increase the risk of interspecies infection. This study provides the details of the flying fox's behavior and its interaction with other wildlife in South-East Asia that may help explain how pathogen spillover occurs in the wild.

  2. An extended car-following model considering the appearing probability of truck and driver's characteristics

    Science.gov (United States)

    Rong, Ying; Wen, Huiying

    2018-05-01

    In this paper, the appearing probability of truck is introduced and an extended car-following model is presented to analyze the traffic flow based on the consideration of driver's characteristics, under honk environment. The stability condition of this proposed model is obtained through linear stability analysis. In order to study the evolution properties of traffic wave near the critical point, the mKdV equation is derived by the reductive perturbation method. The results show that the traffic flow will become more disorder for the larger appearing probability of truck. Besides, the appearance of leading truck affects not only the stability of traffic flow, but also the effect of other aspects on traffic flow, such as: driver's reaction and honk effect. The effects of them on traffic flow are closely correlated with the appearing probability of truck. Finally, the numerical simulations under the periodic boundary condition are carried out to verify the proposed model. And they are consistent with the theoretical findings.

  3. Modeling drivers of phosphorus loads in Chesapeake Bay tributaries and inferences about long-term change

    Science.gov (United States)

    Ryberg, Karen R.; Blomquist, Joel; Sprague, Lori A.; Sekellick, Andrew J.; Keisman, Jennifer

    2018-01-01

    Causal attribution of changes in water quality often consists of correlation, qualitative reasoning, listing references to the work of others, or speculation. To better support statements of attribution for water-quality trends, structural equation modeling was used to model the causal factors of total phosphorus loads in the Chesapeake Bay watershed. By transforming, scaling, and standardizing variables, grouping similar sites, grouping some causal factors into latent variable models, and using methods that correct for assumption violations, we developed a structural equation model to show how causal factors interact to produce total phosphorus loads. Climate (in the form of annual total precipitation and the Palmer Hydrologic Drought Index) and anthropogenic inputs are the major drivers of total phosphorus load in the Chesapeake Bay watershed. Increasing runoff due to natural climate variability is offsetting purposeful management actions that are otherwise decreasing phosphorus loading; consequently, management actions may need to be reexamined to achieve target reductions in the face of climate variability.

  4. Mathematical models of human behavior

    DEFF Research Database (Denmark)

    Møllgaard, Anders Edsberg

    at the Technical University of Denmark. The data set includes face-to-face interaction (Bluetooth), communication (calls and texts), mobility (GPS), social network (Facebook), and general background information including a psychological profile (questionnaire). This thesis presents my work on the Social Fabric...... data set, along with work on other behavioral data. The overall goal is to contribute to a quantitative understanding of human behavior using big data and mathematical models. Central to the thesis is the determination of the predictability of different human activities. Upper limits are derived....... Evidence is provided, which implies that the asymmetry is caused by a self-enhancement in the initiation dynamics. These results have implications for the formation of social networks and the dynamics of the links. It is shown that the Big Five Inventory (BFI) representing a psychological profile only...

  5. Modeling Human Steering Behavior During Path Following in Teleoperation of Unmanned Ground Vehicles.

    Science.gov (United States)

    Mirinejad, Hossein; Jayakumar, Paramsothy; Ersal, Tulga

    2018-04-01

    This paper presents a behavioral model representing the human steering performance in teleoperated unmanned ground vehicles (UGVs). Human steering performance in teleoperation is considerably different from the performance in regular onboard driving situations due to significant communication delays in teleoperation systems and limited information human teleoperators receive from the vehicle sensory system. Mathematical models capturing the teleoperation performance are a key to making the development and evaluation of teleoperated UGV technologies fully simulation based and thus more rapid and cost-effective. However, driver models developed for the typical onboard driving case do not readily address this need. To fill the gap, this paper adopts a cognitive model that was originally developed for a typical highway driving scenario and develops a tuning strategy that adjusts the model parameters in the absence of human data to reflect the effect of various latencies and UGV speeds on driver performance in a teleoperated path-following task. Based on data collected from a human subject test study, it is shown that the tuned model can predict both the trend of changes in driver performance for different driving conditions and the best steering performance of human subjects in all driving conditions considered. The proposed model with the tuning strategy has a satisfactory performance in predicting human steering behavior in the task of teleoperated path following of UGVs. The established model is a suited candidate to be used in place of human drivers for simulation-based studies of UGV mobility in teleoperation systems.

  6. The Relationship Between Duration of Postrotary Nystagmus and Driver Behavior: Learning Theory Module.

    Science.gov (United States)

    Geier, Suzanne Smith; Young, Barbara

    It was hypothesized that behavior patterns, learned early in life and maintained by almost continuous reinforcement, are determined by basic physiology, which in this study is represented by the duration of postrotary nystagmus (involuntary eyeball movement following rotational stimulation). The Southern California Postrotary Nystagmus Test was…

  7. Generalizations on consumer innovation adoption : A meta-analysis on drivers of intention and behavior

    NARCIS (Netherlands)

    Arts, Joep W. C.; Frambach, Ruud T.; Bijmolt, Tammo H. A.

    Previous research has shown that consumer intentions to adopt innovations are often poor predictors of adoption behavior. An important reason for this may be that the evaluative criteria consumers use in both stages of the adoption process weigh differently. Using construal level theory, we develop

  8. A new lattice model of traffic flow with the consideration of the driver's forecast effects

    Energy Technology Data Exchange (ETDEWEB)

    Peng, G.H., E-mail: pengguanghan@yahoo.com.cn [College of Physics and Electronic Science, Hunan University of Arts and Science, Changde 415000 (China); Cai, X.H.; Liu, C.Q.; Cao, B.F. [College of Physics and Electronic Science, Hunan University of Arts and Science, Changde 415000 (China)

    2011-05-30

    In this Letter, a new lattice model is presented with the consideration of the driver's forecast effects (DFE). The linear stability condition of the extended model is obtained by using the linear stability theory. The analytical results show that the new model can improve the stability of traffic flow by considering DFE. The modified KdV equation near the critical point is derived to describe the traffic jam by nonlinear analysis. Numerical simulation also shows that the new model can improve the stability of traffic flow by adjusting the driver's forecast intensity parameter, which is consistent with the theoretical analysis. -- Highlights: → A new driver's forecast lattice model of traffic flow has been presented. → The driver's forecast effects on the stability of traffic flow have been explored. → The modified KdV equation near the critical point is derived to describe the traffic jam by nonlinear analysis. → The analytical and numerical results show that the driver's forecast effect can improve the stability of traffic flow.

  9. Dealing with Drought: Decoupling Climatic and Management-Related Drivers of Water Conservation Behavior

    Science.gov (United States)

    Hemati, A.; Rippy, M.; Grant, S. B.

    2015-12-01

    As global populations grow, cities in drought prone regions of the world such as California and South East Australia are faced with escalating water scarcity and water security challenges. The management approaches geared towards addressing these challenges are diverse. Given the myriad of possible approaches and the tendency to apply them in combination, successful management actions can be difficult to identify. Background climactic variability further complicates the story, making transfer of management lessons from one drought stressed region to another difficult. Here we use Melbourne, a city of 4.3 million people in South East Australia that recently faced and overcame a > 10 year "Millennium" drought, as a test case for evaluating the relative importance of various management-related and climactic factors in driving reductions in municipal water consumption (~60% in 12 years). Our analysis suggests that Melbourne's declining municipal consumption cannot be explained by potable substitution alone, as reductions in municipal consumption were not matched by increased use of alternative sources (e.g., urban rain or recycled water). Thus, water conservation behavior (not source switching) may be responsible for the majority of demand reduction in Melbourne. Interestingly, while voluntary or mandatory water restrictions appear to have substantially altered the rate of change of consumption near the end of Melbourne's Millennium drought (e.g., forcing a period of intense conservation), overall conservation behavior precedes these restrictions. This suggests that other rapidly implemented (and hither too unquantified) management approaches such as advertising or newspapers may have driven water conservation behavior early in the drought. Climatic factors, particularly precipitation may also have influenced conservation behavior; changes in precipitation were significantly positively correlated with changes in water consumption at a lag of 18 months. Similar

  10. Daytime behavior of Pteropus vampyrus in a natural habitat: the driver of viral transmission

    OpenAIRE

    HENGJAN, Yupadee; PRAMONO, Didik; TAKEMAE, Hitoshi; KOBAYASHI, Ryosuke; IIDA, Keisuke; ANDO, Takeshi; KASMONO, Supratikno; BASRI, Chaerul; FITRIANA, Yuli Sulistya; ARIFIN, Eko M. Z.; OHMORI, Yasushige; MAEDA, Ken; AGUNGPRIYONO, Srihadi; HONDO, Eiichi

    2017-01-01

    Flying foxes, the genus Pteropus, are considered viral reservoirs. Their colonial nature and long flight capability enhance their ability to spread viruses quickly. To understand how the viral transmission occurs between flying foxes and other animals, we investigated daytime behavior of the large flying fox (Pteropus vampyrus) in the Leuweung Sancang conservation area, Indonesia, by using instantaneous scan sampling and all-occurrence focal sampling. The data were obtained from 0700 to 1700 ...

  11. Negativity Bias in Dangerous Drivers.

    Directory of Open Access Journals (Sweden)

    Jing Chai

    Full Text Available The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.

  12. Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control

    NARCIS (Netherlands)

    de Croon, E. M.; Blonk, R. W. B.; de Zwart, B. C. H.; Frings-Dresen, M. H. W.; Broersen, J. P. J.

    2002-01-01

    Objectives: Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers.

  13. Modeling lahar behavior and hazards

    Science.gov (United States)

    Manville, Vernon; Major, Jon J.; Fagents, Sarah A.

    2013-01-01

    Lahars are highly mobile mixtures of water and sediment of volcanic origin that are capable of traveling tens to > 100 km at speeds exceeding tens of km hr-1. Such flows are among the most serious ground-based hazards at many volcanoes because of their sudden onset, rapid advance rates, long runout distances, high energy, ability to transport large volumes of material, and tendency to flow along existing river channels where populations and infrastructure are commonly concentrated. They can grow in volume and peak discharge through erosion and incorporation of external sediment and/or water, inundate broad areas, and leave deposits many meters thick. Furthermore, lahars can recur for many years to decades after an initial volcanic eruption, as fresh pyroclastic material is eroded and redeposited during rainfall events, resulting in a spatially and temporally evolving hazard. Improving understanding of the behavior of these complex, gravitationally driven, multi-phase flows is key to mitigating the threat to communities at lahar-prone volcanoes. However, their complexity and evolving nature pose significant challenges to developing the models of flow behavior required for delineating their hazards and hazard zones.

  14. Optimization of a quarter-car suspension model coupled with the driver biomechanical effects

    Science.gov (United States)

    Kuznetsov, Alexey; Mammadov, Musa; Sultan, Ibrahim; Hajilarov, Eldar

    2011-06-01

    In this paper a Human-Vehicle-Road (HVR) model, comprising a quarter-car and a biomechanical representation of the driver, is employed for the analysis. Differential equations are provided to describe the motions of various masses under the influence of a harmonic road excitation. These equations are, subsequently, solved to obtain a closed form mathematical expression for the steady-state vertical acceleration measurable at the vehicle-human interface. The solution makes it possible to find optimal parameters for the vehicle suspension system with respect to a specified ride comfort level. The quantitative definition given in the ISO 2631 standard for the ride comfort level is adopted in this paper for the optimization procedure. Numerical examples, based on actually measured road profiles, are presented to prove the validity of the proposed approach and its suitability for the problem at hand.

  15. A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

    Science.gov (United States)

    Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

    2016-02-19

    In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

  16. Driver behavior analysis during ACC activation and deactivation in a real traffic environment

    NARCIS (Netherlands)

    Pauwelussen, J.; Feenstra, P.J.

    2010-01-01

    For the development of a traffic-simulation model to estimate the effect of adaptive cruise control (ACC) systems on traffic safety, throughput, and environment, data of a field operational test (FOT) were analyzed, in which vehicles were equipped with ACC and lane-departure warning (LDW) systems.

  17. Structural equation modeling of the proximal–distal continuum of adherence drivers

    Directory of Open Access Journals (Sweden)

    McHorney CA

    2012-11-01

    Full Text Available Colleen A McHorney,1 Ning Jackie Zhang,2 Timothy Stump,3 Xiaoquan Zhao41US Outcomes Research, Merck, North Wales, PA, 2University of Central Florida, Orlando, 3Indiana University School of Medicine, Indianapolis, 4George Mason University, Fairfax, USAObjectives: Nonadherence to prescription medications has been shown to be significantly influenced by three key medication-specific beliefs: patients' perceived need for the prescribed medication, their concerns about the prescribed medication, and perceived medication affordability. Structural equation modeling was used to test the predictors of these three proximal determinants of medication adherence using the proximal–distal continuum of adherence drivers as the organizing conceptual framework.Methods: In Spring 2008, survey participants were selected from the Harris Interactive Chronic Illness Panel, an internet-based panel of hundreds of thousands of adults with chronic disease. Respondents were eligible for the survey if they were aged 40 years and older, resided in the US, and reported having at least one of six chronic diseases: asthma, diabetes, hyperlipidemia, hypertension, osteoporosis, or other cardiovascular disease. A final sample size of 1072 was achieved. The proximal medication beliefs were measured by three multi-item scales: perceived need for medications, perceived medication concerns, and perceived medication affordability. The intermediate sociomedical beliefs and skills included four multi-item scales: perceived disease severity, knowledge about the prescribed medication, perceived immunity to side effects, and perceived value of nutraceuticals. Generic health beliefs and skills consisted of patient engagement in their care, health information-seeking tendencies, internal health locus of control, a single-item measure of self-rated health, and general mental health. Structural equation modeling was used to model proximal–distal continuum of adherence drivers.Results: The

  18. Examining the nonparametric effect of drivers' age in rear-end accidents through an additive logistic regression model.

    Science.gov (United States)

    Ma, Lu; Yan, Xuedong

    2014-06-01

    This study seeks to inspect the nonparametric characteristics connecting the age of the driver to the relative risk of being an at-fault vehicle, in order to discover a more precise and smooth pattern of age impact, which has commonly been neglected in past studies. Records of drivers in two-vehicle rear-end collisions are selected from the general estimates system (GES) 2011 dataset. These extracted observations in fact constitute inherently matched driver pairs under certain matching variables including weather conditions, pavement conditions and road geometry design characteristics that are shared by pairs of drivers in rear-end accidents. The introduced data structure is able to guarantee that the variance of the response variable will not depend on the matching variables and hence provides a high power of statistical modeling. The estimation results exhibit a smooth cubic spline function for examining the nonlinear relationship between the age of the driver and the log odds of being at fault in a rear-end accident. The results are presented with respect to the main effect of age, the interaction effect between age and sex, and the effects of age under different scenarios of pre-crash actions by the leading vehicle. Compared to the conventional specification in which age is categorized into several predefined groups, the proposed method is more flexible and able to produce quantitatively explicit results. First, it confirms the U-shaped pattern of the age effect, and further shows that the risks of young and old drivers change rapidly with age. Second, the interaction effects between age and sex show that female and male drivers behave differently in rear-end accidents. Third, it is found that the pattern of age impact varies according to the type of pre-crash actions exhibited by the leading vehicle. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Circuit models and three-dimensional electromagnetic simulations of a 1-MA linear transformer driver stage

    Directory of Open Access Journals (Sweden)

    D. V. Rose

    2010-09-01

    Full Text Available A 3D fully electromagnetic (EM model of the principal pulsed-power components of a high-current linear transformer driver (LTD has been developed. LTD systems are a relatively new modular and compact pulsed-power technology based on high-energy density capacitors and low-inductance switches located within a linear-induction cavity. We model 1-MA, 100-kV, 100-ns rise-time LTD cavities [A. A. Kim et al., Phys. Rev. ST Accel. Beams 12, 050402 (2009PRABFM1098-440210.1103/PhysRevSTAB.12.050402] which can be used to drive z-pinch and material dynamics experiments. The model simulates the generation and propagation of electromagnetic power from individual capacitors and triggered gas switches to a radially symmetric output line. Multiple cavities, combined to provide voltage addition, drive a water-filled coaxial transmission line. A 3D fully EM model of a single 1-MA 100-kV LTD cavity driving a simple resistive load is presented and compared to electrical measurements. A new model of the current loss through the ferromagnetic cores is developed for use both in circuit representations of an LTD cavity and in the 3D EM simulations. Good agreement between the measured core current, a simple circuit model, and the 3D simulation model is obtained. A 3D EM model of an idealized ten-cavity LTD accelerator is also developed. The model results demonstrate efficient voltage addition when driving a matched impedance load, in good agreement with an idealized circuit model.

  20. Model based optimization of driver-pickup separation for eddy current measurement of gap

    Science.gov (United States)

    Klein, G.; Morelli, J.; Krause, T. W.

    2018-04-01

    The fuel channels in CANDU® (CANada Deuterium Uranium) nuclear reactors consist of a pressure tube (PT) contained within a larger diameter calandria tube (CT). The separation between the tubes, known as the PT-CT gap, ensures PT hydride blisters, which could lead to potential cracking of the PT, do not develop. Therefore, accurate measurements are required to confirm that contact between PT and CT is not imminent. Gap measurement uses an eddy current probe. However this probe is sensitive to lift-off variations, which can adversely affect estimated gap. A validated analytical flat plate model of eddy current response to gap was used to examine the effect of driver-pickup spacing on lift-off and response to gap at a frequency of 4 kHz, which is used for in-reactor measurements. This model was compared against, and shown to have good agreement with, a COMSOL® finite element method (FEM) model. The optimum coil separation, which included the constraint of coil size, was found to be 11 mm, resulting in a phase response between lift-off and response to change in gap of 66°. This work demonstrates the advantages of using analytical models for optimizing coil designs for measurement of parameters that may negatively influence the outcome of an inspection measurement.

  1. Examination of a dual-process model predicting riding with drinking drivers.

    Science.gov (United States)

    Hultgren, Brittney A; Scaglione, Nichole M; Cleveland, Michael J; Turrisi, Rob

    2015-06-01

    Nearly 1 in 5 of the fatalities in alcohol-related crashes are passengers. Few studies have utilized theory to examine modifiable psychosocial predictors of individuals' tendencies to be a passenger in a vehicle operated by a driver who has consumed alcohol. This study used a prospective design to test a dual-process model featuring reasoned and reactive psychological influences and psychosocial constructs as predictors of riding with drinking drivers (RWDD) in a sample of individuals aged 18 to 21. College students (N = 508) completed web-based questionnaires assessing RWDD, psychosocial constructs (attitudes, expectancies, and norms), and reasoned and reactive influences (intentions and willingness) at baseline (the middle of the spring semester) and again 1 and 6 months later. Regression was used to analyze reasoned and reactive influences as proximal predictors of RWDD at the 6-month follow-up. Subsequent analyses examined the relationship between the psychosocial constructs as distal predictors of RWDD and the mediation effects of reasoned and reactive influences. Both reasoned and reactive influences predicted RWDD, while only the reactive influence had a significant unique effect. Reactive influences significantly mediated the effects of peer norms, attitudes, and drinking influences on RWDD. Nearly all effects were constant across gender except parental norms (significant for females). Findings highlight that the important precursors of RWDD were reactive influences, attitudes, and peer and parent norms. These findings suggest several intervention methods, specifically normative feedback interventions, parent-based interventions, and brief motivational interviewing, may be particularly beneficial in reducing RWDD. Copyright © 2015 by the Research Society on Alcoholism.

  2. Modeling the dynamics of driver's dilemma zone perception using machine learning methods for safer intersection control.

    Science.gov (United States)

    2014-04-01

    The "dilemma zone" (DZ) is defined as the area where drivers approaching a signalized intersection must decide to either proceed or stop at the onset of the yellow indication. Drivers that might perceive themselves to be too close to an intersection ...

  3. DRIVER INATTENTION

    Directory of Open Access Journals (Sweden)

    Richard TAY

    2004-01-01

    Full Text Available Driver inattention, especially driver distraction, is an extremely influential but generally neglected contributing factor of road crashes. This paper explores some of the common behaviours associated with several common forms of driver inattention, with respect to their perceived crash risks, rates of self-reported behaviours and whether drivers regulate such behaviours depending on the road and traffic environment, and provides some policy recommendations to address issues raised.

  4. Evaluation of ADAS with a supported-driver model for desired allocation of tasks between human and technology performance

    NARCIS (Netherlands)

    van den Beukel, Arie Paul; van der Voort, Mascha C.; Meyer, G.; Valldorf, J.

    2009-01-01

    Partly automated driving is relevant for solving mobility problems, but also causes concerns with respect to the driver‟s reliability in task performance. The supported driver model presented in this paper is therefore intended to answer the question, what type of support and in which circumstances,

  5. Hand-held cell phone use while driving legislation and observed driver behavior among population sub-groups in the United States

    OpenAIRE

    Rudisill, Toni M.; Zhu, Motao

    2017-01-01

    Abstract Background Cell phone use behaviors are known to vary across demographic sub-groups and geographic locations. This study examined whether universal hand-held calling while driving bans were associated with lower road-side observed hand-held cell phone conversations across drivers of different ages (16–24, 25–59, ≥60 years), sexes, races (White, African American, or other), ruralities (suburban, rural, or urban), and regions (Northeast, Midwest, South, and West). Methods Data from the...

  6. Breaking out of the economic box: energy efficiency, social rationality and non-economic drivers of behavioral change

    Energy Technology Data Exchange (ETDEWEB)

    Ehrhardt-Martinez, Karen; Laitner, John A. ' Skip' (ACEEE, American Council for an Energy-Efficient Economy, Washington, D.C. (United States))

    2009-07-01

    Energy concerns are increasingly on people's minds. According to a recent Gallup poll, nearly 30 percent of American's reported that energy prices were the most important financial problem facing their families today. But are these new concerns likely to translate into long-term behavioral changes and more energy-efficient behavior? Research suggests that it will take more than high prices to achieve maximum energy savings. People may like to think of themselves as rational economic actors, but a variety of studies by social-psychologists and behavioral economists reveal that people often act in ways that may be better described as 'socially-rational' and 'predictably irrational'. Despite these findings, many residential energy programs and most policy assessments continue to model potential energy savings as a function of existing technologies and the cost of those energy resources. This paper explores the ways in which individual behavior is shaped by the social context within which people operate and presents an alternative framework for modeling efficiency behavior. The alternative model recognizes that while individuals may not always behave in economically-rational ways, their behavior may be entirely rational from other vantage points. In fact, individuals often behave as rational social actors, determining what is and isn't 'appropriate' behavior by gleaning information from their own observations, from their peers, and from interactions within their sphere of social influence. As such, this paper explores the ways in which social rules, resources and context shape individual patterns of energy consumption. This alternative approach has important implications for program designs and policy recommendations.

  7. An evolutionary behavioral model for decision making

    OpenAIRE

    Romero Lopez, Dr Oscar Javier

    2011-01-01

    For autonomous agents the problem of deciding what to do next becomes increasingly complex when acting in unpredictable and dynamic environments pursuing multiple and possibly conflicting goals. One of the most relevant behavior-based model that tries to deal with this problem is the one proposed by Maes, the Bbehavior Network model. This model proposes a set of behaviors as purposive perception-action units which are linked in a nonhierarchical network, and whose behavior selection process i...

  8. Sexual behaviors and partner-specific correlates of heterosexual anal intercourse among truck drivers and their wives in South India.

    Science.gov (United States)

    Bhatnagar, Tarun; Sakthivel Saravanamurthy, P; Detels, Roger

    2015-02-01

    It is important to know about patterns of sexual behaviors among married couples in order to develop effective HIV prevention strategies for them. Herein we describe the sexual behaviors, estimate prevalence of anal intercourse (AI) among truck drivers ("truckers") and their wives, and determine partner-specific demographic and behavioral correlates of AI. We carried out a cluster-sampled cross-sectional survey among 18-49 year-old wives and their trucker husbands in a south Indian district. Data were collected by same-gender research team members with color-coded computer-assisted interviews. We used random intercept logistic regression to identify the independent correlates of AI. Thirteen percent of 475 wives and 467 truckers reported ever having AI with their spouse. Of those who responded, 55 % of 40 wives and 47 % of 36 truckers never used condoms during AI. Of those who responded, 22 of 32 wives and 24 of 32 husbands felt that condoms were unnecessary during AI. Reporting ever having AI was associated with younger age and higher education of both husband and wife. AI reported by wives was associated with having sexual partner(s) other than husband (adjusted OR 8.8 [95 % CI 3.2-24.0]), correctly answering all HIV knowledge items (adjusted OR 4.9 [95 % CI 1.9-12.5]), husband's sexual debut occurring before marriage (adjusted OR 1.9 [95 % CI 1.0-3.5]), and husband's high HIV risk perception (adjusted OR 2.5 [95 % CI 1.2-5.4]). AI reported by truckers was associated with having sex with a male or transgender (adjusted OR 4.0 [95 % CI 1.2-13.3]). Reported prevalence of AI was high considering that in India anal sex is non-normative, heavily stigmatized and, criminal. Indian heterosexual mobile populations need to be informed about the greater risk of HIV infection consequent to unprotected AI.

  9. Model for absorption-modified multiplication effects in the assay of HEU-containing powders in a random driver

    International Nuclear Information System (INIS)

    Winslow, G.H.

    1981-01-01

    A model has been developed which describes the enhancement of the response, in a random driver, of a ''stack'' of highly enriched uranium of arbitrary height over the integral of the response of infinitessimal layers that would be produced solely by the interrogating sources which are external to the stack. It has been suggested that this method of modeling should also be applicable to powders. This paper is a report on the form the model takes for that application. 4 refs

  10. Research Models in Developmental Behavioral Toxicology.

    Science.gov (United States)

    Dietrich, Kim N.; Pearson, Douglas T.

    Developmental models currently used by child behavioral toxicologists and teratologists are inadequate to address current issues in these fields. Both child behavioral teratology and toxicology scientifically study the impact of exposure to toxic agents on behavior development: teratology focuses on prenatal exposure and postnatal behavior…

  11. Driving Simulator Based Interactive Experiments : Understanding Driver Behavior, Cognition and Technology Uptake under Information and Communication Technologies

    Science.gov (United States)

    2018-01-31

    Advanced Traveler Information Systems (ATIS) and in-vehicle information systems (IVIS) are becoming an integral part of the current driving experience. Although information through in-vehicle technologies provides assistance to drivers with diverse t...

  12. Evapotranspiration from drained wetlands with different hydrologic regimes: Drivers, modeling, and storage functions

    Science.gov (United States)

    Wu, Chin-Lung; Shukla, Sanjay; Shrestha, Niroj K.

    2016-07-01

    We tested whether the current understanding of insignificant effect of drainage on evapotranspiration (ET) in the temperate region wetlands applies to those in the subtropics. Hydro-climatic drivers causing the changes in drained wetlands were identified and used to develop a generic model to predict wetland ET. Eddy covariance (EC)-based ET measurements were made for two years at two differently drained but close by wetlands, a heavily drained wetland (SW) (97% reduced surface storage) and a more functional wetland (DW) (42% reduced storage). Annual ET for more intensively drained SW was 836 mm, 34% less than DW (1271 mm) and the difference was significant (p = 0.001). This difference was mainly due to drainage driven differences in inundation and associated effects on net radiation (Rn) and local relative humidity. Two generic daily ET models, a regression model (MSE = 0.44 mm2, R2 = 0.80) and a machine learning-based Relevance Vector Machine (RVM) model (MSE = 0.36 mm2, R2 = 0.84), were developed with the latter being more robust. The RVM model can predict changes in ET for different restoration scenarios; a 1.1 m rise in drainage level showed 7% increase ET (18 mm) at SW while the increase at DW was negligible. The additional ET, 28% of surface flow, can enhance water storage, flood protection, and climate mitigation services at SW compared to DW. More intensely drained wetlands at higher elevation should be targeted for restoration for enhanced storage through increased ET. The models developed can predict changes in ET for improved evaluation of basin-scale effects of restoration programs and climate change scenarios.

  13. Modeling the safety impacts of driving hours and rest breaks on truck drivers considering time-dependent covariates.

    Science.gov (United States)

    Chen, Chen; Xie, Yuanchang

    2014-12-01

    Driving hours and rest breaks are closely related to driver fatigue, which is a major contributor to truck crashes. This study investigates the effects of driving hours and rest breaks on commercial truck driver safety. A discrete-time logistic regression model is used to evaluate the crash odds ratios of driving hours and rest breaks. Driving time is divided into 11 one hour intervals. These intervals and rest breaks are modeled as dummy variables. In addition, a Cox proportional hazards regression model with time-dependent covariates is used to assess the transient effects of rest breaks, which consists of a fixed effect and a variable effect. Data collected from two national truckload carriers in 2009 and 2010 are used. The discrete-time logistic regression result indicates that only the crash odds ratio of the 11th driving hour is statistically significant. Taking one, two, and three rest breaks can reduce drivers' crash odds by 68%, 83%, and 85%, respectively, compared to drivers who did not take any rest breaks. The Cox regression result shows clear transient effects for rest breaks. It also suggests that drivers may need some time to adjust themselves to normal driving tasks after a rest break. Overall, the third rest break's safety benefit is very limited based on the results of both models. The findings of this research can help policy makers better understand the impact of driving time and rest breaks and develop more effective rules to improve commercial truck safety. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

  14. Converter-level FEM simulation for lifetime prediction of an LED driver with improved thermal modelling

    DEFF Research Database (Denmark)

    Niu, H.; Wang, H.; Ye, X.

    2017-01-01

    application. A converter-level finite element simulation (FEM) simulation is carried out to obtain the ambient temperature of electrolytic capacitors and power MOSFETs used in the LED driver, which takes into account the impact of the driver enclosure and the thermal coupling among different components....... Therefore, the proposed method bridges the link between the global ambient temperature profile outside of the enclosure and the local ambient temperature profiles of the components of interest inside the driver. A quantitative comparison of the estimated annual lifetime consumptions of MOSFETs...

  15. The Train Driver Recovery Problem - a Set Partitioning Based Model and Solution Method

    DEFF Research Database (Denmark)

    Rezanova, Natalia Jurjevna; Ryan, David

    The need to recover a train driver schedule occurs during major disruptions in the daily railway operations. Using data from the train driver schedule of the Danish passenger railway operator DSB S-tog A/S, a solution method to the Train Driver Recovery Problem (TDRP) is developed. The TDRP...... the depth-first search of the Branch & Bound tree. Preliminarily results are encouraging, showing that nearly all tested real-life instances produce integer solutions to the LP relaxation and solutions are found within a few seconds....

  16. Modeling Architectural Patterns’ Behavior Using Architectural Primitives

    NARCIS (Netherlands)

    Waqas Kamal, Ahmad; Avgeriou, Paris

    2008-01-01

    Architectural patterns have an impact on both the structure and the behavior of a system at the architecture design level. However, it is challenging to model patterns’ behavior in a systematic way because modeling languages do not provide the appropriate abstractions and because each pattern

  17. Modeling Driving Behavior at Roundabouts: Impact of Roundabout Layout and Surrounding Traffic on Driving Behavior

    OpenAIRE

    Zhao, Min; Käthner, David; Söffker, Dirk; Jipp, Meike; Lemmer, Karsten

    2017-01-01

    Driving behavior prediction at roundabouts is an important challenge to improve driving safety by supporting drivers with intelligent assistance systems. To predict the driving behavior effciently steering wheel status was proven to have robust predictability based on a Support Vector Machine algorithm. Previous research has not considered potential effects of roundabout layout and surrounding traffic on driving behavior, but that consideration can certainly improve the prediction results....

  18. Associating crash avoidance maneuvers with driver attributes and accident characteristics: a mixed logit model approach

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. Methods: The analysis is conducted by means of a mixed...... about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing a forgiving infrastructure within a sustainable safety systems......Objective: The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives...

  19. Cross-species genomics matches driver mutations and cell compartments to model ependymoma

    Science.gov (United States)

    Johnson, Robert A.; Wright, Karen D.; Poppleton, Helen; Mohankumar, Kumarasamypet M.; Finkelstein, David; Pounds, Stanley B.; Rand, Vikki; Leary, Sarah E.S.; White, Elsie; Eden, Christopher; Hogg, Twala; Northcott, Paul; Mack, Stephen; Neale, Geoffrey; Wang, Yong-Dong; Coyle, Beth; Atkinson, Jennifer; DeWire, Mariko; Kranenburg, Tanya A.; Gillespie, Yancey; Allen, Jeffrey C.; Merchant, Thomas; Boop, Fredrick A.; Sanford, Robert. A.; Gajjar, Amar; Ellison, David W.; Taylor, Michael D.; Grundy, Richard G.; Gilbertson, Richard J.

    2010-01-01

    Understanding the biology that underlies histologically similar but molecularly distinct subgroups of cancer has proven difficult since their defining genetic alterations are often numerous, and the cellular origins of most cancers remain unknown1–3. We sought to decipher this heterogeneity by integrating matched genetic alterations and candidate cells of origin to generate accurate disease models. First, we identified subgroups of human ependymoma, a form of neural tumor that arises throughout the central nervous system (CNS). Subgroup specific alterations included amplifications and homozygous deletions of genes not yet implicated in ependymoma. To select cellular compartments most likely to give rise to subgroups of ependymoma, we matched the transcriptomes of human tumors to those of mouse neural stem cells (NSCs), isolated from different regions of the CNS at different developmental stages, with an intact or deleted Ink4a/Arf locus. The transcriptome of human cerebral ependymomas with amplified EPHB2 and deleted INK4A/ARF matched only that of embryonic cerebral Ink4a/Arf−/− NSCs. Remarkably, activation of Ephb2 signaling in these, but not other NSCs, generated the first mouse model of ependymoma, which is highly penetrant and accurately models the histology and transcriptome of one subgroup of human cerebral tumor. Further comparative analysis of matched mouse and human tumors revealed selective deregulation in the expression and copy number of genes that control synaptogenesis, pinpointing disruption of this pathway as a critical event in the production of this ependymoma subgroup. Our data demonstrate the power of cross-species genomics to meticulously match subgroup specific driver mutations with cellular compartments to model and interrogate cancer subgroups. PMID:20639864

  20. Model for behavior observation training programs

    International Nuclear Information System (INIS)

    Berghausen, P.E. Jr.

    1987-01-01

    Continued behavior observation is mandated by ANSI/ANS 3.3. This paper presents a model for behavior observation training that is in accordance with this standard and the recommendations contained in US NRC publications. The model includes seventeen major topics or activities. Ten of these are discussed: Pretesting of supervisor's knowledge of behavior observation requirements, explanation of the goals of behavior observation programs, why behavior observation training programs are needed (legal and psychological issues), early indicators of emotional instability, use of videotaped interviews to demonstrate significant psychopathology, practice recording behaviors, what to do when unusual behaviors are observed, supervisor rationalizations for noncompliance, when to be especially vigilant, and prevention of emotional instability

  1. Modelling management process of key drivers for economic sustainability in the modern conditions of economic development

    Directory of Open Access Journals (Sweden)

    Pishchulina E.S.

    2017-01-01

    Full Text Available The text is about issues concerning the management of driver for manufacturing enterprise economic sustainability and manufacturing enterprise sustainability assessment as the key aspect of the management of enterprise economic sustainability. The given issues become topical as new requirements for the methods of manufacturing enterprise management in the modern conditions of market economy occur. An economic sustainability model that is considered in the article is an integration of enterprise economic growth, economic balance of external and internal environment and economic sustainability. The method of assessment of economic sustainability of a manufacturing enterprise proposed in the study allows to reveal some weaknesses in the enterprise performance, and untapped reserves, which can be further used to improve the economic sustainability and efficiency of the enterprise. The management of manufacturing enterprise economic sustainability is one of the most important factors of business functioning and development in modern market economy. The relevance of this trend is increasing in accordance with the objective requirements of the growing volumes of production and sale, the increasing complexity of economic relations, changing external environment of an enterprise.

  2. Understanding the role of the OneLove campaign in facilitating drivers of social and behavioral change in southern Africa: a qualitative evaluation.

    Science.gov (United States)

    Jana, Michael; Letsela, Lebohang; Scheepers, Esca; Weiner, Renay

    2015-01-01

    In the wake of the HIV and AIDS pandemic, health communication has played an important role in social and behavior change in HIV prevention and treatment efforts. Despite this significant role, it is not always clear how health communication influences individuals and communities to facilitate social and behavior change. Guided predominantly by Lewin's theory of change in the context of complexity thinking, and supported by qualitative evidence from Soul City Institute's midterm evaluation of the OneLove multimedia campaign in 9 southern African countries, this article illustrates how carefully designed health edutainment communication materials facilitate drivers of social and behavior change. Thus, researched and theory-based health communication aimed at behavior and social change remains an important pillar in HIV prevention and treatment, where personal and social agency remain key.

  3. Heavy-ion driver design and scaling

    International Nuclear Information System (INIS)

    Bieri, R.; Monsler, M.; Meier, W.; Stewart, L.

    1992-01-01

    Parametric models for scaling heavy-ion driver designs are described. Scaling of target performance and driver cost is done for driver parameters including driver energy, number of beams, type of superconductor used in focusing magnets, maximum magnetic field allowed at the superconducting windings, linear quadrupole array packing fraction mass, and ion charge state. The cumulative accelerator voltage and beam currents are determined from the Maschke limits on beam current for each choice of driver energy and post-acceleration pulse duration. The heavy-ion driver is optimized over the large available driver parameter space. Parametric studies and the choice of a base driver model are described in a companion paper

  4. A new conceptual model of coral biomineralisation: hypoxia as the physiological driver of skeletal extension

    Science.gov (United States)

    Wooldridge, S.

    2013-05-01

    That corals skeletons are built of aragonite crystals with taxonomy-linked ultrastructure has been well understood since the 19th century. Yet, the way by which corals control this crystallization process remains an unsolved question. Here, I outline a new conceptual model of coral biomineralisation that endeavours to relate known skeletal features with homeostatic functions beyond traditional growth (structural) determinants. In particular, I propose that the dominant physiological driver of skeletal extension is night-time hypoxia, which is exacerbated by the respiratory oxygen demands of the coral's algal symbionts (= zooxanthellae). The model thus provides a new narrative to explain the high growth rate of symbiotic corals, by equating skeletal deposition with the "work-rate" of the coral host needed to maintain a stable and beneficial symbiosis. In this way, coral skeletons are interpreted as a continuous (long-run) recording unit of the stability and functioning of the coral-algae endosymbiosis. After providing supportive evidence for the model across multiple scales of observation, I use coral core data from the Great Barrier Reef (Australia) to highlight the disturbed nature of the symbiosis in recent decades, but suggest that its onset is consistent with a trajectory that has been followed since at least the start of the 1900s. In concluding, I outline how the proposed capacity of cnidarians (which includes modern reef corals) to overcome the metabolic limitation of hypoxia via skeletogenesis also provides a new hypothesis to explain the sudden appearance in the fossil record of calcified skeletons at the Precambrian-Cambrian transition - and the ensuing rapid appearance of most major animal phyla.

  5. A new conceptual model of coral biomineralisation: hypoxia as the physiological driver of skeletal extension

    Directory of Open Access Journals (Sweden)

    S. Wooldridge

    2013-05-01

    Full Text Available That corals skeletons are built of aragonite crystals with taxonomy-linked ultrastructure has been well understood since the 19th century. Yet, the way by which corals control this crystallization process remains an unsolved question. Here, I outline a new conceptual model of coral biomineralisation that endeavours to relate known skeletal features with homeostatic functions beyond traditional growth (structural determinants. In particular, I propose that the dominant physiological driver of skeletal extension is night-time hypoxia, which is exacerbated by the respiratory oxygen demands of the coral's algal symbionts (= zooxanthellae. The model thus provides a new narrative to explain the high growth rate of symbiotic corals, by equating skeletal deposition with the "work-rate" of the coral host needed to maintain a stable and beneficial symbiosis. In this way, coral skeletons are interpreted as a continuous (long-run recording unit of the stability and functioning of the coral–algae endosymbiosis. After providing supportive evidence for the model across multiple scales of observation, I use coral core data from the Great Barrier Reef (Australia to highlight the disturbed nature of the symbiosis in recent decades, but suggest that its onset is consistent with a trajectory that has been followed since at least the start of the 1900s. In concluding, I outline how the proposed capacity of cnidarians (which includes modern reef corals to overcome the metabolic limitation of hypoxia via skeletogenesis also provides a new hypothesis to explain the sudden appearance in the fossil record of calcified skeletons at the Precambrian–Cambrian transition – and the ensuing rapid appearance of most major animal phyla.

  6. Multiaxial behavior of foams - Experiments and modeling

    Science.gov (United States)

    Maheo, Laurent; Guérard, Sandra; Rio, Gérard; Donnard, Adrien; Viot, Philippe

    2015-09-01

    Cellular materials are strongly related to pressure level inside the material. It is therefore important to use experiments which can highlight (i) the pressure-volume behavior, (ii) the shear-shape behavior for different pressure level. Authors propose to use hydrostatic compressive, shear and combined pressure-shear tests to determine cellular materials behavior. Finite Element Modeling must take into account these behavior specificities. Authors chose to use a behavior law with a Hyperelastic, a Viscous and a Hysteretic contributions. Specific developments has been performed on the Hyperelastic one by separating the spherical and the deviatoric part to take into account volume change and shape change characteristics of cellular materials.

  7. Prediction of safe driving Behaviours based on health belief model: the case of taxi drivers in Bandar Abbas, Iran.

    Science.gov (United States)

    Razmara, Asghar; Aghamolaei, Teamur; Madani, Abdoulhossain; Hosseini, Zahra; Zare, Shahram

    2018-03-20

    Road accidents are among the main causes of mortality. As safe and secure driving is a key strategy to reduce car injuries and offenses, the present research aimed to explore safe driving behaviours among taxi drivers based on the Health Belief Model (HBM). This study was conducted on 184 taxi drivers in Bandar Abbas who were selected based on a multiple stratified sampling method. Data were collected by a questionnaire comprised of a demographic information section along with the constructs of the HBM. Data were analysed by SPSS ver19 via a Pearson's correlation coefficient and multiple regressions. The mean age of the participants was 45.1 years (SD = 11.1). They all had, on average, 10.3 (SD = 7/5) years of taxi driving experience. Among the HBM components, cues to action and perceived benefits were shown to be positively correlated with safe driving behaviours, while perceived barriers were negatively correlated. Cues to action, perceived barriers and perceived benefits were shown to be the strongest predictors of a safe drivers' behaviour. Based on the results of this study in designing health promotion programmes to improve safe driving behaviours among taxi drivers, cues to action, perceived benefits and perceived barriers are important. Therefore, advertising, the design of information campaigns, emphasis on the benefits of safe driving behaviours and modification barriers are recommended.

  8. A Study of Bending Mode Algorithm of Adaptive Front-Lighting System Based on Driver Preview Behavior

    Directory of Open Access Journals (Sweden)

    Zhenhai Gao

    2014-01-01

    Full Text Available The function of adaptive front-lighting system is to improve the lighting condition of the road ahead and driving safety at night. The current system seldom considers characteristics of the driver’s preview behavior and eye movement. To solve this problem, an AFS algorithm modeling a driver’s preview behavior was proposed. According to the vehicle’s state, the driver’s manipulating input, and the vehicle’s future state change which resulted from the driver’s input, a dynamic predictive algorithm of the vehicle’s future track was established based on an optimal preview acceleration model. Then, an experiment on the change rule of the driver’s preview distance with different speeds and different road curvatures was implemented with the eye tracker and the calibration method of the driver’s preview time was established. On the basis of these above theories and experiments, the preview time was introduced to help predict the vehicle’s future track and an AFS algorithm modeling the driver’s preview behavior was built. Finally, a simulation analysis of the AFS algorithm was carried out. By analyzing the change process of the headlamp’s lighting region while bend turning which was controlled by the algorithm, its control effect was verified to be precise.

  9. Unification and mechanistic detail as drivers of model construction: models of networks in economics and sociology.

    Science.gov (United States)

    Kuorikoski, Jaakko; Marchionni, Caterina

    2014-12-01

    We examine the diversity of strategies of modelling networks in (micro) economics and (analytical) sociology. Field-specific conceptions of what explaining (with) networks amounts to or systematic preference for certain kinds of explanatory factors are not sufficient to account for differences in modelling methodologies. We argue that network models in both sociology and economics are abstract models of network mechanisms and that differences in their modelling strategies derive to a large extent from field-specific conceptions of the way in which a good model should be a general one. Whereas the economics models aim at unification, the sociological models aim at a set of mechanism schemas that are extrapolatable to the extent that the underlying psychological mechanisms are general. These conceptions of generality induce specific biases in mechanistic explanation and are related to different views of when knowledge from different fields should be seen as relevant.

  10. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    Science.gov (United States)

    Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

    2017-09-01

    Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

  11. Biosocial Models of Deviant Behavior.

    Science.gov (United States)

    Rowe, David C.

    1995-01-01

    Describes biological influences on criminality. Illustrative data suggest a biological sex difference in criminality and heritable differences in this trait among individuals. Methods of isolating environmental influences are described. Author notes that using environment-friendly behavior genetic research designs is not only proper but would…

  12. Seemingly irrational driving behavior model: The effect of habit strength and anticipated affective reactions.

    Science.gov (United States)

    Chung, Yi-Shih

    2015-09-01

    An increasing amount of evidence suggests that aberrant driving behaviors are not entirely rational. On the basis of the dual-process theory, this study postulates that drivers may learn to perform irrational aberrant driving behaviors, and these behaviors could be derived either from a deliberate or an intuitive decision-making approach. Accordingly, a seemingly irrational driving behavior model is proposed; in this model, the theory of planned behavior (TPB) was adopted to represent the deliberate decision-making mechanism, and habit strength was incorporated to reflect the intuitive decision process. A multiple trivariate mediation structure was designed to reflect the process through which driving behaviors are learned. Anticipated affective reactions (AARs) were further included to examine the effect of affect on aberrant driving behaviors. Considering the example of speeding behaviors, this study developed scales and conducted a two-wave survey of students in two departments at a university in Northern Taiwan. The analysis results show that habit strength consists of multiple aspects, and frequency of past behavior cannot be a complete repository for accumulating habit strength. Habit strength appeared to be a crucial mediator between intention antecedents (e.g., attitude) and the intention itself. Including habit strength in the TPB model enhanced the explained variance of speeding intention by 26.7%. In addition, AARs were different from attitudes; particularly, young drivers tended to perform speeding behaviors to reduce negative feelings such as regret. The proposed model provides an effective alternative approach for investigating aberrant driving behaviors; corresponding countermeasures are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. A Conceptual Model of Investor Behavior

    OpenAIRE

    Lovric, M.; Kaymak, U.; Spronk, J.

    2008-01-01

    textabstractBased on a survey of behavioral finance literature, this paper presents a descriptive model of individual investor behavior in which investment decisions are seen as an iterative process of interactions between the investor and the investment environment. This investment process is influenced by a number of interdependent variables and driven by dual mental systems, the interplay of which contributes to boundedly rational behavior where investors use various heuristics and may exh...

  14. A Conceptual Model of Investor Behavior

    NARCIS (Netherlands)

    M. Lovric (Milan); U. Kaymak (Uzay); J. Spronk (Jaap)

    2008-01-01

    textabstractBased on a survey of behavioral finance literature, this paper presents a descriptive model of individual investor behavior in which investment decisions are seen as an iterative process of interactions between the investor and the investment environment. This investment process is

  15. The association between graduated driver licensing laws and travel behaviors among adolescents: an analysis of US National Household Travel Surveys

    Directory of Open Access Journals (Sweden)

    Motao Zhu

    2016-07-01

    Full Text Available Abstract Background Young novice drivers have crash rates higher than any other age group. To address this problem, graduated driver licensing (GDL laws have been implemented in the United States to require an extended learner permit phase, and create night time driving or passenger restrictions for adolescent drivers. GDL allows adolescents to gain experience driving under low-risk conditions with the aim of reducing crashes. The restricted driving might increase riding with parents or on buses, which might be safer, or walking or biking, which might be more dangerous. We examined whether GDL increases non-driver travels, and whether it reduces total travels combining drivers and non-drivers. Methods We used data from the US National Household Travel Survey for the years 1995–1996, 2001–2002, and 2008–2009 to estimate the adjusted ratio for the number of trips and trip kilometers made by persons exposed to a GDL law, compared with those not exposed. Results Adolescents aged 16 years had fewer trips and kilometers as drivers when exposed to a GDL law: ratio 0.84 (95 % confidence interval (CI 0.71, 1.00 for trips; 0.79 (0.63, 0.98 for kilometers. For adolescents aged 17 years, the trip ratio was 0.94 (0.83, 1.07 and the kilometers ratio 0.80 (0.63, 1.03. There was little association between GDL laws and trips or kilometers traveled by other methods: ratio 1.03 for trips and 1.00 for kilometers for age 16 years, 0.94 for trips and 1.07 for kilometers for age 17. Conclusions If these associations are causal, GDL laws reduced driving kilometers by about 20 % for 16 and 17 year olds, and reduced the number of driving trips by 16 % among 16 year olds. GDL laws showed little relationship with trips by other methods.

  16. Drivers of past and future Arctic sea-ice evolution in CMIP5 models

    Science.gov (United States)

    Burgard, Clara; Notz, Dirk

    2016-04-01

    The Arctic sea-ice cover has been melting rapidly over the last decades. The main drivers of this sea-ice retreat are assumed to be changes in sea-ice thermodynamics, driven by changes in atmospheric surface fluxes and the oceanic heat flux at the base of the ice. To identify the fluxes most affecting past and future sea-ice evolution (under the RCP4.5 scenario) in climate models, we analyzed the surface energy budget over the Arctic Ocean in global climate models involved in the Coupled Model Intercomparison Project 5 (CMIP5) framework. In the multi-model ensemble annual mean, the sum of atmospheric fluxes increases from 1990 to 2045, mainly driven by an increase of the radiative surface fluxes and decreases from 2045 to 2099, mainly driven by an increase in upward turbulent heat fluxes. However, due to the large model spread, the future changes in the sum of atmospheric fluxes are not significant. These non-significant changes result from several effects counteracting each other under climate change. On the one hand, a higher CO2 concentration, air temperature and air moisture lead to a higher incoming energy flux (incoming longwave radiation). On the other hand, the resulting melt of sea ice leads to higher outgoing energy fluxes (outgoing longwave radiation, sensible heat flux, latent heat flux). Shortwave radiation behaves differently, but also in two counteracting ways, as higher air moisture leads to a decrease in incoming shortwave radiation and less sea-ice cover leads to a decrease in outgoing shortwave radiation. The small changes in the atmospheric fluxes can be converted to an energy gain or loss by the ocean/sea-ice system, either as sensible heat by changing the oceanic heat content or as latent heat by changing the sea-ice volume. Such analysis in the multi-model ensemble mean shows that the loss of energy at the surface due to atmospheric fluxes is decreasing during the 21st century, leading to an increase in oceanic heat content and an increase in

  17. Relational models for knowledge sharing behavior

    NARCIS (Netherlands)

    Boer, N.I.; Berends, J.J.; Baalen, P.

    2011-01-01

    In this paper we explore the relational dimension of knowledge sharing behavior by proposing a comprehensive theoretical framework for studying knowledge sharing in organizations. This theoretical framework originates from (Fiske, 1991) and (Fiske, 1992) Relational Models Theory (RMT). The RMT

  18. Punishment models of addictive behavior

    NARCIS (Netherlands)

    Vanderschuren, L.J.M.J.|info:eu-repo/dai/nl/126514917; Minnaard, A.M.|info:eu-repo/dai/nl/413292533; Smeets, J.A.S.|info:eu-repo/dai/nl/413578577; Lesscher, H.M.B.|info:eu-repo/dai/nl/258637196

    2017-01-01

    Substance addiction is a chronic relapsing brain disorder, characterized by loss of control over substance use. In recent years, there has been a lively interest in animal models of loss of control over substance use, using punishment paradigms. We provide an overview of punishment models of

  19. Attributing Asymmetric Productivity Responses to Internal Ecosystem Dynamics and External Drivers Using Probabilistic Models

    Science.gov (United States)

    Parolari, A.; Goulden, M.

    2017-12-01

    A major challenge to interpreting asymmetric changes in ecosystem productivity is the attribution of these changes to external climate forcing or to internal ecophysiological processes that respond to these drivers (e.g., photosynthesis response to drying soil). For example, positive asymmetry in productivity can result from either positive skewness in the distribution of annual rainfall amount or from negative curvature in the productivity response to annual rainfall. To analyze the relative influences of climate and ecosystem dynamics on both positive and negative asymmetry in multi-year ANPP experiments, we use a multi-scale coupled ecosystem water-carbon model to interpret field experimental results that span gradients of rainfall skewness and ANPP response curvature. The model integrates rainfall variability, soil moisture dynamics, and net carbon assimilation from the daily to inter-annual scales. From the underlying physical basis of the model, we compute the joint probability distribution of the minimum and maximum ANPP for an annual ANPP experiment of N years. The distribution is used to estimate the likelihood that either positive or negative asymmetry will be observed in an experiment, given the annual rainfall distribution and the ANPP response curve. We estimate the total asymmetry as the mode of this joint distribution and the relative contribution attributable to rainfall skewness as the mode for a linear ANPP response curve. Applied to data from several long-term ANPP experiments, we find that there is a wide range of observed ANPP asymmetry (positive and negative) and a spectrum of contributions from internal and external factors. We identify the soil water holding capacity relative to the mean rain event depth as a critical ecosystem characteristic that controls the non-linearity of the ANPP response and positive curvature at high rainfall. Further, the seasonal distribution of rainfall is shown to control the presence or absence of negative

  20. A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

    Directory of Open Access Journals (Sweden)

    Zutao Zhang

    2016-02-01

    Full Text Available In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT is adopted to extract the EEG power spectrum density (PSD. In this step, sparse representation classification combined with k-singular value decomposition (KSVD is firstly introduced in PSD to estimate the driver’s vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

  1. The modeling of transfer of steering between automated vehicle and human driver using hybrid control framework

    NARCIS (Netherlands)

    Kaustubh, M.; Willemsen, DMC; Mazo Espinosa, M.; Sjöberg, J.; Morris, B.

    2016-01-01

    Proponents of autonomous driving pursue driverless technologies, whereas others foresee a gradual transition where there will be automated driving systems that share the control of the vehicle with the driver. With such advances it becomes pertinent that the developed automated systems need to be

  2. The modeling of transfer of steering between automated vehicle and human driver using hybrid control framework

    NARCIS (Netherlands)

    Kaustubh, M.; Willemsen, D.M.C.; Mazo, M.

    2016-01-01

    Proponents of autonomous driving pursue driverless technologies, whereas others foresee a gradual transition where there will be automated driving systems that share the control of the vehicle with the driver. With such advances it becomes pertinent that the developed automated systems need to be

  3. Aligning drivers, contract, and management of IT-outsourcing relationships: a type-dependent model

    DEFF Research Database (Denmark)

    Arenfeldt, Katrine; Corty Dam, Amalie; Fenger, Kim Harder

    2017-01-01

    In today’s competitive business environment, information technology outsourcing has become a wide-spread reality across all industries and sectors. Researchers have investigated this complex phenomenon from various angles, and established a sound knowledge base regarding the drivers, management, ...

  4. Evaluation of Massey Ferguson Model 165 Tractor Drivers exposed to whole-body vibration

    Directory of Open Access Journals (Sweden)

    P. Nassiri

    2013-12-01

    Conclusion: This study shows that the need to provide intervention , controlling and managing measures to eliminate or reduce exposure to whole body vibration among tractor drivers its necessary. And, preventing main disorder Including musculoskeletal disorders, discomfort and early fatigue is of circular importance. More studies are also necessary to identify the sources of vibration among various of tractors.

  5. Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model.

    Science.gov (United States)

    Kim, Dae-Hwan; Ramjan, Lucie M; Mak, Kwok-Kei

    2016-01-01

    Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea. A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience. Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes. Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

  6. An integrative model of organizational safety behavior.

    Science.gov (United States)

    Cui, Lin; Fan, Di; Fu, Gui; Zhu, Cherrie Jiuhua

    2013-06-01

    This study develops an integrative model of safety management based on social cognitive theory and the total safety culture triadic framework. The purpose of the model is to reveal the causal linkages between a hazardous environment, safety climate, and individual safety behaviors. Based on primary survey data from 209 front-line workers in one of the largest state-owned coal mining corporations in China, the model is tested using structural equation modeling techniques. An employee's perception of a hazardous environment is found to have a statistically significant impact on employee safety behaviors through a psychological process mediated by the perception of management commitment to safety and individual beliefs about safety. The integrative model developed here leads to a comprehensive solution that takes into consideration the environmental, organizational and employees' psychological and behavioral aspects of safety management. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

  7. Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control.

    Science.gov (United States)

    de Croon, E M; Blonk, R W B; de Zwart, B C H; Frings-Dresen, M H W; Broersen, J P J

    2002-06-01

    Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers. From 1181 lorry drivers (adjusted response 63%) self reported information was gathered by questionnaire on the independent variables (job control, quantitative workload, physical demands, and supervisor demands) and the dependent variables (fatigue and job dissatisfaction). Stepwise multiple regression analyses were performed to examine the main effects of job demands and job control and the interaction effect between job control and job demands on fatigue and job dissatisfaction. The inclusion of physical and supervisor demands in the JD-C model explained a significant amount of variance in fatigue (3%) and job dissatisfaction (7%) over and above job control and quantitative workload. Moreover, in accordance with Karasek's interaction hypothesis, job control buffered the positive relation between quantitative workload and job dissatisfaction. Despite methodological limitations, the results suggest that the inclusion of (occupation) specific job control and job demand measures is a fruitful elaboration of the JD-C model. The occupation specific JD-C model gives occupational stress researchers better insight into the relation between the psychosocial work environment and wellbeing. Moreover, the occupation specific JD-C model may give practitioners more concrete and useful information about risk factors in the psychosocial work environment. Therefore, this model may provide points of departure for effective stress reducing interventions at work.

  8. Are professional drivers less sleepy than non-professional drivers?

    Science.gov (United States)

    Anund, Anna; Ahlström, Christer; Fors, Carina; Åkerstedt, Torbjörn

    2018-01-01

    Objective It is generally believed that professional drivers can manage quite severe fatigue before routine driving performance is affected. In addition, there are results indicating that professional drivers can adapt to prolonged night shifts and may be able to learn to drive without decreased performance under high levels of sleepiness. However, very little research has been conducted to compare professionals and non-professionals when controlling for time driven and time of day. Method The aim of this study was to use a driving simulator to investigate whether professional drivers are more resistant to sleep deprivation than non-professional drivers. Differences in the development of sleepiness (self-reported, physiological and behavioral) during driving was investigated in 11 young professional and 15 non-professional drivers. Results Professional drivers self-reported significantly lower sleepiness while driving a simulator than non-professional drivers. In contradiction, they showed longer blink durations and more line crossings, both of which are indicators of sleepiness. They also drove faster. The reason for the discrepancy in the relation between the different sleepiness indicators for the two groups could be due to more experience to sleepiness among the professional drivers or possibly to the faster speed, which might unconsciously have been used by the professionals to try to counteract sleepiness. Conclusion Professional drivers self-reported significantly lower sleepiness while driving a simulator than non-professional drivers. However, they showed longer blink durations and more line crossings, both of which are indicators of sleepiness, and they drove faster.

  9. Principle for the Validation of a Driving Support using a Computer Vision-Based Driver Modelization on a Simulator

    Directory of Open Access Journals (Sweden)

    Baptiste Rouzier

    2015-07-01

    Full Text Available This paper presents a new structure for a driving support designed to compensate for the problems caused by the behaviour of the driver without causing a feeling of unease. This assistance is based on a shared control between the human and an automatic support that computes and applies an assisting torque on the steering wheel. This torque is computed from a representation of the hazards encountered on the road by virtual potentials. However, the equilibrium between the relative influences of the human and the support on the steering wheel are difficult to find and depend upon the situation. This is why this driving support includes a modelization of the driver based on an analysis of several face features using a computer vision algorithm. The goal is to determine whether the driver is drowsy or whether he is paying attention to some specific points in order to adapt the strength of the support. The accuracy of the measurements made on the face features is estimated, and the interest of the proposal as well as the concepts raised by such assistance are studied through simulations.

  10. Calibrating and Validating a Simulation Model to Identify Drivers of Urban Land Cover Change in the Baltimore, MD Metropolitan Region

    Directory of Open Access Journals (Sweden)

    Claire Jantz

    2014-09-01

    Full Text Available We build upon much of the accumulated knowledge of the widely used SLEUTH urban land change model and offer advances. First, we use SLEUTH’s exclusion/attraction layer to identify and test different urban land cover change drivers; second, we leverage SLEUTH’s self-modification capability to incorporate a demographic model; and third, we develop a validation procedure to quantify the influence of land cover change drivers and assess uncertainty. We found that, contrary to our a priori expectations, new development is not attracted to areas serviced by existing or planned water and sewer infrastructure. However, information about where population and employment growth is likely to occur did improve model performance. These findings point to the dominant role of centrifugal forces in post-industrial cities like Baltimore, MD. We successfully developed a demographic model that allowed us to constrain the SLEUTH model forecasts and address uncertainty related to the dynamic relationship between changes in population and employment and urban land use. Finally, we emphasize the importance of model validation. In this work the validation procedure played a key role in rigorously assessing the impacts of different exclusion/attraction layers and in assessing uncertainty related to population and employment forecasts.

  11. Models of iodine behavior in reactor containments

    Energy Technology Data Exchange (ETDEWEB)

    Weber, C.F.; Beahm, E.C.; Kress, T.S.

    1992-10-01

    Models are developed for many phenomena of interest concerning iodine behavior in reactor containments during severe accidents. Processes include speciation in both gas and liquid phases, reactions with surfaces, airborne aerosols, and other materials, and gas-liquid interface behavior. Although some models are largely empirical formulations, every effort has been made to construct mechanistic and rigorous descriptions of relevant chemical processes. All are based on actual experimental data generated at the Oak Ridge National Laboratory (ORNL) or elsewhere, and, hence, considerable data evaluation and parameter estimation are contained in this study. No application or encoding is attempted, but each model is stated in terms of rate processes, with the intention of allowing mechanistic simulation. Taken together, this collection of models represents a best estimate iodine behavior and transport in reactor accidents.

  12. Models of iodine behavior in reactor containments

    International Nuclear Information System (INIS)

    Weber, C.F.; Beahm, E.C.; Kress, T.S.

    1992-10-01

    Models are developed for many phenomena of interest concerning iodine behavior in reactor containments during severe accidents. Processes include speciation in both gas and liquid phases, reactions with surfaces, airborne aerosols, and other materials, and gas-liquid interface behavior. Although some models are largely empirical formulations, every effort has been made to construct mechanistic and rigorous descriptions of relevant chemical processes. All are based on actual experimental data generated at the Oak Ridge National Laboratory (ORNL) or elsewhere, and, hence, considerable data evaluation and parameter estimation are contained in this study. No application or encoding is attempted, but each model is stated in terms of rate processes, with the intention of allowing mechanistic simulation. Taken together, this collection of models represents a best estimate iodine behavior and transport in reactor accidents

  13. Model analysis of adaptive car driving behavior

    NARCIS (Netherlands)

    Wewerinke, P.H.

    1996-01-01

    This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks. As an illustrative example the overtaking task is considered and modeled in system theoretic terms.

  14. Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.

    Science.gov (United States)

    Wali, Behram; Khattak, Asad J; Xu, Jingjing

    2018-01-01

    The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability

  15. Explaining clinical behaviors using multiple theoretical models

    OpenAIRE

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-01-01

    Abstract Background In the field of implementation research, there is an increased interest in use of theory when designing implementation research studies involving behavior change. In 2003, we initiated a series of five studies to establish a scientific rationale for interventions to translate research findings into clinical practice by exploring the performance of a number of different, commonly used, overlapping behavioral theories and models. We reflect on the strengths and weaknesses of...

  16. Applying incentive sensitization models to behavioral addiction

    DEFF Research Database (Denmark)

    Rømer Thomsen, Kristine; Fjorback, Lone; Møller, Arne

    2014-01-01

    The incentive sensitization theory is a promising model for understanding the mechanisms underlying drug addiction, and has received support in animal and human studies. So far the theory has not been applied to the case of behavioral addictions like Gambling Disorder, despite sharing clinical...... symptoms and underlying neurobiology. We examine the relevance of this theory for Gambling Disorder and point to predictions for future studies. The theory promises a significant contribution to the understanding of behavioral addiction and opens new avenues for treatment....

  17. Organizational buying behavior: An integrated model

    Directory of Open Access Journals (Sweden)

    Rakić Beba

    2002-01-01

    Full Text Available Organizational buying behavior is decision making process by which formal organizations establish the need for purchased products and services, and identify, evaluate, and choose among alternative brands and suppliers. Understanding the buying decision processes is essential to developing the marketing programs of companies that sell to organizations, or to 'industrial customers'. In business (industrial marketing, exchange relationships between the organizational selling center and the organizational buying center are crucial. Integrative model of organizational buying behavior offers a systematic framework in analyzing the complementary factors and what effect they have on the behavior of those involved in making buying decisions.

  18. Explaining clinical behaviors using multiple theoretical models

    Directory of Open Access Journals (Sweden)

    Eccles Martin P

    2012-10-01

    Full Text Available Abstract Background In the field of implementation research, there is an increased interest in use of theory when designing implementation research studies involving behavior change. In 2003, we initiated a series of five studies to establish a scientific rationale for interventions to translate research findings into clinical practice by exploring the performance of a number of different, commonly used, overlapping behavioral theories and models. We reflect on the strengths and weaknesses of the methods, the performance of the theories, and consider where these methods sit alongside the range of methods for studying healthcare professional behavior change. Methods These were five studies of the theory-based cognitions and clinical behaviors (taking dental radiographs, performing dental restorations, placing fissure sealants, managing upper respiratory tract infections without prescribing antibiotics, managing low back pain without ordering lumbar spine x-rays of random samples of primary care dentists and physicians. Measures were derived for the explanatory theoretical constructs in the Theory of Planned Behavior (TPB, Social Cognitive Theory (SCT, and Illness Representations specified by the Common Sense Self Regulation Model (CSSRM. We constructed self-report measures of two constructs from Learning Theory (LT, a measure of Implementation Intentions (II, and the Precaution Adoption Process. We collected data on theory-based cognitions (explanatory measures and two interim outcome measures (stated behavioral intention and simulated behavior by postal questionnaire survey during the 12-month period to which objective measures of behavior (collected from routine administrative sources were related. Planned analyses explored the predictive value of theories in explaining variance in intention, behavioral simulation and behavior. Results Response rates across the five surveys ranged from 21% to 48%; we achieved the target sample size for three of

  19. Explaining clinical behaviors using multiple theoretical models.

    Science.gov (United States)

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-10-17

    In the field of implementation research, there is an increased interest in use of theory when designing implementation research studies involving behavior change. In 2003, we initiated a series of five studies to establish a scientific rationale for interventions to translate research findings into clinical practice by exploring the performance of a number of different, commonly used, overlapping behavioral theories and models. We reflect on the strengths and weaknesses of the methods, the performance of the theories, and consider where these methods sit alongside the range of methods for studying healthcare professional behavior change. These were five studies of the theory-based cognitions and clinical behaviors (taking dental radiographs, performing dental restorations, placing fissure sealants, managing upper respiratory tract infections without prescribing antibiotics, managing low back pain without ordering lumbar spine x-rays) of random samples of primary care dentists and physicians. Measures were derived for the explanatory theoretical constructs in the Theory of Planned Behavior (TPB), Social Cognitive Theory (SCT), and Illness Representations specified by the Common Sense Self Regulation Model (CSSRM). We constructed self-report measures of two constructs from Learning Theory (LT), a measure of Implementation Intentions (II), and the Precaution Adoption Process. We collected data on theory-based cognitions (explanatory measures) and two interim outcome measures (stated behavioral intention and simulated behavior) by postal questionnaire survey during the 12-month period to which objective measures of behavior (collected from routine administrative sources) were related. Planned analyses explored the predictive value of theories in explaining variance in intention, behavioral simulation and behavior. Response rates across the five surveys ranged from 21% to 48%; we achieved the target sample size for three of the five surveys. For the predictor variables

  20. Modeling of tritium behavior in Li2O

    International Nuclear Information System (INIS)

    Billone, M.C.; Attaya, H.; Kopasz, J.P.

    1992-08-01

    The TIARA and DISPL2 codes are being developed at Argonne National Laboratory to predict tritium retention and release from lithium ceramics under steady-state and transient conditions, respectively. Tritium retention and release are important design and safety issues for tritium-breeding blankets of fusion reactors. Emphasis has been placed on tritium behavior in Li 2 O because of the selection of this ceramic as a first option for the ITER driver blanket and because of the relatively good material properties data base for Li 2 O. Models and correlations for diffusion, surface desorption/adsorption, and solubility/precipitation of tritium in Li 2 0 have been developed based on well-controlled laboratory data from as-fabricated and irradiated samples. With the models and correlations, the codes are validated to the results of in-reactor purge flow tests. The results of validation of TIARA to tritium retention data from VOM-15H, EXOTIC-2, and CRITIC-1 are presented, along with predictions of tritium retention in BEATRIX-II. For DISPL2, results are presented for tritium release predictions vs. data for MOZART, CRITIC-1, and BEATRIX-II. Recommendations are made for improving both the data base and the modeling to allow extrapolation with reasonable uncertainty levels to fusion reactor design conditions

  1. Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

    Science.gov (United States)

    Peng, L.; Sheffield, J.; Li, D.

    2015-12-01

    Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

  2. FORMALIZATION OF LOCOMOTIVE DRIVER ACTIVITY TENSION INDICATOR BASED ON THE ERGONOMIC MODEL

    Directory of Open Access Journals (Sweden)

    O. M. Horobchenko

    2017-02-01

    Full Text Available Purpose. A key factor contributing to the safety and quality of ergatic system "train-driver" is the intensity of the locomotive crew’s work. The aim of this work is formalization of locomotive driver activity tension indicator. Methodology. One of the characteristics of driver activity tension is the difference between the time allotted to complete the task, and the necessary (external reserve or deficiency time. The sets of major and minor operations in the management of the train locomotive in different train situations were identified. Using the methods of fuzzy logic, the concept of "materiality of the operation of the locomotive control" is presented in the form of a set of linguistic variables. To determine the function membership of the elements of the set "the importance of the operation of the locomotive control" the method of expert evaluations was used. Coefficient of temporary tension is presented in the form of fuzzy number L-R-type. Findings. It was found the value of the relative number of operations of locomotive control according to the distribution using the parameter of operation "importance". To determine the most tensioned mode of the driver ranking the traffic condition according to the parameter of relative amounts of the important management operations was conducted. The most difficult modes are the "front hindrance", "movement in unfavorable weather conditions" and "departure from the station to the running line". Originality. The introduction of the value "conventional importance of the operation" allowed us to more accurately describe the terms of train driving. For the first time the work presents determination of tension of the driver’s work in the form of a unimodal fuzzy number, which will make it possible to use the methods of the theory of artificial intelligence to simulate activity of the locomotive driver and develop intelligent control systems. Practical value. There were obtained the opportunity to

  3. Modelling aerosol behavior in reactor cooling systems

    International Nuclear Information System (INIS)

    McDonald, B.H.

    1990-01-01

    This paper presents an overview of some of the areas of concern in using computer codes to model fission-product aerosol behavior in the reactor cooling system (RCS) of a water-cooled nuclear reactor during a loss-of-coolant accident. The basic physical processes that require modelling include: fission product release and aerosol formation in the reactor core, aerosol transport and deposition in the reactor core and throughout the rest of the RCS, and the interaction between aerosol transport processes and the thermalhydraulics. In addition to these basic physical processes, chemical reactions can have a large influence on the nature of the aerosol and its behavior in the RCS. The focus is on the physics and the implications of numerical methods used in the computer codes to model aerosol behavior in the RCS

  4. The sex disparity in risky driving: A survey of Colombian young drivers.

    Science.gov (United States)

    Oviedo-Trespalacios, Oscar; Scott-Parker, Bridie

    2018-01-02

    The overrepresentation of young drivers in poor road safety outcomes has long been recognized as a global road safety issue. In addition, the overrepresentation of males in crash statistics has been recognized as a pervasive young driver problem. Though progress in road safety evidenced as a stabilization and/or reduction in poor road safety outcomes has been made in developed nations, less-developed nations contribute the greatest road safety trauma, and developing nations such as Colombia continue to experience increasing trends in fatality rates. The aim of the research was to explore sex differences in self-reported risky driving behaviors of young drivers, including the associations with crash involvement, in a sample of young drivers attending university in Colombia. The Spanish version of the Behaviour of Young Novice Drivers Scale (BYNDS-Sp) was applied in an online survey to a sample of 392 students (225 males) aged 16-24 years attending a major university. Appropriate comparative statistics and logistic regression modeling were used when analyzing the data. Males reported consistently more risky driving behaviors, with approximately one quarter of all participants reporting risky driving exposure. Males reported greater crash involvement, with violations such as speeding associated with crash involvement for both males and females. Young drivers in Colombia appear to engage in the same risky driving behaviors as young drivers in developed nations. In addition, young male drivers in Colombia reported greater engagement in risky driving behaviors than young female drivers, a finding consistent with the behaviors of young male drivers in developed nations. As such, the research findings suggest that general interventions such as education, engineering, and enforcement should target transient rule violations such as speeding and using a handheld mobile phone while driving for young drivers in Colombia. Future research should investigate how these

  5. Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior.

    Science.gov (United States)

    Bell, Jennifer L; Taylor, Matthew A; Chen, Guang-Xiang; Kirk, Rachel D; Leatherman, Erin R

    2017-02-01

    Roadway incidents are the leading cause of work-related death in the United States. The objective of this research was to evaluate whether two types of feedback from a commercially available in-vehicle monitoring system (IVMS) would reduce the incidence of risky driving behaviors in drivers from two companies. IVMS were installed in 315 vehicles representing the industries of local truck transportation and oil and gas support operations, and data were collected over an approximate two-year period in intervention and control groups. In one period, intervention group drivers were given feedback from in-cab warning lights from an IVMS that indicated occurrence of harsh vehicle maneuvers. In another period, intervention group drivers viewed video recordings of their risky driving behaviors with supervisors, and were coached by supervisors on safe driving practices. Risky driving behaviors declined significantly more during the period with coaching plus instant feedback with lights in comparison to the period with lights-only feedback (ORadj=0.61 95% CI 0.43-0.86; Holm-adjusted p=0.035) and the control group (ORadj=0.52 95% CI 0.33-0.82; Holm-adjusted p=0.032). Lights-only feedback was not found to be significantly different than the control group's decline from baseline (ORadj=0.86 95% CI 0.51-1.43; Holm-adjusted p>0.05). The largest decline in the rate of risky driving behaviors occurred when feedback included both supervisory coaching and lights. Supervisory coaching is an effective form of feedback to improve driving habits in the workplace. The potential advantages and limitations of this IVMS-based intervention program are discussed. Published by Elsevier Ltd.

  6. Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems.

    Science.gov (United States)

    Rahman, Md Mahmudur; Lesch, Mary F; Horrey, William J; Strawderman, Lesley

    2017-11-01

    Advanced Driver Assistance Systems (ADAS) are intended to enhance driver performance and improve transportation safety. The potential benefits of these technologies, such as reduction in number of crashes, enhancing driver comfort or convenience, decreasing environmental impact, etc., have been acknowledged by transportation safety researchers and federal transportation agencies. Although these systems afford safety advantages, they may also challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the implementation of these systems into the transportation system. Recognizing the need for research into the factors affecting driver acceptance, this study assessed the utility of the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT) for modelling driver acceptance in terms of Behavioral Intention to use an ADAS. Each of these models propose a set of factors that influence acceptance of a technology. Data collection was done using two approaches: a driving simulator approach and an online survey approach. In both approaches, participants interacted with either a fatigue monitoring system or an adaptive cruise control system combined with a lane-keeping system. Based on their experience, participants responded to several survey questions to indicate their attitude toward using the ADAS and their perception of its usefulness, usability, etc. A sample of 430 surveys were collected for this study. Results found that all the models (TAM, TPB, and UTAUT) can explain driver acceptance with their proposed sets of factors, each explaining 71% or more of the variability in Behavioral Intention. Among the models, TAM was found to perform the best in modelling driver acceptance followed by TPB. The findings of this study confirm that these models can be applied to ADAS technologies and that they provide a basis for understanding driver

  7. Capitalizing on Citizen Science Data for Validating Models and Generating Hypotheses Describing Meteorological Drivers of Mosquito-Borne Disease Risk

    Science.gov (United States)

    Boger, R. A.; Low, R.; Paull, S.; Anyamba, A.; Soebiyanto, R. P.

    2017-12-01

    Temperature and precipitation are important drivers of mosquito population dynamics, and a growing set of models have been proposed to characterize these relationships. Validation of these models, and development of broader theories across mosquito species and regions could nonetheless be improved by comparing observations from a global dataset of mosquito larvae with satellite-based measurements of meteorological variables. Citizen science data can be particularly useful for two such aspects of research into the meteorological drivers of mosquito populations: i) Broad-scale validation of mosquito distribution models and ii) Generation of quantitative hypotheses regarding changes to mosquito abundance and phenology across scales. The recently released GLOBE Observer Mosquito Habitat Mapper (GO-MHM) app engages citizen scientists in identifying vector taxa, mapping breeding sites and decommissioning non-natural habitats, and provides a potentially useful new tool for validating mosquito ubiquity projections based on the analysis of remotely sensed environmental data. Our early work with GO-MHM data focuses on two objectives: validating citizen science reports of Aedes aegypti distribution through comparison with accepted scientific data sources, and exploring the relationship between extreme temperature and precipitation events and subsequent observations of mosquito larvae. Ultimately the goal is to develop testable hypotheses regarding the shape and character of this relationship between mosquito species and regions.

  8. Error Resilient Video Compression Using Behavior Models

    Directory of Open Access Journals (Sweden)

    Jacco R. Taal

    2004-03-01

    Full Text Available Wireless and Internet video applications are inherently subjected to bit errors and packet errors, respectively. This is especially so if constraints on the end-to-end compression and transmission latencies are imposed. Therefore, it is necessary to develop methods to optimize the video compression parameters and the rate allocation of these applications that take into account residual channel bit errors. In this paper, we study the behavior of a predictive (interframe video encoder and model the encoders behavior using only the statistics of the original input data and of the underlying channel prone to bit errors. The resulting data-driven behavior models are then used to carry out group-of-pictures partitioning and to control the rate of the video encoder in such a way that the overall quality of the decoded video with compression and channel errors is optimized.

  9. Integrating Norm Activation Model and Theory of Planned Behavior to Understand Sustainable Transport Behavior: Evidence from China.

    Science.gov (United States)

    Liu, Yuwei; Sheng, Hong; Mundorf, Norbert; Redding, Colleen; Ye, Yinjiao

    2017-12-18

    With increasing urbanization in China, many cities are facing serious environmental problems due to continuous and substantial increase in automobile transportation. It is becoming imperative to examine effective ways to reduce individual automobile use to facilitate sustainable transportation behavior. Empirical, theory-based research on sustainable transportation in China is limited. In this research, we propose an integrated model based on the norm activation model and the theory of planned behavior by combining normative and rational factors to predict individuals' intention to reduce car use. Data from a survey of 600 car drivers in China's three metropolitan areas was used to test the proposed model and hypotheses. Results showed that three variables, perceived norm of car-transport reduction, attitude towards reduction, and perceived behavior control over car-transport reduction, significantly affected the intention to reduce car-transport. Personal norms mediated the relationship between awareness of consequences of car-transport, ascription of responsibility of car-transport, perceived subjective norm for car-transport reduction, and intention to reduce car-transport. The results of this research not only contribute to theory development in the area of sustainable transportation behavior, but also provide a theoretical frame of reference for relevant policy-makers in urban transport management.

  10. Integrating Norm Activation Model and Theory of Planned Behavior to Understand Sustainable Transport Behavior: Evidence from China

    Directory of Open Access Journals (Sweden)

    Yuwei Liu

    2017-12-01

    Full Text Available With increasing urbanization in China, many cities are facing serious environmental problems due to continuous and substantial increase in automobile transportation. It is becoming imperative to examine effective ways to reduce individual automobile use to facilitate sustainable transportation behavior. Empirical, theory-based research on sustainable transportation in China is limited. In this research, we propose an integrated model based on the norm activation model and the theory of planned behavior by combining normative and rational factors to predict individuals’ intention to reduce car use. Data from a survey of 600 car drivers in China’s three metropolitan areas was used to test the proposed model and hypotheses. Results showed that three variables, perceived norm of car-transport reduction, attitude towards reduction, and perceived behavior control over car-transport reduction, significantly affected the intention to reduce car-transport. Personal norms mediated the relationship between awareness of consequences of car-transport, ascription of responsibility of car-transport, perceived subjective norm for car-transport reduction, and intention to reduce car-transport. The results of this research not only contribute to theory development in the area of sustainable transportation behavior, but also provide a theoretical frame of reference for relevant policy-makers in urban transport management.

  11. Behavioral and statistical models of educational inequality

    DEFF Research Database (Denmark)

    Holm, Anders; Breen, Richard

    2016-01-01

    This paper addresses the question of how students and their families make educational decisions. We describe three types of behavioral model that might underlie decision-making and we show that they have consequences for what decisions are made. Our study thus has policy implications if we wish...

  12. Modeling landowner behavior regarding forest certification

    Science.gov (United States)

    David C. Mercker; Donald G. Hodges

    2008-01-01

    Nonindustrial private forest owners in western Tennessee were surveyed to assess their awareness, acceptance, and perceived benefits of forest certification. More than 80 percent of the landowners indicated a willingness to consider certification for their lands. A model was created to explain landowner behavior regarding their willingness to consider certification....

  13. A conceptual model of investor behavior

    NARCIS (Netherlands)

    Lovric, M.; Kaymak, U.; Spronk, J.; Nefti, S.; Gray, J.O.

    2010-01-01

    Behavioral finance is a subdiscipline of finance that uses insights from cogni tive and social psychology to enrich our knowledge of how investors make their financial decisions. Agent-based artificial financial markets are bottomup models of financial markets that start from the micro level of

  14. Models of behavioral change and adaptation

    NARCIS (Netherlands)

    Rasouli, S.; Timmermans, H.J.P.; Zhang, J.

    2017-01-01

    This chapter explains and summarizes models of behavioral change and adaptation, which have received less application in the life choice analysis associated with urban policy. Related to various life choices, life trajectory events are major decisions with a relatively long-lasting impact, such as

  15. Understanding young and older male drivers' willingness to drive while intoxicated: the predictive utility of constructs specified by the theory of planned behaviour and the prototype willingness model.

    Science.gov (United States)

    Rivis, Amanda; Abraham, Charles; Snook, Sarah

    2011-05-01

    The present study examined the predictive utility of constructs specified by the theory of planned behaviour (TPB) and prototype willingness model (PWM) for young and older male drivers' willingness to drive while intoxicated. A cross-sectional questionnaire was employed. Two hundred male drivers, recruited via a street survey, voluntarily completed measures of attitude, subjective norm, perceived behavioural control, prototype perceptions, and willingness. Findings showed that the TPB and PWM variables explained 65% of the variance in young male drivers' willingness and 47% of the variance in older male drivers' willingness, with the interaction between prototype favourability and similarity contributing 7% to the variance explained in older males' willingness to drive while intoxicated. The findings possess implications for theory, research, and anti-drink driving campaigns. ©2010 The British Psychological Society.

  16. A Conceptual Model of Natural and Anthropogenic Drivers and Their Influence on the Prince William Sound, Alaska, Ecosystem.

    Science.gov (United States)

    Harwell, Mark A; Gentile, John H; Cummins, Kenneth W; Highsmith, Raymond C; Hilborn, Ray; McRoy, C Peter; Parrish, Julia; Weingartner, Thomas

    2010-07-01

    Prince William Sound (PWS) is a semi-enclosed fjord estuary on the coast of Alaska adjoining the northern Gulf of Alaska (GOA). PWS is highly productive and diverse, with primary productivity strongly coupled to nutrient dynamics driven by variability in the climate and oceanography of the GOA and North Pacific Ocean. The pelagic and nearshore primary productivity supports a complex and diverse trophic structure, including large populations of forage and large fish that support many species of marine birds and mammals. High intra-annual, inter-annual, and interdecadal variability in climatic and oceanographic processes as drives high variability in the biological populations. A risk-based conceptual ecosystem model (CEM) is presented describing the natural processes, anthropogenic drivers, and resultant stressors that affect PWS, including stressors caused by the Great Alaska Earthquake of 1964 and the Exxon Valdez oil spill of 1989. A trophodynamic model incorporating PWS valued ecosystem components is integrated into the CEM. By representing the relative strengths of driver/stressors/effects, the CEM graphically demonstrates the fundamental dynamics of the PWS ecosystem, the natural forces that control the ecological condition of the Sound, and the relative contribution of natural processes and human activities to the health of the ecosystem. The CEM illustrates the dominance of natural processes in shaping the structure and functioning of the GOA and PWS ecosystems.

  17. Mapping potential carbon and timber losses from hurricanes using a decision tree and ecosystem services driver model.

    Science.gov (United States)

    Delphin, S; Escobedo, F J; Abd-Elrahman, A; Cropper, W

    2013-11-15

    Information on the effect of direct drivers such as hurricanes on ecosystem services is relevant to landowners and policy makers due to predicted effects from climate change. We identified forest damage risk zones due to hurricanes and estimated the potential loss of 2 key ecosystem services: aboveground carbon storage and timber volume. Using land cover, plot-level forest inventory data, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and a decision tree-based framework; we determined potential damage to subtropical forests from hurricanes in the Lower Suwannee River (LS) and Pensacola Bay (PB) watersheds in Florida, US. We used biophysical factors identified in previous studies as being influential in forest damage in our decision tree and hurricane wind risk maps. Results show that 31% and 0.5% of the total aboveground carbon storage in the LS and PB, respectively was located in high forest damage risk (HR) zones. Overall 15% and 0.7% of the total timber net volume in the LS and PB, respectively, was in HR zones. This model can also be used for identifying timber salvage areas, developing ecosystem service provision and management scenarios, and assessing the effect of other drivers on ecosystem services and goods. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Robust driver heartbeat estimation: A q-Hurst exponent based automatic sensor change with interactive multi-model EKF.

    Science.gov (United States)

    Vrazic, Sacha

    2015-08-01

    Preventing car accidents by monitoring the driver's physiological parameters is of high importance. However, existing measurement methods are not robust to driver's body movements. In this paper, a system that estimates the heartbeat from the seat embedded piezoelectric sensors, and that is robust to strong body movements is presented. Multifractal q-Hurst exponents are used within a classifier to predict the most probable best sensor signal to be used in an Interactive Multi-Model Extended Kalman Filter pulsation estimation procedure. The car vibration noise is reduced using an autoregressive exogenous model to predict the noise on sensors. The performance of the proposed system was evaluated on real driving data up to 100 km/h and with slaloms at high speed. It is shown that this method improves by 36.7% the pulsation estimation under strong body movement compared to static sensor pulsation estimation and appears to provide reliable pulsation variability information for top-level analysis of drowsiness or other conditions.

  19. A learning-based autonomous driver: emulate human driver's intelligence in low-speed car following

    Science.gov (United States)

    Wei, Junqing; Dolan, John M.; Litkouhi, Bakhtiar

    2010-04-01

    In this paper, an offline learning mechanism based on the genetic algorithm is proposed for autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is implemented based on a Prediction- and Cost function-Based algorithm (PCB). PCB is designed to emulate a human driver's decision process, which is modeled as traffic scenario prediction and evaluation. This paper focuses on using a learning algorithm to optimize PCB with very limited training data, so that PCB can have the ability to predict and evaluate traffic scenarios similarly to human drivers. 80 seconds of human driving data was collected in low-speed (car-following scenarios. In the low-speed car-following tests, PCB was able to perform more human-like carfollowing after learning. A more general 120 kilometer-long simulation showed that PCB performs robustly even in scenarios that are not part of the training set.

  20. Excellent gamer, excellent driver? The impact of adolescents' video game playing on driving behavior: a two-wave panel study.

    Science.gov (United States)

    Beullens, Kathleen; Roe, Keith; Van den Bulck, Jan

    2011-01-01

    This study explored the impact of adolescents' playing of racing and drive'em up games on their risky driving behavior. Participants were 354 adolescent boys and girls who took part in a longitudinal panel survey on video game playing and risk taking attitudes, intentions and behaviors. In line with cultivation theory and theory of planned behavior the results showed that (even after controlling for aggression and sensation seeking) video game playing during adolescence succeeded in predicting later risky driving behavior through adolescents' attitudes and intentions to exhibit this behavior in the future. The results suggest that this relationship may in part be explained by the game content. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. Discrete time modelization of human pilot behavior

    Science.gov (United States)

    Cavalli, D.; Soulatges, D.

    1975-01-01

    This modelization starts from the following hypotheses: pilot's behavior is a time discrete process, he can perform only one task at a time and his operating mode depends on the considered flight subphase. Pilot's behavior was observed using an electro oculometer and a simulator cockpit. A FORTRAN program has been elaborated using two strategies. The first one is a Markovian process in which the successive instrument readings are governed by a matrix of conditional probabilities. In the second one, strategy is an heuristic process and the concepts of mental load and performance are described. The results of the two aspects have been compared with simulation data.

  2. A motivational model for environmentally responsible behavior.

    Science.gov (United States)

    Tabernero, Carmen; Hernández, Bernardo

    2012-07-01

    This paper presents a study examining whether self-efficacy and intrinsic motivation are related to environmentally responsible behavior (ERB). The study analysed past environmental behavior, self-regulatory mechanisms (self-efficacy, satisfaction, goals), and intrinsic and extrinsic motivation in relation to ERBs in a sample of 156 university students. Results show that all the motivational variables studied are linked to ERB. The effects of self-efficacy on ERB are mediated by the intrinsic motivation responses of the participants. A theoretical model was created by means of path analysis, revealing the power of motivational variables to predict ERB. Structural equation modeling was used to test and fit the research model. The role of motivational variables is discussed with a view to creating adequate learning contexts and experiences to generate interest and new sensations in which self-efficacy and affective reactions play an important role.

  3. Modeling irrigation behavior in groundwater systems

    Science.gov (United States)

    Foster, Timothy; Brozović, Nicholas; Butler, Adrian P.

    2014-08-01

    Integrated hydro-economic models have been widely applied to water management problems in regions of intensive groundwater-fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.

  4. Empirical assessment of loyalty drivers using consumers’ retail format choice

    Directory of Open Access Journals (Sweden)

    Gindi, A.A.

    2017-05-01

    Full Text Available Using Stimulus–Organism–Response (S-O-R framework, this study examines Stimulus– Response relationships of fresh vegetable consumers’ behavior in Klang Valley, Malaysia. In particular, the study focused on how loyalty drivers affect retail formats choice by the fresh vegetable (FV consumers. The Stimuli that pertain to loyalty drivers include promotional activities, perceived price and social interaction and the Response is the retail format choice. Three hypotheses were developed and tested with the data collected from a survey using simple random sampling technique. Structural Equation Model (SEM was used in analyzing the data. Results of the study revealed that Stimuli (loyalty drivers influence Response (retail format choice for the different FV markets in Malaysia. Based on the finding of the research, Malaysian retailers have different marketing strategies to be considered with regards to loyalty drivers.

  5. Assessment Of Ethical Behavior Among Professionals At Procurement And After Tendering Process With Its Impacts And Drivers In Nepalese Construction Industry

    Directory of Open Access Journals (Sweden)

    Ram Sagar Yadav

    2015-08-01

    Full Text Available Objective of this study is to assess ethical behavior among professionals at procurement and after tendering process with its impacts and drivers in Nepalese Construction Industry. Different literatures were reviewed to assess ethical practices along with its cause and effect inside Nepalese Construction Industry. Pilot study was conducted for the validity of the questionnaire. One key informant from each selected organization was interviewed. The questionnaire contains shortcomings of ethical behavior at procurement and after tendering phase impact of shortcomings of ethical practices and factors leading to these ethical practices based on the objectives of the research. Five ranking Likert Scale were used. The collected data were analyzed based on relative importance index RII in three different categories as Investigating Offices 3 numbers Professional Associations 4 numbers and Government Departments 4 numbers with total of 11 organizations. All together 240 respondents were targeted out of which 170 response were collected with response rate of 70.83. The research shows that for commitment of professionals The overall level of unethical conduct in construction industry is placed at first rank with agreement level of 72.7. For Professionals shortcomings of ethical behavior at procurement phase Individuals or organizations undertaking work without adequate qualification experience training is placed at first rank with agreement level of 68.00. For Professionals shortcomings of ethical behavior after awarding the Tender Contractors professional dont dispose waste in suitable and safe ways which is friendly with the environment is placed at first rank with agreement level of 67.50. For factors lead to shortcomings of ethical behavior Personal culture or personal behavior is placed at first rank with agreement level of 78.20. From the research it is clear that shortcomings of ethical behaviors have negative impact firstly on cost as it affects

  6. Driver style and driver skills – clustering drivers differing in their potential danger in traffic

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Møller, Mette; Prato, Carlo Giacomo

    The Driver Behavior Questionnaire (DBQ) and the Driver Skill Inventory (DSI) are two of the most frequently used measures of driving style and driving skill. The motivation behind the present study was to test drivers’ insight into their own driving ability based on a combined use of the DBQ......, annual mileage and accident involvement. 3908 drivers aged 18–84 participated in the survey. The results suggested that the drivers have good insight into their own driving ability, as the driving skill level mirrored the frequency of aberrant driving behaviors. K-means cluster analysis revealed four...... distinct clusters that differed in the frequency of aberrant driving behavior and driving skills, as well as individual characteristics and driving related factors such as annual mileage, accident frequency and number of tickets and fines. Thus, two sub-groups were identified as more unsafe than the two...

  7. Modeling Adaptive Behavior for Systems Design

    DEFF Research Database (Denmark)

    Rasmussen, Jens

    1994-01-01

    Field studies in modern work systems and analysis of recent major accidents have pointed to a need for better models of the adaptive behavior of individuals and organizations operating in a dynamic and highly competitive environment. The paper presents a discussion of some key characteristics.......) The basic difference between the models of system functions used in engineering and design and those evolving from basic research within the various academic disciplines and finally 3.) The models and methods required for closed-loop, feedback system design....

  8. The impact of threat appeals on fear arousal and driver behavior: a meta-analysis of experimental research 1990-2011.

    Science.gov (United States)

    Carey, Rachel N; McDermott, Daragh T; Sarma, Kiran M

    2013-01-01

    The existing empirical research exploring the impact of threat appeals on driver behavior has reported inconsistent findings. In an effort to provide an up-to-date synthesis of the experimental findings, meta-analytic techniques were employed to examine the impact of threat-based messages on fear arousal and on lab-based indices of driving behavior. Experimental studies (k = 13, N = 3044), conducted between 1990 and 2011, were included in the analyses. The aims of the current analysis were (a) to examine whether or not the experimental manipulations had a significant impact on evoked fear, (b) to examine the impact of threat appeals on three distinct indices of driving, and (c) to identify moderators and mediators of the relationship between fear and driving outcomes. Large effects emerged for the level of fear evoked, with experimental groups reporting increased fear arousal in comparison to control groups (r = .64, n = 619, pappeals on driving outcomes, however, was not significant (r = .03, p = .17). This analysis of the experimental literature indicates that threat appeals can lead to increased fear arousal, but do not appear to have the desired impact on driving behavior. We discuss these findings in the context of threat-based road safety campaigns and future directions for experimental research in this area.

  9. The Impact of Threat Appeals on Fear Arousal and Driver Behavior: A Meta-Analysis of Experimental Research 1990–2011

    Science.gov (United States)

    Carey, Rachel N.; McDermott, Daragh T.; Sarma, Kiran M.

    2013-01-01

    The existing empirical research exploring the impact of threat appeals on driver behavior has reported inconsistent findings. In an effort to provide an up-to-date synthesis of the experimental findings, meta-analytic techniques were employed to examine the impact of threat-based messages on fear arousal and on lab-based indices of driving behavior. Experimental studies (k = 13, N = 3044), conducted between 1990 and 2011, were included in the analyses. The aims of the current analysis were (a) to examine whether or not the experimental manipulations had a significant impact on evoked fear, (b) to examine the impact of threat appeals on three distinct indices of driving, and (c) to identify moderators and mediators of the relationship between fear and driving outcomes. Large effects emerged for the level of fear evoked, with experimental groups reporting increased fear arousal in comparison to control groups (r = .64, n = 619, pappeals on driving outcomes, however, was not significant (r = .03, p = .17). This analysis of the experimental literature indicates that threat appeals can lead to increased fear arousal, but do not appear to have the desired impact on driving behavior. We discuss these findings in the context of threat-based road safety campaigns and future directions for experimental research in this area. PMID:23690955

  10. The impact of threat appeals on fear arousal and driver behavior: a meta-analysis of experimental research 1990-2011.

    Directory of Open Access Journals (Sweden)

    Rachel N Carey

    Full Text Available The existing empirical research exploring the impact of threat appeals on driver behavior has reported inconsistent findings. In an effort to provide an up-to-date synthesis of the experimental findings, meta-analytic techniques were employed to examine the impact of threat-based messages on fear arousal and on lab-based indices of driving behavior. Experimental studies (k = 13, N = 3044, conducted between 1990 and 2011, were included in the analyses. The aims of the current analysis were (a to examine whether or not the experimental manipulations had a significant impact on evoked fear, (b to examine the impact of threat appeals on three distinct indices of driving, and (c to identify moderators and mediators of the relationship between fear and driving outcomes. Large effects emerged for the level of fear evoked, with experimental groups reporting increased fear arousal in comparison to control groups (r = .64, n = 619, p<.01. The effect of threat appeals on driving outcomes, however, was not significant (r = .03, p = .17. This analysis of the experimental literature indicates that threat appeals can lead to increased fear arousal, but do not appear to have the desired impact on driving behavior. We discuss these findings in the context of threat-based road safety campaigns and future directions for experimental research in this area.

  11. Rational-driver approximation in car-following theory

    Science.gov (United States)

    Lubashevsky, Ihor; Wagner, Peter; Mahnke, Reinhard

    2003-11-01

    The problem of a car following a lead car driven with constant velocity is considered. To derive the governing equations for the following car dynamics a cost functional is constructed. This functional ranks the outcomes of different driving strategies, which applies to fairly general properties of the driver behavior. Assuming rational-driver behavior, the existence of the Nash equilibrium is proved. Rational driving is defined by supposing that a driver corrects continuously the car motion to follow the optimal path minimizing the cost functional. The corresponding car-following dynamics is described quite generally by a boundary value problem based on the obtained extremal equations. Linearization of these equations around the stationary state results in a generalization of the widely used optimal velocity model. Under certain conditions (the “dense traffic” limit) the rational car dynamics comprises two stages, fast and slow. During the fast stage a driver eliminates the velocity difference between the cars, the subsequent slow stage optimizes the headway. In the dense traffic limit an effective Hamiltonian description is constructed. This allows a more detailed nonlinear analysis. Finally, the differences between rational and bounded rational driver behavior are discussed. The latter, in particular, justifies some basic assumptions used recently by the authors to construct a car-following model lying beyond the frameworks of rationality.

  12. Human Guidance Behavior Decomposition and Modeling

    Science.gov (United States)

    Feit, Andrew James

    Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

  13. Feasibility of a computer-delivered driver safety behavior screening and intervention program initiated during an emergency department visit.

    Science.gov (United States)

    Murphy, Mary; Smith, Lucia; Palma, Anton; Lounsbury, David; Bijur, Polly; Chambers, Paul; Gallagher, E John

    2013-01-01

    Injuries from motor vehicle crashes are a significant public health problem. The emergency department (ED) provides a setting that may be used to screen for behaviors that increase risk for motor vehicle crashes and provide brief interventions to people who might otherwise not have access to screening and intervention. The purpose of the present study was to (1) assess the feasibility of using a computer-assisted screening program to educate ED patients about risky driving behaviors, (2) evaluate patient acceptance of the computer-based traffic safety educational intervention during an ED visit, and (3) assess postintervention changes in risky driving behaviors. Pre/posteducational intervention involving medically stable adult ED patients in a large urban academic ED serving over 100,000 patients annually. Patients completed a self-administered, computer-based program that queried patients on risky driving behaviors (texting, talking, and other forms of distracted driving) and alcohol use. The computer provided patients with educational information on the dangers of these behaviors and data were collected on patient satisfaction with the program. Staff called patients 1 month post-ED visit for a repeat query. One hundred forty-nine patients participated, and 111 completed 1-month follow up (75%); the mean age was 39 (range: 21-70), 59 percent were Hispanic, and 52 percent were male. Ninety-seven percent of patients reported that the program was easy to use and that they were comfortable receiving this education via computer during their ED visit. All driving behaviors significantly decreased in comparison to baseline with the following reductions reported: talking on the phone, 30 percent; aggressive driving, 30 percent; texting while driving, 19 percent; drowsy driving, 16 percent; driving while multitasking, 12 percent; and drinking and driving, 9 percent. Overall, patients were very satisfied receiving educational information about these behaviors via computer

  14. Somatic drivers of B-ALL in a model of ETV6-RUNX1; Pax5+/− leukemia

    International Nuclear Information System (INIS)

    Weyden, Louise van der; Giotopoulos, George; Wong, Kim; Rust, Alistair G.; Robles-Espinoza, Carla Daniela; Osaki, Hikari; Huntly, Brian J.; Adams, David J.

    2015-01-01

    B-cell precursor acute lymphoblastic leukemia (B-ALL) is amongst the leading causes of childhood cancer-related mortality. Its most common chromosomal aberration is the ETV6-RUNX1 fusion gene, with ~25 % of ETV6-RUNX1 patients also carrying PAX5 alterations. We have recreated this mutation background by inter-crossing Etv6-RUNX1 (Etv6 RUNX1-SB ) and Pax5 +/− mice and performed an in vivo analysis to find driver genes using Sleeping Beauty transposon-mediated mutagenesis and also exome sequencing. Combination of Etv6-RUNX1 and Pax5 +/− alleles generated a transplantable B220 + CD19+ B-ALL with a significant disease incidence. RNA-seq analysis showed a gene expression pattern consistent with arrest at the pre-B stage. Analysis of the transposon common insertion sites identified genes involved in B-cell development (Zfp423) and the JAK/STAT signaling pathway (Jak1, Stat5 and Il2rb), while exome sequencing revealed somatic hotspot mutations in Jak1 and Jak3 at residues analogous to those mutated in human leukemias, and also mutation of Trp53. Powerful synergies exists in our model suggesting STAT pathway activation and mutation of Trp53 are potent drivers of B-ALL in the context of Etv6-RUNX1;Pax5 +/− . The online version of this article (doi:10.1186/s12885-015-1586-1) contains supplementary material, which is available to authorized users

  15. Aids to determining fuel models for estimating fire behavior

    Science.gov (United States)

    Hal E. Anderson

    1982-01-01

    Presents photographs of wildland vegetation appropriate for the 13 fuel models used in mathematical models of fire behavior. Fuel model descriptions include fire behavior associated with each fuel and its physical characteristics. A similarity chart cross-references the 13 fire behavior fuel models to the 20 fuel models used in the National Fire Danger Rating System....

  16. Low-complexity Behavioral Model for Predictive Maintenance of Railway Turnouts

    DEFF Research Database (Denmark)

    Barkhordari, Pegah; Galeazzi, Roberto; Tejada, Alejandro de Miguel

    2017-01-01

    together with the Eigensystem Realization Algorithm – a type of subspace identification – to identify a fourth order model of the infrastructure. The robustness and predictive capability of the low-complexity behavioral model to reproduce track responses under different types of train excitations have been......Maintenance of railway infrastructures represents a major cost driver for any infrastructure manager since reliability and dependability must be guaranteed at all times. Implementation of predictive maintenance policies relies on the availability of condition monitoring systems able to assess...... the infrastructure health state. The core of any condition monitoring system is the a-priori knowledge about the process to be monitored, in the form of either mathematical models of different complexity or signal features characterizing the healthy/faulty behavior. This study investigates the identification...

  17. Empirical Behavioral Models to Support Alternative Tools for the Analysis of Mixed-Priority Pedestrian-Vehicle Interaction in a Highway Capacity Context

    Science.gov (United States)

    Rouphail, Nagui M.

    2011-01-01

    This paper presents behavioral-based models for describing pedestrian gap acceptance at unsignalized crosswalks in a mixed-priority environment, where some drivers yield and some pedestrians cross in gaps. Logistic regression models are developed to predict the probability of pedestrian crossings as a function of vehicle dynamics, pedestrian assertiveness, and other factors. In combination with prior work on probabilistic yielding models, the results can be incorporated in a simulation environment, where they can more fully describe the interaction of these two modes. The approach is intended to supplement HCM analytical procedure for locations where significant interaction occurs between drivers and pedestrians, including modern roundabouts. PMID:21643488

  18. Work Environment, Stress, and Driving Anger: A Structural Equation Model for Predicting Traffic Sanctions of Public Transport Drivers

    Science.gov (United States)

    2018-01-01

    Public transport is an effective and sustainable alternative to private vehicle usage, also helping to reduce the environmental impact of driving. However, the work environment of public transport operators is full of adverse conditions, which, together with their high mileage, may increase the occurrence of negative safety outcomes such as traffic accidents, often preceded by risky road behaviors enhanced by stress, anger, and difficult operating conditions. The aims of this study were, first, to determine the association between work-related psychosocial factors and individual characteristics of public transport drivers and the rate of traffic sanctions they are subject to; and second, to assess the mediation of driving anger in this relationship. A sample of professional drivers (57.4% city bus, 17.6% taxi, and 25% inter-urban bus male operators) was used for this cross-sectional study, responding to a five-section survey including demographic data and driving-related factors, psychosocial work factors including job stress, driving stress, risk predisposition, and driving anger. The results of this study showed significant associations between work-related factors: measures of stress and self-reported rates of traffic fines. Second, it was found that driving anger mediates the associations between driving stress, risk predisposition, and traffic sanctions; and partially mediates the association between driving experience, hourly intensity, and job stress. This study supports the idea that traffic penalties reported by public transport rates are preceded by work-related, personality, and other individual factors that, when combined with driving anger, enhance the occurrence of road misbehavior that may affect overall road safety. PMID:29534530

  19. Work Environment, Stress, and Driving Anger: A Structural Equation Model for Predicting Traffic Sanctions of Public Transport Drivers

    Directory of Open Access Journals (Sweden)

    Luis Montoro

    2018-03-01

    Full Text Available Public transport is an effective and sustainable alternative to private vehicle usage, also helping to reduce the environmental impact of driving. However, the work environment of public transport operators is full of adverse conditions, which, together with their high mileage, may increase the occurrence of negative safety outcomes such as traffic accidents, often preceded by risky road behaviors enhanced by stress, anger, and difficult operating conditions. The aims of this study were, first, to determine the association between work-related psychosocial factors and individual characteristics of public transport drivers and the rate of traffic sanctions they are subject to; and second, to assess the mediation of driving anger in this relationship. A sample of professional drivers (57.4% city bus, 17.6% taxi, and 25% inter-urban bus male operators was used for this cross-sectional study, responding to a five-section survey including demographic data and driving-related factors, psychosocial work factors including job stress, driving stress, risk predisposition, and driving anger. The results of this study showed significant associations between work-related factors: measures of stress and self-reported rates of traffic fines. Second, it was found that driving anger mediates the associations between driving stress, risk predisposition, and traffic sanctions; and partially mediates the association between driving experience, hourly intensity, and job stress. This study supports the idea that traffic penalties reported by public transport rates are preceded by work-related, personality, and other individual factors that, when combined with driving anger, enhance the occurrence of road misbehavior that may affect overall road safety.

  20. Work Environment, Stress, and Driving Anger: A Structural Equation Model for Predicting Traffic Sanctions of Public Transport Drivers.

    Science.gov (United States)

    Montoro, Luis; Useche, Sergio; Alonso, Francisco; Cendales, Boris

    2018-03-12

    Public transport is an effective and sustainable alternative to private vehicle usage, also helping to reduce the environmental impact of driving. However, the work environment of public transport operators is full of adverse conditions, which, together with their high mileage, may increase the occurrence of negative safety outcomes such as traffic accidents, often preceded by risky road behaviors enhanced by stress, anger, and difficult operating conditions. The aims of this study were, first, to determine the association between work-related psychosocial factors and individual characteristics of public transport drivers and the rate of traffic sanctions they are subject to; and second, to assess the mediation of driving anger in this relationship. A sample of professional drivers (57.4% city bus, 17.6% taxi, and 25% inter-urban bus male operators) was used for this cross-sectional study, responding to a five-section survey including demographic data and driving-related factors, psychosocial work factors including job stress, driving stress, risk predisposition, and driving anger. The results of this study showed significant associations between work-related factors: measures of stress and self-reported rates of traffic fines. Second, it was found that driving anger mediates the associations between driving stress, risk predisposition, and traffic sanctions; and partially mediates the association between driving experience, hourly intensity, and job stress. This study supports the idea that traffic penalties reported by public transport rates are preceded by work-related, personality, and other individual factors that, when combined with driving anger, enhance the occurrence of road misbehavior that may affect overall road safety.

  1. Behavior genetic modeling of human fertility

    DEFF Research Database (Denmark)

    Rodgers, J L; Kohler, H P; Kyvik, K O

    2001-01-01

    Behavior genetic designs and analysis can be used to address issues of central importance to demography. We use this methodology to document genetic influence on human fertility. Our data come from Danish twin pairs born from 1953 to 1959, measured on age at first attempt to get pregnant (First......Try) and number of children (NumCh). Behavior genetic models were fitted using structural equation modeling and DF analysis. A consistent medium-level additive genetic influence was found for NumCh, equal across genders; a stronger genetic influence was identified for FirstTry, greater for females than for males....... A bivariate analysis indicated significant shared genetic variance between NumCh and FirstTry....

  2. The Effectiveness of “Improvement of Driver-Behavior Program” on Self-Control of Individuals Whose Driving Licenses Have Been Seized due to Drinking and Driving.

    Directory of Open Access Journals (Sweden)

    Ýbrahim Taymur

    2014-12-01

    Conclusion: We conclude that the quality of “Driver-Behavior Improvement Program” should be enhanced by extending the duration of the education and addressing the age factor in improving self-control features of the relevant individuals. [JCBPR 2014; 3(3.000: 182-190

  3. Behavioral Reference Model for Pervasive Healthcare Systems.

    Science.gov (United States)

    Tahmasbi, Arezoo; Adabi, Sahar; Rezaee, Ali

    2016-12-01

    The emergence of mobile healthcare systems is an important outcome of application of pervasive computing concepts for medical care purposes. These systems provide the facilities and infrastructure required for automatic and ubiquitous sharing of medical information. Healthcare systems have a dynamic structure and configuration, therefore having an architecture is essential for future development of these systems. The need for increased response rate, problem limited storage, accelerated processing and etc. the tendency toward creating a new generation of healthcare system architecture highlight the need for further focus on cloud-based solutions for transfer data and data processing challenges. Integrity and reliability of healthcare systems are of critical importance, as even the slightest error may put the patients' lives in danger; therefore acquiring a behavioral model for these systems and developing the tools required to model their behaviors are of significant importance. The high-level designs may contain some flaws, therefor the system must be fully examined for different scenarios and conditions. This paper presents a software architecture for development of healthcare systems based on pervasive computing concepts, and then models the behavior of described system. A set of solutions are then proposed to improve the design's qualitative characteristics including, availability, interoperability and performance.

  4. Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses

    International Nuclear Information System (INIS)

    Li, Liang; You, Sixiong; Yang, Chao; Yan, Bingjie; Song, Jian; Chen, Zheng

    2016-01-01

    Highlights: • The novel approximated global optimal energy management strategy has been proposed for hybrid powertrains. • Eight typical driving behaviors have been classified with K-means to deal with the multiplicative traffic conditions. • The stochastic driver models of different driving behaviors were established based on the Markov chains. • ECMS was used to modify the SMPC-based energy management strategy to improve its fuel economy. • The approximated global optimal energy management strategy for plug-in hybrid electric buses has been verified and analyzed. - Abstract: Driving cycles of a city bus is statistically characterized by some repetitive features, which makes the predictive energy management strategy very desirable to obtain approximate optimal fuel economy of a plug-in hybrid electric bus. But dealing with the complicated traffic conditions and finding an approximated global optimal strategy which is applicable to the plug-in hybrid electric bus still remains a challenging technique. To solve this problem, a novel driving-behavior-aware modified stochastic model predictive control method is proposed for the plug-in hybrid electric bus. Firstly, the K-means is employed to classify driving behaviors, and the driver models based on Markov chains is obtained under different kinds of driving behaviors. While the obtained driver behaviors are regarded as stochastic disturbance inputs, the local minimum fuel consumption might be obtained with a traditional stochastic model predictive control at each step, taking tracking the reference battery state of charge trajectory into consideration in the finite predictive horizons. However, this technique is still accompanied by some working points with reduced/worsened fuel economy. Thus, the stochastic model predictive control is modified with the equivalent consumption minimization strategy to eliminate these undesirable working points. The results in real-world city bus routines show that the

  5. Modelling drivers and distribution of lead and zinc concentrations in soils of an urban catchment (Sydney estuary, Australia).

    Science.gov (United States)

    Johnson, L E; Bishop, T F A; Birch, G F

    2017-11-15

    The human population is increasing globally and land use is changing to accommodate for this growth. Soils within urban areas require closer attention as the higher population density increases the chance of human exposure to urban contaminants. One such example of an urban area undergoing an increase in population density is Sydney, Australia. The city also possesses a notable history of intense industrial activity. By integrating multiple soil surveys and covariates into a linear mixed model, it was possible to determine the main drivers and map the distribution of lead and zinc concentrations within the Sydney estuary catchment. The main drivers as derived from the model included elevation, distance to main roads, main road type, soil landscape, population density (lead only) and land use (zinc only). Lead concentrations predicted using the model exceeded the established guideline value of 300mgkg -1 over a large portion of the study area with concentrations exceeding 1000mgkg -1 in the south of the catchment. Predicted zinc did not exceed the established guideline value of 7400mgkg -1 ; however concentrations were higher to the south and west of the study area. Unlike many other studies we considered the prediction uncertainty when assessing the contamination risk. Although the predictions indicate contamination over a large area, the broadness of the prediction intervals suggests that in many of these areas we cannot be sure that the site is contaminated. More samples are required to determine the contaminant distribution with greater precision, especially in residential areas where contamination was highest. Managing sources and addressing areas of elevated lead and zinc concentrations in urban areas has the potential to reduce the impact of past human activities and improve the urban environment of the future. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Agent-based modeling of sustainable behaviors

    CERN Document Server

    Sánchez-Maroño, Noelia; Fontenla-Romero, Oscar; Polhill, J; Craig, Tony; Bajo, Javier; Corchado, Juan

    2017-01-01

    Using the O.D.D. (Overview, Design concepts, Detail) protocol, this title explores the role of agent-based modeling in predicting the feasibility of various approaches to sustainability. The chapters incorporated in this volume consist of real case studies to illustrate the utility of agent-based modeling and complexity theory in discovering a path to more efficient and sustainable lifestyles. The topics covered within include: households' attitudes toward recycling, designing decision trees for representing sustainable behaviors, negotiation-based parking allocation, auction-based traffic signal control, and others. This selection of papers will be of interest to social scientists who wish to learn more about agent-based modeling as well as experts in the field of agent-based modeling.

  7. Mob control models of threshold collective behavior

    CERN Document Server

    Breer, Vladimir V; Rogatkin, Andrey D

    2017-01-01

    This book presents mathematical models of mob control with threshold (conformity) collective decision-making of the agents. Based on the results of analysis of the interconnection between the micro- and macromodels of active network structures, it considers the static (deterministic, stochastic and game-theoretic) and dynamic (discrete- and continuous-time) models of mob control, and highlights models of informational confrontation. Many of the results are applicable not only to mob control problems, but also to control problems arising in social groups, online social networks, etc. Aimed at researchers and practitioners, it is also a valuable resource for undergraduate and postgraduate students as well as doctoral candidates specializing in the field of collective behavior modeling.

  8. Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

    Science.gov (United States)

    Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

    2017-11-01

    Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

  9. Investigating the influence of working memory capacity when driving behavior is combined with cognitive load: An LCT study of young novice drivers.

    Science.gov (United States)

    Ross, Veerle; Jongen, Ellen M M; Wang, Weixin; Brijs, Tom; Brijs, Kris; Ruiter, Robert A C; Wets, Geert

    2014-01-01

    Distracted driving has received increasing attention in the literature due to potential adverse safety outcomes. An often posed solution to alleviate distraction while driving is hands-free technology. Interference by distraction can occur however at the sensory input (e.g., visual) level, but also at the cognitive level where hands-free technology induces working memory (WM) load. Active maintenance of goal-directed behavior in the presence of distraction depends on WM capacity (i.e., Lavie's Load theory) which implies that people with higher WM capacity are less susceptible to distractor interference. This study investigated the interaction between verbal WM load and WM capacity on driving performance to determine whether individuals with higher WM capacity were less affected by verbal WM load, leading to a smaller deterioration of driving performance. Driving performance of 46 young novice drivers (17-25 years-old) was measured with the lane change task (LCT). Participants drove without and with verbal WM load of increasing complexity (auditory-verbal response N-back task). Both visuospatial and verbal WM capacity were investigated. Dependent measures were mean deviation in the lane change path (MDEV), lane change initiation (LCI) and percentage of correct lane changes (PCL). Driving experience was included as a covariate. Performance on each dependent measure deteriorated with increasing verbal WM load. Meanwhile, higher WM capacity related to better LCT performance. Finally, for LCI and PCL, participants with higher verbal WM capacity were influenced less by verbal WM load. These findings entail that completely eliminating distraction is necessary to minimize crash risks among young novice drivers. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Modelling how drivers respond to a bicyclist crossing their path at an intersection: How do test track and driving simulator compare?

    Science.gov (United States)

    Boda, Christian-Nils; Dozza, Marco; Bohman, Katarina; Thalya, Prateek; Larsson, Annika; Lubbe, Nils

    2018-02-01

    Bicyclist fatalities are a great concern in the European Union. Most of them are due to crashes between motorized vehicles and bicyclists at unsignalised intersections. Different countermeasures are currently being developed and implemented in order to save lives. One type of countermeasure, active safety systems, requires a deep understanding of driver behaviour to be effective without being annoying. The current study provides new knowledge about driver behaviour which can inform assessment programmes for active safety systems such as Euro NCAP. This study investigated how drivers responded to bicyclists crossing their path at an intersection. The influences of car speed and cyclist speed on the driver response process were assessed for three different crossing configurations. The same experimental protocol was tested in a fixed-base driving simulator and on a test track. A virtual model of the test track was used in the driving simulator to keep the protocol as consistent as possible across testing environments. Results show that neither car speed nor bicycle speed directly influenced the response process. The crossing configuration did not directly influence the braking response process either, but it did influence the strategy chosen by the drivers to approach the intersection. The point in time when the bicycle became visible (which depended on the car speed, the bicycle speed, and the crossing configuration) and the crossing configuration alone had the largest effects on the driver response process. Dissimilarities between test-track and driving-simulator studies were found; however, there were also interesting similarities, especially in relation to the driver braking behaviour. Drivers followed the same strategy to initiate braking, independent of the test environment. On the other hand, the test environment affected participants' strategies for releasing the gas pedal and regulating deceleration. Finally, a mathematical model, based on both experiments

  11. VOTERS DECIDE. CLASSICAL MODELS OF ELECTORAL BEHAVIOR.

    Directory of Open Access Journals (Sweden)

    Constantin SASU

    2015-04-01

    Full Text Available The decision to vote and choosing among the candidates is a extremely important one with repercussions on everyday life by determining, in global mode, its quality for the whole society. Therefore the whole process by which the voter decide becomes a central concern. In this paper we intend to locate the determinants of the vote decision in the electoral behavior classical theoretical models developed over time. After doing synthesis of classical schools of thought on electoral behavior we conclude that it has been made a journey through the mind, soul and cheek, as follows: the mind as reason in theory developed by Downs, soul as preferably for an actor in Campbell's theory, etc. and cheek as an expression of the impossibility of detachment from social groups to which we belong in Lazarsfeld's theory.

  12. Modeling Individual Cyclic Variation in Human Behavior.

    Science.gov (United States)

    Pierson, Emma; Althoff, Tim; Leskovec, Jure

    2018-04-01

    Cycles are fundamental to human health and behavior. Examples include mood cycles, circadian rhythms, and the menstrual cycle. However, modeling cycles in time series data is challenging because in most cases the cycles are not labeled or directly observed and need to be inferred from multidimensional measurements taken over time. Here, we present Cyclic Hidden Markov Models (CyH-MMs) for detecting and modeling cycles in a collection of multidimensional heterogeneous time series data. In contrast to previous cycle modeling methods, CyHMMs deal with a number of challenges encountered in modeling real-world cycles: they can model multivariate data with both discrete and continuous dimensions; they explicitly model and are robust to missing data; and they can share information across individuals to accommodate variation both within and between individual time series. Experiments on synthetic and real-world health-tracking data demonstrate that CyHMMs infer cycle lengths more accurately than existing methods, with 58% lower error on simulated data and 63% lower error on real-world data compared to the best-performing baseline. CyHMMs can also perform functions which baselines cannot: they can model the progression of individual features/symptoms over the course of the cycle, identify the most variable features, and cluster individual time series into groups with distinct characteristics. Applying CyHMMs to two real-world health-tracking datasets-of human menstrual cycle symptoms and physical activity tracking data-yields important insights including which symptoms to expect at each point during the cycle. We also find that people fall into several groups with distinct cycle patterns, and that these groups differ along dimensions not provided to the model. For example, by modeling missing data in the menstrual cycles dataset, we are able to discover a medically relevant group of birth control users even though information on birth control is not given to the model.

  13. Traffic Games: Modeling Freeway Traffic with Game Theory.

    Science.gov (United States)

    Cortés-Berrueco, Luis E; Gershenson, Carlos; Stephens, Christopher R

    2016-01-01

    We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers' interactions.

  14. Modeling Pseudo-elastic Behavior of Springback

    International Nuclear Information System (INIS)

    Xia, Z. Cedric

    2005-01-01

    One of the principal foundations of mathematical theory of conventional plasticity for rate-independent metals is that there exists a well-defined yield surface in stress space for any material point under deformation. A material point can undergo further plastic deformation if the applied stresses are beyond current yield surface which is generally referred as 'plastic loading'. On the other hand, if the applied stress state falls within or on the yield surface, the metal will deform elastically only and is said to be undergoing 'elastic unloading'. Although it has been always recognized throughout the history of development of plasticity theory that there is indeed inelastic deformation accompanying elastic unloading, which leads to metal's hysteresis behavior, its effects were thought to be negligible and were largely ignored in the mathematical treatment.Recently there have been renewed interests in the study of unloading behavior of sheet metals upon large plastic deformation and its implications on springback prediction. Springback is essentially an elastic recovery process of a formed sheet metal blank when it is released from the forming dies. Its magnitude depends on the stress states and compliances of the deformed sheet metal if no further plastic loading occurs during the relaxation process. Therefore the accurate determination of material compliances during springback and its effective incorporation into simulation software are important aspects for springback calculation. Some of the studies suggest that the unloading curve might deviate from linearity, and suggestions were made that a reduced elastic modulus be used for springback simulation.The aim of this study is NOT to take a position on the debate of whether elastic moduli are changed during sheet metal forming process. Instead we propose an approach of modeling observed psuedoelastic behavior within the context of mathematical theory of plasticity, where elastic moduli are treated to be

  15. Modeling plug-in electric vehicle charging demand with BEAM: the framework for behavior energy autonomy mobility

    Energy Technology Data Exchange (ETDEWEB)

    Sheppard, Colin; Waraich, Rashid; Campbell, Andrew; Pozdnukov, Alexei; Gopal, Anand R.

    2017-05-01

    This report summarizes the BEAM modeling framework (Behavior, Energy, Mobility, and Autonomy) and its application to simulating plug-in electric vehicle (PEV) mobility, energy consumption, and spatiotemporal charging demand. BEAM is an agent-based model of PEV mobility and charging behavior designed as an extension to MATSim (the Multi-Agent Transportation Simulation model). We apply BEAM to the San Francisco Bay Area and conduct a preliminary calibration and validation of its prediction of charging load based on observed charging infrastructure utilization for the region in 2016. We then explore the impact of a variety of common modeling assumptions in the literature regarding charging infrastructure availability and driver behavior. We find that accurately reproducing observed charging patterns requires an explicit representation of spatially disaggregated charging infrastructure as well as a more nuanced model of the decision to charge that balances tradeoffs people make with regards to time, cost, convenience, and range anxiety.

  16. Analysis of Food Hub Commerce and Participation Using Agent-Based Modeling: Integrating Financial and Social Drivers.

    Science.gov (United States)

    Krejci, Caroline C; Stone, Richard T; Dorneich, Michael C; Gilbert, Stephen B

    2016-02-01

    Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants. Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models. Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on traditional economic assumptions. Further simulation studies assessed the effect of changes in parameters, such as producer reliability and the consumer profiles, on long-term food hub sustainability. The persona-based ABM model produced different and more resilient results than the more traditional way of modeling consumers. Reduced producer reliability significantly reduced trade; in some instances, a modest reduction in reliability threatened the sustainability of the system. Finally, a modest increase in price-driven consumers at the outset of the simulation quickly resulted in those consumers becoming a majority of the overall customer base. Results suggest that social factors, such as desire to support the community, can be more important than financial factors. An ABM of food hub dynamics, based on human factors data gathered from the field, can be a useful tool for policy decisions. Similar approaches can be used for modeling customer dynamics with other sustainable organizations. © 2015, Human Factors and Ergonomics Society.

  17. Driver style and driver skill – Clustering sub-groups of drivers differing in their potential danger in traffic

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Møller, Mette; Prato, Carlo Giacomo

    The Driver Behavior Questionnaire (DBQ) and the Driver Skill Inventory (DSI) are two of the most frequently used measures of self-reported driving style and driving skill. The motivation behind the present study was to test drivers’ consistency or judgment of their own self-reported driving ability...... based on a combined use of the DBQ and the DSI. Moreover, the joint use of the two instruments was applied to identify sub-groups of drivers that differ in their potential danger in traffic (as measured by frequency of aberrant driving behaviors and level of driving skills), as well as to test whether...... the sub-groups of drivers differed in characteristics such as age, gender, annual mileage and accident involvement. 3908 drivers aged 18–84 participated in the survey. The results suggested that the drivers are consistent in their reporting of driving ability, as the self-reported driving skill level...

  18. Behavioral optimization models for multicriteria portfolio selection

    Directory of Open Access Journals (Sweden)

    Mehlawat Mukesh Kumar

    2013-01-01

    Full Text Available In this paper, behavioral construct of suitability is used to develop a multicriteria decision making framework for portfolio selection. To achieve this purpose, we rely on multiple methodologies. Analytical hierarchy process technique is used to model the suitability considerations with a view to obtaining the suitability performance score in respect of each asset. A fuzzy multiple criteria decision making method is used to obtain the financial quality score of each asset based upon investor's rating on the financial criteria. Two optimization models are developed for optimal asset allocation considering simultaneously financial and suitability criteria. An empirical study is conducted on randomly selected assets from National Stock Exchange, Mumbai, India to demonstrate the effectiveness of the proposed methodology.

  19. Generalized Penner models and multicritical behavior

    International Nuclear Information System (INIS)

    Tan, C.

    1992-01-01

    In this paper, we are interested in the critical behavior of generalized Penner models at t∼-1+μ/N where the topological expansion for the free energy develops logarithmic singularities: Γ∼-(χ 0 μ 2 lnμ+χ 1 lnμ+...). We demonstrate that these criticalities can best be characterized by the fact that the large-N generating function becomes meromorphic with a single pole term of unit residue, F(z)→1/(z-a), where a is the location of the ''sink.'' For a one-band eigenvalue distribution, we identify multicritical potentials; we find that none of these can be associated with the c=1 string compactified at an integral multiple of the self-dual radius. We also give an exact solution to the Gaussian Penner model and explicitly demonstrate that, at criticality, this solution does not correspond to a c=1 string compactified at twice the self-dual radius

  20. MINI-TRAC code: a driver program for assessment of constitutive equations of two-fluid model

    International Nuclear Information System (INIS)

    Akimoto, Hajime; Abe, Yutaka; Ohnuki, Akira; Murao, Yoshio

    1991-05-01

    MINI-TRAC code, a driver program for assessment of constitutive equations of two-fluid model, has been developed to perform assessment and improvement of constitutive equations of two-fluid model widely and efficiently. The MINI-TRAC code uses one-dimensional conservation equations for mass, momentum and energy based on the two-fluid model. The code can work on a personal computer because it can be operated with a core memory size less than 640 KB. The MINI-TRAC code includes constitutive equations of TRAC-PF1/MOD1 code, TRAC-BF1 code and RELAP5/MOD2 code. The code is modulated so that one can easily change constitutive equations to perform a test calculation. This report is a manual of the MINI-TRAC code. The basic equations, numerics, constitutive, equations included in the MINI-TRAC code will be described. The user's manual such as input description will be presented. The program structure and contents of main variables will also be mentioned in this report. (author)

  1. Streamlined Modeling for Characterizing Spacecraft Anomalous Behavior

    Science.gov (United States)

    Klem, B.; Swann, D.

    2011-09-01

    Anomalous behavior of on-orbit spacecraft can often be detected using passive, remote sensors which measure electro-optical signatures that vary in time and spectral content. Analysts responsible for assessing spacecraft operational status and detecting detrimental anomalies using non-resolved imaging sensors are often presented with various sensing and identification issues. Modeling and measuring spacecraft self emission and reflected radiant intensity when the radiation patterns exhibit a time varying reflective glint superimposed on an underlying diffuse signal contribute to assessment of spacecraft behavior in two ways: (1) providing information on body component orientation and attitude; and, (2) detecting changes in surface material properties due to the space environment. Simple convex and cube-shaped spacecraft, designed to operate without protruding solar panel appendages, may require an enhanced level of preflight characterization to support interpretation of the various physical effects observed during on-orbit monitoring. This paper describes selected portions of the signature database generated using streamlined signature modeling and simulations of basic geometry shapes apparent to non-imaging sensors. With this database, summarization of key observable features for such shapes as spheres, cylinders, flat plates, cones, and cubes in specific spectral bands that include the visible, mid wave, and long wave infrared provide the analyst with input to the decision process algorithms contained in the overall sensing and identification architectures. The models typically utilize baseline materials such as Kapton, paints, aluminum surface end plates, and radiators, along with solar cell representations covering the cylindrical and side portions of the spacecraft. Multiple space and ground-based sensors are assumed to be located at key locations to describe the comprehensive multi-viewing aspect scenarios that can result in significant specular reflection

  2. Methodology to evaluate teen driver training programs : [brief].

    Science.gov (United States)

    2014-03-01

    In the United States, teenage drivers are more at risk of being involved in crashes than : any other age group. Statistics reveal a clear need for improving teenagers driving : skills, judgment and behavior. Driver education programs are a crucial...

  3. Using naturalistic driving study data to investigate the impact of driver distraction on driver's brake reaction time in freeway rear-end events in car-following situation.

    Science.gov (United States)

    Gao, Jingru; Davis, Gary A

    2017-12-01

    The rear-end crash is one of the most common freeway crash types, and driver distraction is often cited as a leading cause of rear-end crashes. Previous research indicates that driver distraction could have negative effects on driving performance, but the specific association between driver distraction and crash risk is still not fully revealed. This study sought to understand the mechanism by which driver distraction, defined as secondary task distraction, could influence crash risk, as indicated by a driver's reaction time, in freeway car-following situations. A statistical analysis, exploring the causal model structure regarding drivers' distraction impacts on reaction times, was conducted. Distraction duration, distraction scenario, and secondary task type were chosen as distraction-related factors. Besides, exogenous factors including weather, visual obstruction, lighting condition, traffic density, and intersection presence and endogenous factors including driver age and gender were considered. There was an association between driver distraction and reaction time in the sample freeway rear-end events from SHRP 2 NDS database. Distraction duration, the distracted status when a leader braked, and secondary task type were related to reaction time, while all other factors showed no significant effect on reaction time. The analysis showed that driver distraction duration is the primary direct cause of the increase in reaction time, with other factors having indirect effects mediated by distraction duration. Longer distraction duration, the distracted status when a leader braked, and engaging in auditory-visual-manual secondary task tended to result in longer reaction times. Given drivers will be distracted occasionally, countermeasures which shorten distraction duration or avoid distraction presence while a leader vehicle brakes are worth considering. This study helps better understand the mechanism of freeway rear-end events in car-following situations, and

  4. Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping.

    Science.gov (United States)

    Mitchell, Matthew G E; Johansen, Kasper; Maron, Martine; McAlpine, Clive A; Wu, Dan; Rhodes, Jonathan R

    2018-05-01

    Urban areas are sources of land use change and CO 2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha -1 calculated across the entire urban land area, and 110.9±19.7MgCha -1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km 2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Going one's own way: drivers in developing business models for sustainability

    NARCIS (Netherlands)

    Rauter, R.; Jonker, J.; Baumgartner, R.J.

    2017-01-01

    Business models have received much attention in recent years due to their importance in the fundamental logic of every company. This paper is based on a qualitative, empirical research study conducted in cooperation with 10 Austrian companies in 2014. It aims to investigate business models for

  6. Adapting forest management to climate change using bioclimate models with topographic drivers

    Science.gov (United States)

    Gerald E. Rehfeldt; James J. Worrall; Suzanne B. Marchetti; Nicholas L. Crookston

    2015-01-01

    Bioclimate models incorporating topographic predictors as surrogates for microclimate effects are developed for Populus tremuloides and Picea engelmannii to provide the fine-grained specificity to local terrain required for adapting management of three Colorado (USA) national forests (1.28 million ha) and their periphery to climate change. Models were built with the...

  7. Modeling and simulation of driver's anticipation effect in a two lane system on curved road with slope

    Science.gov (United States)

    Kaur, Ramanpreet; Sharma, Sapna

    2018-06-01

    The complexity of traffic flow phenomena on curved road with slope is investigated and a new lattice model is presented with the addition of driver's anticipation effect for two lane system. The condition under which the free flow turns into the jammed one, is obtained theoretically by using stability analysis. The results obtained through linear analysis indicates that the stable region increases (decreases) corresponding to uphill (downhill) case due to increasing slope angle for fixed anticipation parameter. It is found that when the vehicular density becomes higher than a critical value, traffic jam appears in the form of kink antikink density waves. Analytically, the kink antikink density waves are described by the solution of mKdV equation obtained from non linear analysis. In addition, the theoretical results has been verified through numerical simulation, which confirm that the slope on a curved highway significantly influence the traffic dynamics and traffic jam can be suppressed efficiently by considering the anticipation parameter in a two lane lattice model when lane changing is allowed.

  8. NACP MsTMIP: Global and North American Driver Data for Multi-Model Intercomparison

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides environmental data that have been standardized and aggregated for use as input to carbon cycle models at global (0.5-degree resolution) and...

  9. NACP MsTMIP: Global and North American Driver Data for Multi-Model Intercomparison

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides environmental data that have been standardized and aggregated for use as input to carbon cycle models at global (0.5-degree...

  10. Variations in Driver Behavior: An Analysis of Car-Following Behavior Heterogeneity as a Function of Road Type and Traffic Condition

    Science.gov (United States)

    2017-11-15

    Microsimulation modeling is a tool used by practitioners and researchers to predict and evaluate the flow of traffic on real transportation networks. These models are used in practice to inform decisions and thus must reflect a high level of accuracy...

  11. Do aggressive driving and negative emotional driving mediate the link between impulsiveness and risky driving among young Italian drivers?

    Science.gov (United States)

    Smorti, Martina; Guarnieri, Silvia

    2016-01-01

    The present study examined the contribution of impulsiveness and aggressive and negative emotional driving to the prediction of traffic violations and accidents taking into account potential mediation effects. Three hundred and four young drivers completed self-report measures assessing impulsiveness, aggressive and negative emotional driving, driving violations, and accidents. Structural equation modeling was used to assess the direct and indirect effects of impulsiveness on violations and accidents among young drivers through aggressive and negative emotional driving. Impulsiveness only indirectly influenced drivers' violations on the road via both the behavioral and emotional states of the driver. On the contrary, impulsiveness was neither directly nor indirectly associated with traffic accidents. Therefore, impulsiveness modulates young drivers' behavioral and emotional states while driving, which in turn influences risky driving.

  12. Swarming behavior of simple model squirmers

    International Nuclear Information System (INIS)

    Thutupalli, Shashi; Seemann, Ralf; Herminghaus, Stephan

    2011-01-01

    We have studied experimentally the collective behavior of self-propelling liquid droplets, which closely mimic the locomotion of some protozoal organisms, the so-called squirmers. For the sake of simplicity, we concentrate on quasi-two-dimensional (2D) settings, although our swimmers provide a fully 3D propulsion scheme. At an areal density of 0.46, we find strong polar correlation of the locomotion velocities of neighboring droplets, which decays over less than one droplet diameter. When the areal density is increased to 0.78, distinct peaks show up in the angular correlation function, which point to the formation of ordered rafts. This shows that pronounced textures, beyond what has been seen in simulations so far, may show up in crowds of simple model squirmers, despite the simplicity of their (purely physical) mutual interaction.

  13. Behavior of cosmological models with varying G

    International Nuclear Information System (INIS)

    Barrow, J.D.; Parsons, P.

    1997-01-01

    We provide a detailed analysis of Friedmann-Robertson-Walker universes in a wide range of scalar-tensor theories of gravity. We apply solution-generating methods to three parametrized classes of scalar-tensor theory which lead naturally to general relativity in the weak-field limit. We restrict the parameters which specify these theories by the requirements imposed by the weak-field tests of gravitation theories in the solar system and by the requirement that viable cosmological solutions be obtained. We construct a range of exact solutions for open, closed, and flat isotropic universes containing matter with equation of state p≤(1)/(3)ρ and in vacuum. We study the range of early- and late-time behaviors displayed, examine when there is a open-quotes bounceclose quotes at early times, and expansion maxima in closed models. copyright 1997 The American Physical Society

  14. Swarming behavior of simple model squirmers

    Energy Technology Data Exchange (ETDEWEB)

    Thutupalli, Shashi; Seemann, Ralf; Herminghaus, Stephan, E-mail: shashi.thutupalli@ds.mpg.de, E-mail: stephan.herminghaus@ds.mpg.de [Max Planck Institute for Dynamics and Self-Organization, Bunsenstrasse 10, 37073 Goettingen (Germany)

    2011-07-15

    We have studied experimentally the collective behavior of self-propelling liquid droplets, which closely mimic the locomotion of some protozoal organisms, the so-called squirmers. For the sake of simplicity, we concentrate on quasi-two-dimensional (2D) settings, although our swimmers provide a fully 3D propulsion scheme. At an areal density of 0.46, we find strong polar correlation of the locomotion velocities of neighboring droplets, which decays over less than one droplet diameter. When the areal density is increased to 0.78, distinct peaks show up in the angular correlation function, which point to the formation of ordered rafts. This shows that pronounced textures, beyond what has been seen in simulations so far, may show up in crowds of simple model squirmers, despite the simplicity of their (purely physical) mutual interaction.

  15. Modeling Human Behavior to Anticipate Insider Attacks

    Directory of Open Access Journals (Sweden)

    Ryan E Hohimer

    2011-01-01

    Full Text Available The insider threat ranks among the most pressing cyber-security challenges that threaten government and industry information infrastructures. To date, no systematic methods have been developed that provide a complete and effective approach to prevent data leakage, espionage, and sabotage. Current practice is forensic in nature, relegating to the analyst the bulk of the responsibility to monitor, analyze, and correlate an overwhelming amount of data. We describe a predictive modeling framework that integrates a diverse set of data sources from the cyber domain, as well as inferred psychological/motivational factors that may underlie malicious insider exploits. This comprehensive threat assessment approach provides automated support for the detection of high-risk behavioral "triggers" to help focus the analyst's attention and inform the analysis. Designed to be domain-independent, the system may be applied to many different threat and warning analysis/sense-making problems.

  16. Modeling the exergy behavior of human body

    International Nuclear Information System (INIS)

    Keutenedjian Mady, Carlos Eduardo; Silva Ferreira, Maurício; Itizo Yanagihara, Jurandir; Hilário Nascimento Saldiva, Paulo; Oliveira Junior, Silvio de

    2012-01-01

    Exergy analysis is applied to assess the energy conversion processes that take place in the human body, aiming at developing indicators of health and performance based on the concepts of exergy destroyed rate and exergy efficiency. The thermal behavior of the human body is simulated by a model composed of 15 cylinders with elliptical cross section representing: head, neck, trunk, arms, forearms, hands, thighs, legs, and feet. For each, a combination of tissues is considered. The energy equation is solved for each cylinder, being possible to obtain transitory response from the body due to a variation in environmental conditions. With this model, it is possible to obtain heat and mass flow rates to the environment due to radiation, convection, evaporation and respiration. The exergy balances provide the exergy variation due to heat and mass exchange over the body, and the exergy variation over time for each compartments tissue and blood, the sum of which leads to the total variation of the body. Results indicate that exergy destroyed and exergy efficiency decrease over lifespan and the human body is more efficient and destroys less exergy in lower relative humidities and higher temperatures. -- Highlights: ► In this article it is indicated an overview of the human thermal model. ► It is performed the energy and exergy analysis of the human body. ► Exergy destruction and exergy efficiency decreases with lifespan. ► Exergy destruction and exergy efficiency are a function of environmental conditions.

  17. Car-following Behavior Model Learning Using Timed Automata

    NARCIS (Netherlands)

    Zhang, Yihuan; Lin, Q.; Wang, Jun; Verwer, S.E.; Dochain, D.; Henrion, D.; Peaucelle, D.

    Learning driving behavior is fundamental for autonomous vehicles to “understand” traffic situations. This paper proposes a novel method for learning a behavioral model of car-following using automata learning algorithms. The model is interpretable for car-following behavior analysis. Frequent common

  18. A Conceptual Model of Leisure-Time Choice Behavior.

    Science.gov (United States)

    Bergier, Michel J.

    1981-01-01

    Methods of studying the gap between predisposition and actual behavior of consumers of spectator sports is discussed. A model is drawn from the areas of behavioral sciences, consumer behavior, and leisure research. The model is constructed around the premise that choice is primarily a function of personal, product, and environmental factors. (JN)

  19. Behavioral characterization of mouse models of neuroferritinopathy.

    Directory of Open Access Journals (Sweden)

    Sara Capoccia

    Full Text Available Ferritin is the main intracellular protein of iron storage with a central role in the regulation of iron metabolism and detoxification. Nucleotide insertions in the last exon of the ferritin light chain cause a neurodegenerative disease known as Neuroferritinopathy, characterized by iron deposition in the brain, particularly in the cerebellum, basal ganglia and motor cortex. The disease progresses relentlessly, leading to dystonia, chorea, motor disability and neuropsychiatry features. The characterization of a good animal model is required to compare and contrast specific features with the human disease, in order to gain new insights on the consequences of chronic iron overload on brain function and behavior. To this aim we studied an animal model expressing the pathogenic human FTL mutant 498InsTC under the phosphoglycerate kinase (PGK promoter. Transgenic (Tg mice showed strong accumulation of the mutated protein in the brain, which increased with age, and this was accompanied by brain accumulation of ferritin/iron bodies, the main pathologic hallmark of human neuroferritinopathy. Tg-mice were tested throughout development and aging at 2-, 8- and 18-months for motor coordination and balance (Beam Walking and Footprint tests. The Tg-mice showed a significant decrease in motor coordination at 8 and 18 months of age, with a shorter latency to fall and abnormal gait. Furthermore, one group of aged naïve subjects was challenged with two herbicides (Paraquat and Maneb known to cause oxidative damage. The treatment led to a paradoxical increase in behavioral activation in the transgenic mice, suggestive of altered functioning of the dopaminergic system. Overall, data indicate that mice carrying the pathogenic FTL498InsTC mutation show motor deficits with a developmental profile suggestive of a progressive pathology, as in the human disease. These mice could be a powerful tool to study the neurodegenerative mechanisms leading to the disease and help

  20. Behavioral characterization of mouse models of neuroferritinopathy.

    Science.gov (United States)

    Capoccia, Sara; Maccarinelli, Federica; Buffoli, Barbara; Rodella, Luigi F; Cremona, Ottavio; Arosio, Paolo; Cirulli, Francesca

    2015-01-01

    Ferritin is the main intracellular protein of iron storage with a central role in the regulation of iron metabolism and detoxification. Nucleotide insertions in the last exon of the ferritin light chain cause a neurodegenerative disease known as Neuroferritinopathy, characterized by iron deposition in the brain, particularly in the cerebellum, basal ganglia and motor cortex. The disease progresses relentlessly, leading to dystonia, chorea, motor disability and neuropsychiatry features. The characterization of a good animal model is required to compare and contrast specific features with the human disease, in order to gain new insights on the consequences of chronic iron overload on brain function and behavior. To this aim we studied an animal model expressing the pathogenic human FTL mutant 498InsTC under the phosphoglycerate kinase (PGK) promoter. Transgenic (Tg) mice showed strong accumulation of the mutated protein in the brain, which increased with age, and this was accompanied by brain accumulation of ferritin/iron bodies, the main pathologic hallmark of human neuroferritinopathy. Tg-mice were tested throughout development and aging at 2-, 8- and 18-months for motor coordination and balance (Beam Walking and Footprint tests). The Tg-mice showed a significant decrease in motor coordination at 8 and 18 months of age, with a shorter latency to fall and abnormal gait. Furthermore, one group of aged naïve subjects was challenged with two herbicides (Paraquat and Maneb) known to cause oxidative damage. The treatment led to a paradoxical increase in behavioral activation in the transgenic mice, suggestive of altered functioning of the dopaminergic system. Overall, data indicate that mice carrying the pathogenic FTL498InsTC mutation show motor deficits with a developmental profile suggestive of a progressive pathology, as in the human disease. These mice could be a powerful tool to study the neurodegenerative mechanisms leading to the disease and help developing

  1. Multitemporal Modelling of Socio-Economic Wildfire Drivers in Central Spain between the 1980s and the 2000s: Comparing Generalized Linear Models to Machine Learning Algorithms.

    Science.gov (United States)

    Vilar, Lara; Gómez, Israel; Martínez-Vega, Javier; Echavarría, Pilar; Riaño, David; Martín, M Pilar

    2016-01-01

    The socio-economic factors are of key importance during all phases of wildfire management that include prevention, suppression and restoration. However, modeling these factors, at the proper spatial and temporal scale to understand fire regimes is still challenging. This study analyses socio-economic drivers of wildfire occurrence in central Spain. This site represents a good example of how human activities play a key role over wildfires in the European Mediterranean basin. Generalized Linear Models (GLM) and machine learning Maximum Entropy models (Maxent) predicted wildfire occurrence in the 1980s and also in the 2000s to identify changes between each period in the socio-economic drivers affecting wildfire occurrence. GLM base their estimation on wildfire presence-absence observations whereas Maxent on wildfire presence-only. According to indicators like sensitivity or commission error Maxent outperformed GLM in both periods. It achieved a sensitivity of 38.9% and a commission error of 43.9% for the 1980s, and 67.3% and 17.9% for the 2000s. Instead, GLM obtained 23.33, 64.97, 9.41 and 18.34%, respectively. However GLM performed steadier than Maxent in terms of the overall fit. Both models explained wildfires from predictors such as population density and Wildland Urban Interface (WUI), but differed in their relative contribution. As a result of the urban sprawl and an abandonment of rural areas, predictors like WUI and distance to roads increased their contribution to both models in the 2000s, whereas Forest-Grassland Interface (FGI) influence decreased. This study demonstrates that human component can be modelled with a spatio-temporal dimension to integrate it into wildfire risk assessment.

  2. Evapotranspiration from drained wetlands: drivers, modeling, storage functions, and restoration implications

    Science.gov (United States)

    Shukla, S.; Wu, C. L.; Shrestha, N.

    2017-12-01

    Abstract Evapotranspiration (ET) is a major component of wetland and watershed water budgets. The effect of wetland drainage on ET is not well understood. We tested whether the current understanding of insignificant effect of drainage on ET in the temperate region wetlands applies to those in the sub-tropics. Eddy covariance (EC) based ET measurements were made for two years at two previously drained and geographically close wetlands in the Everglades region of Florida. One wetland was significantly drained with 97% of its storage capacity lost. The other was a more functional wetland with 42% of storage capacity lost. Annual average ET at the significantly drained wetland was 836 mm, 34% less than the function wetland (1271 mm) and the difference was statistically significant (p = 0.001). Such differences in wetland ET in the same climatic region have not been observed. The difference in ET was mainly due to drainage driven differences in inundation and associated effects on net radiation (Rn) and local relative humidity. Two daily ET models, a regression (r2 = 0.80) and a Relevance Vector Machine (RVM) model (r2 = 0.84), were developed with the latter being more robust. These models, when used in conjunction with hydrologic models, improved ET predictions for drained wetlands. Predictions from an integrated model showed that more intensely drained wetlands at higher elevation should be targeted for restoration of downstream flows (flooding) because they have the ability to loose higher water volume through ET which increases available water storage capacity of wetlands. Daily ET models can predict changes in ET for improved evaluation of basin-scale effects of restoration programs and climate change scenarios.

  3. Behavioral model of visual perception and recognition

    Science.gov (United States)

    Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

    1993-09-01

    In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and

  4. Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

    Science.gov (United States)

    Walz, M. A.; Donat, M.; Leckebusch, G. C.

    2017-12-01

    As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

  5. Extension of internationalisation models drivers and processes for the globalisation of product development

    DEFF Research Database (Denmark)

    Søndergaard, Erik Stefan; Oehmen, Josef; Ahmed-Kristensen, Saeema

    2016-01-01

    of product development and collaborative distributed development beyond sourcing, sales and production elements. The paper then provides propositions for how to further develop the suggested model, and how western companies can learn from the Chinese approaches, and globalise their product development...

  6. Evaluating predictive models for solar energy growth in the US states and identifying the key drivers

    Science.gov (United States)

    Chakraborty, Joheen; Banerji, Sugata

    2018-03-01

    Driven by a desire to control climate change and reduce the dependence on fossil fuels, governments around the world are increasing the adoption of renewable energy sources. However, among the US states, we observe a wide disparity in renewable penetration. In this study, we have identified and cleaned over a dozen datasets representing solar energy penetration in each US state, and the potentially relevant socioeconomic and other factors that may be driving the growth in solar. We have applied a number of predictive modeling approaches - including machine learning and regression - on these datasets over a 17-year period and evaluated the relative performance of the models. Our goals were: (1) identify the most important factors that are driving the growth in solar, (2) choose the most effective predictive modeling technique for solar growth, and (3) develop a model for predicting next year’s solar growth using this year’s data. We obtained very promising results with random forests (about 90% efficacy) and varying degrees of success with support vector machines and regression techniques (linear, polynomial, ridge). We also identified states with solar growth slower than expected and representing a potential for stronger growth in future.

  7. Land use as a Driver of Patterns of Rodenticide Exposure in Modeled Kit Fox Populations

    Science.gov (United States)

    Although rodenticides are increasingly regulated, they nonetheless cause poisonings in many non-target wildlife species. Second-generation anticoagualant rodenticide use is common in agricultural and residential lands. Here, we use an individual-based population model to assess t...

  8. Modeling of Uncertainties in Major Drivers in U.S. Electricity Markets: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Short, W.; Ferguson, T.; Leifman, M.

    2006-09-01

    This paper presents information on the Stochastic Energy Deployment System (SEDS) model. DOE and NREL are developing this new model, intended to address many of the shortcomings of the current suite of energy models. Once fully built, the salient qualities of SEDS will include full probabilistic treatment of the major uncertainties in national energy forecasts; code compactness for desktop application; user-friendly interface for a reasonably trained analyst; run-time within limits acceptable for quick-response analysis; choice of detailed or aggregate representations; and transparency of design, code, and assumptions. Moreover, SEDS development will be increasingly collaborative, as DOE and NREL will be coordinating with multiple national laboratories and other institutions, making SEDS nearly an 'open source' project. The collaboration will utilize the best expertise on specific sectors and problems, and also allow constant examination and review of the model. This paper outlines the rationale for this project and a description of its alpha version, as well as some example results. It also describes some of the expected development efforts in SEDS.

  9. SUBJECTIVE METHODS FOR ASSESSMENT OF DRIVER DROWSINESS

    Directory of Open Access Journals (Sweden)

    Alina Mashko

    2017-12-01

    Full Text Available The paper deals with the issue of fatigue and sleepiness behind the wheel, which for a long time has been of vital importance for the research in the area of driver-car interaction safety. Numerous experiments on car simulators with diverse measurements to observe human behavior have been performed at the laboratories of the faculty of the authors. The paper provides analysis and an overview and assessment of the subjective (self-rating and observer rating methods for observation of driver behavior and the detection of critical behavior in sleep deprived drivers using the developed subjective rating scales.

  10. Automobile Driver Fingerprinting

    Directory of Open Access Journals (Sweden)

    Enev Miro

    2016-01-01

    Full Text Available Today’s automobiles leverage powerful sensors and embedded computers to optimize efficiency, safety, and driver engagement. However the complexity of possible inferences using in-car sensor data is not well understood. While we do not know of attempts by automotive manufacturers or makers of after-market components (like insurance dongles to violate privacy, a key question we ask is: could they (or their collection and later accidental leaks of data violate a driver’s privacy? In the present study, we experimentally investigate the potential to identify individuals using sensor data snippets of their natural driving behavior. More specifically we record the in-vehicle sensor data on the controllerarea- network (CAN of a typical modern vehicle (popular 2009 sedan as each of 15 participants (a performed a series of maneuvers in an isolated parking lot, and (b drove the vehicle in traffic along a defined ~ 50 mile loop through the Seattle metropolitan area. We then split the data into training and testing sets, train an ensemble of classifiers, and evaluate identification accuracy of test data queries by looking at the highest voted candidate when considering all possible one-vs-one comparisons. Our results indicate that, at least among small sets, drivers are indeed distinguishable using only incar sensors. In particular, we find that it is possible to differentiate our 15 drivers with 100% accuracy when training with all of the available sensors using 90% of driving data from each person. Furthermore, it is possible to reach high identification rates using less than 8 minutes of training data. When more training data is available it is possible to reach very high identification using only a single sensor (e.g., the brake pedal. As an extension, we also demonstrate the feasibility of performing driver identification across multiple days of data collection

  11. Modelling drivers of mangrove propagule dispersal and restoration of abandoned shrimp farms

    Directory of Open Access Journals (Sweden)

    D. Di Nitto

    2013-07-01

    Full Text Available Propagule dispersal of four mangrove species Rhizophora mucronata, R. apiculata, Ceriops tagal and Avicennia officinalis in the Pambala–Chilaw Lagoon Complex (Sri Lanka was studied by combining a hydrodynamic model with species-specific knowledge on propagule dispersal behaviour. Propagule transport was simulated using a finite-volume advection-diffusion model to investigate the effect of dispersal vectors (tidal flow, freshwater discharge and wind, trapping agents (retention by vegetation and seed characteristics (buoyancy on propagule dispersal patterns. Sensitivity analysis showed that smaller propagules, like the oval-shaped propagules of Avicennia officinalis, dispersed over larger distances and were most sensitive to changing values of retention by mangrove vegetation compared to larger, torpedo-shaped propagules of Rhizophora spp. and C. tagal. Directional propagule dispersal in this semi-enclosed lagoon with a small tidal range was strongly concentrated towards the edges of the lagoon and channels. Short distance dispersal appeared to be the main dispersal strategy for all four studied species, with most of the propagules being retained within the vegetation. Only a small proportion (max. 5% of propagules left the lagoon through a channel connecting the lagoon with the open sea. Wind significantly influenced dispersal distance and direction once propagules entered the lagoon or adjacent channels. Implications of these findings for mangrove restoration were tested by simulating partial removal in the model of dikes around abandoned shrimp ponds to restore tidal hydrology and facilitate natural recolonisation by mangroves. The specific location of dike removal, (with respect to the vicinity of mangroves and independently suitable hydrodynamic flows, was found to significantly affect the resultant quantities and species of inflowing propagules and hence the potential effectiveness of natural regeneration. These results demonstrate the

  12. Leadership drivers of organizational creativity: a path model of creative climate in a professional service firm

    OpenAIRE

    Sandvik Madsen, Alexander; Espedal, Bjarne; Selart, Marcus

    2015-01-01

    The purpose of this study was to explore how and under what conditions two different leadership roles are able to facilitate an organizational climate that supports creativity. The study was conducted in a leading professional service firm. The introduced hypotheses were tested by means of a structural equation model. Findings indicate that the leadership roles are conceptually different and that organizational structure is important for leaders’ ability to create a climate ...

  13. Functional Bus Driver-Pupil Passenger Relationships.

    Science.gov (United States)

    Farmer, Ernest

    1987-01-01

    Successful school bus drivers bring much more than mechanical know-how to the job. They develop good rapport with students while acting to bring undesirable student behavior under control. Drivers must also show an interest in students' welfare and have a good sense of humor. (MLH)

  14. Traffic Safety through Driver Assistance and Intelligence

    Directory of Open Access Journals (Sweden)

    Heiner Bubb

    2011-05-01

    BMW, Daimler, Audi, Citroen, Lexus, VW, Opel, Peugeot, Renault, Chevrolet, Saab and Bosch. Both the contributions of research work concerning driving behavior analysis and driver assistance systems have to be aligned with a permanently updated interaction within the system of driver, vehicle and road traffic environment.

  15. Difficulties in emotion regulation and risky driving among Lithuanian drivers.

    Science.gov (United States)

    Šeibokaitė, Laura; Endriulaitienė, Auksė; Sullman, Mark J M; Markšaitytė, Rasa; Žardeckaitė-Matulaitienė, Kristina

    2017-10-03

    Risky driving is a common cause of traffic accidents and injuries. However, there is no clear evidence of how difficulties in emotion regulation contribute to risky driving behavior, particularly in small post-Soviet countries. The present study aimed to investigate the relationship between difficulties in emotion regulation and self-reported risky driving behavior in a sample of Lithuanian drivers. A total of 246 nonprofessional Lithuanian drivers participated in a cross-sectional survey. Difficulties in emotion regulation were assessed using the Difficulties in Emotion Regulation Scale (DERS; Gratz and Roemer 2004), and risky driving behavior was assessed using the Manchester Driver Behaviour Questionnaire (DBQ; Lajunen et al. 2004). Males scored higher than females in aggressive violations and ordinary violations. Females scored higher for the nonacceptance of emotional responses, whereas males had more difficulties with emotional awareness than females. More difficulties in emotion regulation were positively correlated with driving errors, lapses, aggressive violations, and ordinary violations for both males and females. Structural equation modeling showed that difficulties in emotion regulation explained aggressive and ordinary violations more clearly than lapses and errors. When controlling for interactions among the distinct regulation difficulties, difficulties with impulse control and difficulties engaging in goal-directed behavior predicted risky driving. Furthermore, nonacceptance of emotional responses and limited access to emotion regulation strategies were related to less violations and more driving errors. Emotion regulation difficulties were associated with the self-reported risky driving behaviors of Lithuanian drivers. This provides useful hints for improving driver training programs in order to prevent traffic injuries.

  16. Conscientious personality and young drivers' crash risk.

    Science.gov (United States)

    Ehsani, Johnathon P; Li, Kaigang; Simons-Morton, Bruce G; Fox Tree-McGrath, Cheyenne; Perlus, Jessamyn G; O'Brien, Fearghal; Klauer, Sheila G

    2015-09-01

    Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior, and crashes and near-crashes, using naturalistic driving research methods. Participants' driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate, and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants' KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Conscientiousness was marginally negatively associated with CNC (path c=-0.034, p=.09) and both potential mediators KRD (path a=-0.040, p=.09) and secondary task engagement while driving (path a=-0.053, p=.03). KRD, but not secondary task engagement, was found to mediate (path b=0.376, p=.02) the relationship between conscientiousness and CNC (path c'=-0.025, p=.20). Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, and suffered fewer CNC. Part of the variability in crash risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers' personality into account when providing guidance, and establishing norms and

  17. Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints

    Czech Academy of Sciences Publication Activity Database

    Colwell, R. K.; Gotelli, N. J.; Ashton, L. A.; Beck, J.; Brehm, G.; Fayle, Tom Maurice; Fiedler, K.; Forister, M. L.; Kessler, M.; Kitching, R. L.; Klimeš, Petr; Kluge, J.; Longino, J. T.; Maunsell, S. C.; McCain, C. M.; Moses, J.; Noben, N.; Sam, Kateřina; Sam, Legi; Shapiro, A. M.; Wang, X.; Novotný, Vojtěch

    2016-01-01

    Roč. 19, č. 9 (2016), s. 1009-1022 ISSN 1461-023X R&D Projects: GA ČR GB14-36098G; GA ČR GA14-32302S; GA ČR(CZ) GP14-32024P; GA ČR GA13-10486S Institutional support: RVO:60077344 Keywords : Bayesian model * biogeography * elevational gradients Subject RIV: EH - Ecology, Behaviour Impact factor: 9.449, year: 2016 http://onlinelibrary.wiley.com/doi/10.1111/ele.12640/full

  18. Psychological drivers in doping: The life-cycle model of performance enhancement

    Directory of Open Access Journals (Sweden)

    Aidman Eugene

    2008-03-01

    Full Text Available Abstract Background Performance enhancement (PE is a natural and essential ingredient of competitive sport. Except for nutritional supplement contamination, accidental use of doping is highly unlikely. It requires deliberation, planning and commitment; and is influenced by a host of protective and risk factors. Hypothesis In the course of their career, athletes constantly set goals and make choices regarding the way these goals can be achieved. The cycle of choice – goal commitment – execution – feedback on goal attainment – goal evaluation/adjustment has numerous exit points, each providing an opportunity for behaviour change, which may or may not be related to the use of prohibited methods. The interplay between facilitating and inhibiting systemic and personality factors, constantly influenced by situational factors could result in an outcome vector of 'doping attitudes', which combines with subjective norms to influence intentions to choose prohibited PE methods. These influences also vary from one stage of athlete development to the next, making some athletes more vulnerable to engaging in doping practices than others, and more vulnerable at certain time periods – and not others. Testing the hypothesis Model-testing requires a series of carefully planned and coordinated studies. Correlational studies can establish relationships where the directionality is not-known or not important. Experimental studies with the manipulation of doping expectancies and risk factors can be used to demonstrate causality and evaluate potential intervention strategies. The final model can be tested via a behavioural simulation, with outcomes compared to those expected from literature precedence or used as a simulated computer game for empirical data collection. Implications A hypothesized life-cycle model of PE identifies vulnerability factors across the stages of athlete development with the view of informing the design of anti-doping assessment and

  19. Drivers of inorganic carbon dynamics in first-year sea ice: A model study

    DEFF Research Database (Denmark)

    Moreau, Sebastien; Vancoppenolle, Martin; Delille, Bruno

    2015-01-01

    , of total dissolved inorganic carbon (DIC) and total alkalinity (TA) are represented using fluid transport equa- tions. Carbonate chemistry, the consumption, and release of CO2 by primary production and respiration, the precipitation and dissolution of ikaite (CaCO3ﰀ6H2O) and ice-air CO2 fluxes, are also...... included. The model is evaluated using observations from a 6 month field study at Point Barrow, Alaska, and an ice-tank experi- ment. At Barrow, results show that the DIC budget is mainly driven by physical processes, wheras brine-air CO2 fluxes, ikaite formation, and net primary production, are secondary...

  20. Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases.

    Science.gov (United States)

    Mezlini, Aziz M; Goldenberg, Anna

    2017-10-01

    Discovering genetic mechanisms driving complex diseases is a hard problem. Existing methods often lack power to identify the set of responsible genes. Protein-protein interaction networks have been shown to boost power when detecting gene-disease associations. We introduce a Bayesian framework, Conflux, to find disease associated genes from exome sequencing data using networks as a prior. There are two main advantages to using networks within a probabilistic graphical model. First, networks are noisy and incomplete, a substantial impediment to gene discovery. Incorporating networks into the structure of a probabilistic models for gene inference has less impact on the solution than relying on the noisy network structure directly. Second, using a Bayesian framework we can keep track of the uncertainty of each gene being associated with the phenotype rather than returning a fixed list of genes. We first show that using networks clearly improves gene detection compared to individual gene testing. We then show consistently improved performance of Conflux compared to the state-of-the-art diffusion network-based method Hotnet2 and a variety of other network and variant aggregation methods, using randomly generated and literature-reported gene sets. We test Hotnet2 and Conflux on several network configurations to reveal biases and patterns of false positives and false negatives in each case. Our experiments show that our novel Bayesian framework Conflux incorporates many of the advantages of the current state-of-the-art methods, while offering more flexibility and improved power in many gene-disease association scenarios.

  1. Uncovering the drivers of host-associated microbiota with joint species distribution modelling.

    Science.gov (United States)

    Björk, Johannes R; Hui, Francis K C; O'Hara, Robert B; Montoya, Jose M

    2018-06-01

    In addition to the processes structuring free-living communities, host-associated microbiota are directly or indirectly shaped by the host. Therefore, microbiota data have a hierarchical structure where samples are nested under one or several variables representing host-specific factors, often spanning multiple levels of biological organization. Current statistical methods do not accommodate this hierarchical data structure and therefore cannot explicitly account for the effect of the host in structuring the microbiota. We introduce a novel extension of joint species distribution models (JSDMs) which can straightforwardly accommodate and discern between effects such as host phylogeny and traits, recorded covariates such as diet and collection site, among other ecological processes. Our proposed methodology includes powerful yet familiar outputs seen in community ecology overall, including (a) model-based ordination to visualize and quantify the main patterns in the data; (b) variance partitioning to assess how influential the included host-specific factors are in structuring the microbiota; and (c) co-occurrence networks to visualize microbe-to-microbe associations. © 2018 John Wiley & Sons Ltd.

  2. Perceived enjoyment, concentration, intention, and speed violation behavior: Using flow theory and theory of planned behavior.

    Science.gov (United States)

    Atombo, Charles; Wu, Chaozhong; Zhang, Hui; Wemegah, Tina D

    2017-10-03

    Road accidents are an important public health concern, and speeding is a major contributor. Although flow theory (FLT) is a valid model for understanding behavior, currently the nature of the roles and interplay of FLT constructs within the theory of planned behavior (TPB) framework when attempting to explain the determinants of motivations for intention to speed and speeding behavior of car drivers is not yet known. The study aims to synthesize TPB and FLT in explaining drivers of advanced vehicles intentions to speed and speed violation behaviors and evaluate factors that are critical for explaining intention and behavior. The hypothesized model was validated using a sample collected from 354 fully licensed drivers of advanced vehicles, involving 278 males and 76 females on 2 occasions separated by a 3-month interval. During the first of the 2 occasions, participants completed questionnaire measures of TPB and FLT variables. Three months later, participants' speed violation behaviors were assessed. The study observed a significant positive relationship between the constructs. The proposed model accounted for 51 and 45% of the variance in intention to speed and speed violation behavior, respectively. The independent predictors of intention were enjoyment, attitude, and subjective norm. The independent predictors of speed violation behavior were enjoyment, concentration, intention, and perceived behavioral control. The findings suggest that safety interventions for preventing speed violation behaviors should be aimed at underlying beliefs influencing the speeding behaviors of drivers of advanced vehicles. Furthermore, perceived enjoyment is of equal importance to driver's intention, influencing speed violation behavior.

  3. Phase behavior of model ABC triblock copolymers

    Science.gov (United States)

    Chatterjee, Joon

    The phase behavior of poly(isoprene-b-styrene- b-ethylene oxide) (ISO), a model ABC triblock copolymer has been studied. This class of materials exhibit self-assembly, forming a large array of ordered morphologies at length scales of 5-100 nm. The formation of stable three-dimensionally continuous network morphologies is of special interest in this study. Since these nanostructures considerably impact the material properties, fundamental knowledge for designing ABC systems have high technological importance for realizing applications in the areas of nanofabrication, nanoporous media, separation membranes, drug delivery and high surface area catalysts. A comprehensive framework was developed to describe the phase behavior of the ISO triblock copolymers at weak to intermediate segregation strengths spanning a wide range of composition. Phases were characterized through a combination of characterization techniques, including small angle x-ray scattering, dynamic mechanical spectroscopy, transmission electron microscopy, and birefringence measurements. Combined with previous investigations on ISO, six different stable ordered state symmetries have been identified: lamellae (LAM), Fddd orthorhombic network (O70), double gyroid (Q230), alternating gyroid (Q214), hexagonal (HEX), and body-centered cubic (BCC). The phase map was found to be somewhat asymmetric around the fI = fO isopleth. This work provides a guide for theoretical studies and gives insight into the intricate effects of various parameters on the self-assembly of ABC triblock copolymers. Experimental SAXS data evaluated with a simple scattering intensity model show that local mixing varies continuously across the phase map between states of two- and three-domain segregation. Strategies of blending homopolymers with ISO triblock copolymer were employed for studying the swelling properties of a lamellar state. Results demonstrate that lamellar domains swell or shrink depending upon the type of homopolymer that

  4. Mathematical Modeling to Assess the Drivers of the Recent Emergence of Typhoid Fever in Blantyre, Malawi.

    Science.gov (United States)

    Pitzer, Virginia E; Feasey, Nicholas A; Msefula, Chisomo; Mallewa, Jane; Kennedy, Neil; Dube, Queen; Denis, Brigitte; Gordon, Melita A; Heyderman, Robert S

    2015-11-01

    Multiyear epidemics of Salmonella enterica serovar Typhi have been reported from countries across eastern and southern Africa in recent years. In Blantyre, Malawi, a dramatic increase in typhoid fever cases has recently occurred, and may be linked to the emergence of the H58 haplotype. Strains belonging to the H58 haplotype often exhibit multidrug resistance and may have a fitness advantage relative to other Salmonella Typhi strains. To explore hypotheses for the increased number of typhoid fever cases in Blantyre, we fit a mathematical model to culture-confirmed cases of Salmonella enterica infections at Queen Elizabeth Central Hospital, Blantyre. We explored 4 hypotheses: (1) an increase in the basic reproductive number (R0) in response to increasing population density; (2) a decrease in the incidence of cross-immunizing infection with Salmonella Enteritidis; (3) an increase in the duration of infectiousness due to failure to respond to first-line antibiotics; and (4) an increase in the transmission rate following the emergence of the H58 haplotype. Increasing population density or decreasing cross-immunity could not fully explain the observed pattern of typhoid emergence in Blantyre, whereas models allowing for an increase in the duration of infectiousness and/or the transmission rate of typhoid following the emergence of the H58 haplotype provided a good fit to the data. Our results suggest that an increase in the transmissibility of typhoid due to the emergence of drug resistance associated with the H58 haplotype may help to explain recent outbreaks of typhoid in Malawi and similar settings in Africa. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

  5. Drivers of inorganic carbon dynamics in first-year sea ice: A model study

    Science.gov (United States)

    Moreau, Sébastien; Vancoppenolle, Martin; Delille, Bruno; Tison, Jean-Louis; Zhou, Jiayun; Kotovich, Marie; Thomas, David; Geilfus, Nicolas-Xavier; Goosse, Hugues

    2015-04-01

    Sea ice is an active source or a sink for carbon dioxide (CO2), although to what extent is not clear. Here, we analyze CO2 dynamics within sea ice using a one-dimensional halo-thermodynamic sea ice model including gas physics and carbon biogeochemistry. The ice-ocean fluxes, and vertical transport, of total dissolved inorganic carbon (DIC) and total alkalinity (TA) are represented using fluid transport equations. Carbonate chemistry, the consumption and release of CO2 by primary production and respiration, the precipitation and dissolution of ikaite (CaCO3•6H2O) and ice-air CO2 fluxes, are also included. The model is evaluated using observations from a 6-month field study at Point Barrow, Alaska and an ice-tank experiment. At Barrow, results show that the DIC budget is mainly driven by physical processes, wheras brine-air CO2 fluxes, ikaite formation, and net primary production, are secondary factors. In terms of ice-atmosphere CO2 exchanges, sea ice is a net CO2 source and sink in winter and summer, respectively. The formulation of the ice-atmosphere CO2 flux impacts the simulated near-surface CO2 partial pressure (pCO2), but not the DIC budget. Because the simulated ice-atmosphere CO2 fluxes are limited by DIC stocks, and therefore < 2 mmol m-2 day-1, we argue that the observed much larger CO2 fluxes from eddy covariance retrievals cannot be explained by a sea ice direct source and must involve other processes or other sources of CO2. Finally, the simulations suggest that near surface TA/DIC ratios of ~2, sometimes used as an indicator of calcification, would rather suggest outgassing.

  6. The relative impact of climate change mitigation policies and socioeconomic drivers on water scarcity - An integrated assessment modeling approach

    Science.gov (United States)

    Hejazi, M. I.; Edmonds, J. A.; Clarke, L. E.; Kyle, P.; Davies, E. G.; Chaturvedi, V.; Patel, P.; Eom, J.; Wise, M.; Kim, S.; Calvin, K. V.; Moss, R. H.

    2012-12-01

    We investigate the relative effects of climate emission mitigation policies and socioeconomic drivers on water scarcity conditions over the 21st century both globally and regionally, by estimating both water availability and demand within a technologically-detailed global integrated assessment model of energy, agriculture, and climate change - the Global Change Assessment Model (GCAM). We first develop a global gridded monthly hydrologic model that reproduces historical streamflow observations and simulates the future availability of freshwater under both a changing climate and an evolving landscape, and incorporate this model into GCAM. We then develop and incorporate technologically oriented representations of water demands for the agricultural (irrigation and livestock), energy (electricity generation, primary energy production and processing), industrial (manufacturing and mining), and municipal sectors. The energy, industrial, and municipal sectors are represented in fourteen geopolitical regions, with the agricultural sector further disaggregated into as many as eighteen agro-ecological zones (AEZs) within each region. To perform the water scarcity analysis at the grid scale, the global water demands for the six demand sectors are spatially downscaled to 0.5 o x 0.5o resolution to match the scale of GWAM. The water scarcity index (WSI) compares total water demand to the total amount of renewable water available, and defines extreme water scarcity in any region as demand greater than 40% of total water availability. Using a reference scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W/m2 by 2095 and a global population of 14 billion, global annual water demand grows from about 9% of total annual renewable freshwater in 2005 to about 32% by 2095. This results in almost half of the world population living under extreme water scarcity by the end of the 21st century. Regionally, the demands for water exceed the total

  7. Scanpath Based N-Gram Models for Predicting Reading Behavior

    DEFF Research Database (Denmark)

    Mishra, Abhijit; Bhattacharyya, Pushpak; Carl, Michael

    2013-01-01

    Predicting reading behavior is a difficult task. Reading behavior depends on various linguistic factors (e.g. sentence length, structural complexity etc.) and other factors (e.g individual's reading style, age etc.). Ideally, a reading model should be similar to a language model where the model i...

  8. Statistical analysis of road-vehicle-driver interaction as an enabler to designing behavioural models

    International Nuclear Information System (INIS)

    Chakravarty, T; Chowdhury, A; Ghose, A; Bhaumik, C; Balamuralidhar, P

    2014-01-01

    Telematics form an important technology enabler for intelligent transportation systems. By deploying on-board diagnostic devices, the signatures of vehicle vibration along with its location and time are recorded. Detailed analyses of the collected signatures offer deep insights into the state of the objects under study. Towards that objective, we carried out experiments by deploying telematics device in one of the office bus that ferries employees to office and back. Data is being collected from 3-axis accelerometer, GPS, speed and the time for all the journeys. In this paper, we present initial results of the above exercise by applying statistical methods to derive information through systematic analysis of the data collected over four months. It is demonstrated that the higher order derivative of the measured Z axis acceleration samples display the properties Weibull distribution when the time axis is replaced by the amplitude of such processed acceleration data. Such an observation offers us a method to predict future behaviour where deviations from prediction are classified as context-based aberrations or progressive degradation of the system. In addition we capture the relationship between speed of the vehicle and median of the jerk energy samples using regression analysis. Such results offer an opportunity to develop a robust method to model road-vehicle interaction thereby enabling us to predict such like driving behaviour and condition based maintenance etc

  9. Heavy-ion driver parametric studies and choice of a base 5 mega-joule driver design

    International Nuclear Information System (INIS)

    Bieri, R.; Meier, W.

    1992-01-01

    Parametric studies to optimize heavy-ion driver designs are described and an optimized 5 MJ driver design is described. Parametric studies are done on driver parameters including driver energy, number of beams, type of superconductor used in focusing magnets, maximum magnetic field allowed at the superconducting windings, axial quadrupole field packing fraction, ion mass, and ion charge state. All modeled drivers use the maximum beam currents allowed by the Maschke limits; driver scaling is described in a companion paper. The optimized driver described is conservative and cost effective. The base driver direct costs are only $120/Joule, and the base driver uses no recirculation, beam combination, or beam separation. The low driver cost achieved is due, in part, to the use of compact Nb 3 Sn quadrupole arrays, but results primarily from optimization over the large, multi-dimensional, parameter space available for heavy-ion drivers

  10. Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews.

    Science.gov (United States)

    Kuesten, Carla; Bi, Jian

    2018-06-03

    Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews.

  11. Matching of traction control systems for all-wheel devices by means of a virtual driver model; Abstimmung von Traktionsregelsystemen fuer Allradfahrzeuge mit Hilfe eines virtuellen Fahrermodells

    Energy Technology Data Exchange (ETDEWEB)

    Vockenhuber, Mario [MAGNA Powertrain AG und Co. KG, Lannach (Austria); Fischer, Rainer [Magna Powertrain, Engineering Center Steyr, St. Valentin (Austria); Butz, Torsten; Ehmann, Martin [TESIS DYNAware GmbH, Muenchen (Germany)

    2011-07-01

    Simulation of the full vehicle dynamics is an efficient means for function development and validation as well as calibration of traction control systems for four-wheel drive vehicles. Simulation models for vehicle, control systems and environment with a suitable level of detail are used to investigate different layout variants of the drivetrain on various tracks. This contribution outlines a driver model which enables considering the influence of different driving styles. Various human driver types are depicted by specific controller parameterization or definition of reference values for longitudinal and lateral vehicle guidance. Thus, apart from the calibration of control system electronics also realistic load spectra for durability computations of mechanical components can be determined via simulation. (orig.)

  12. ECO-DRIVING MODELING ENVIRONMENT

    Science.gov (United States)

    2015-11-01

    This research project aims to examine the eco-driving modeling capabilities of different traffic modeling tools available and to develop a driver-simulator-based eco-driving modeling tool to evaluate driver behavior and to reliably estimate or measur...

  13. Consumer Behavior Modeling: Fuzzy Logic Model for Air Purifiers Choosing

    Directory of Open Access Journals (Sweden)

    Oleksandr Dorokhov

    2017-12-01

    Full Text Available At the beginning, the article briefly describes the features of the marketing complex household goods. Also provides an overview of some aspects of the market for indoor air purifiers. The specific subject of the study was the process of consumer choice of household appliances for cleaning air in living quarters. The aim of the study was to substantiate and develop a computer model for evaluating by the potential buyers devices for air purification in conditions of vagueness and ambiguity of their consumer preferences. Accordingly, the main consumer criteria are identified, substantiated and described when buyers choose air purifiers. As methods of research, approaches based on fuzzy logic, fuzzy sets theory and fuzzy modeling were chosen. It was hypothesized that the fuzzy-multiple model allows rather accurately reflect consumer preferences and potential consumer choice in conditions of insufficient and undetermined information. Further, a computer model for estimating the consumer qualities of air cleaners by customers is developed. A proposed approach based on the application of fuzzy logic theory and practical modeling in the specialized computer software MATLAB. In this model, the necessary membership functions and their terms are constructed, as well as a set of rules for fuzzy inference to make decisions on the estimation of a specific air purifier. A numerical example of a comparative evaluation of air cleaners presented on the Ukrainian market is made and is given. Numerical simulation results confirmed the applicability of the proposed approach and the correctness of the hypothesis advanced about the possibility of modeling consumer behavior using fuzzy logic. The analysis of the obtained results is carried out and the prospects of application, development, and improvement of the developed model and the proposed approach are determined.

  14. Agent-Based Modeling of Taxi Behavior Simulation with Probe Vehicle Data

    Directory of Open Access Journals (Sweden)

    Saurav Ranjit

    2018-05-01

    Full Text Available Taxi behavior is a spatial–temporal dynamic process involving discrete time dependent events, such as customer pick-up, customer drop-off, cruising, and parking. Simulation models, which are a simplification of a real-world system, can help understand the effects of change of such dynamic behavior. In this paper, agent-based modeling and simulation is proposed, that describes the dynamic action of an agent, i.e., taxi, governed by behavior rules and properties, which emulate the taxi behavior. Taxi behavior simulations are fundamentally done for optimizing the service level for both taxi drivers as well as passengers. Moreover, simulation techniques, as such, could be applied to another field of application as well, where obtaining real raw data are somewhat difficult due to privacy issues, such as human mobility data or call detail record data. This paper describes the development of an agent-based simulation model which is based on multiple input parameters (taxi stay point cluster; trip information (origin and destination; taxi demand information; free taxi movement; and network travel time that were derived from taxi probe GPS data. As such, agent’s parameters were mapped into grid network, and the road network, for which the grid network was used as a base for query/search/retrieval of taxi agent’s parameters, while the actual movement of taxi agents was on the road network with routing and interpolation. The results obtained from the simulated taxi agent data and real taxi data showed a significant level of similarity of different taxi behavior, such as trip generation; trip time; trip distance as well as trip occupancy, based on its distribution. As for efficient data handling, a distributed computing platform for large-scale data was used for extracting taxi agent parameter from the probe data by utilizing both spatial and non-spatial indexing technique.

  15. Research on driver fatigue detection

    Science.gov (United States)

    Zhang, Ting; Chen, Zhong; Ouyang, Chao

    2018-03-01

    Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.

  16. Induction linac drivers for commercial heavy-ion beam fusion

    International Nuclear Information System (INIS)

    Keefe, D.

    1987-11-01

    This paper discusses induction linac drivers necessary to accelerate heavy ions at inertial fusion targets. Topics discussed are: driver configurations, the current-amplifying induction linac, high current beam behavior and emittance growth, new considerations for driver design, the heavy ion fusion systems study, and future studies. 13 refs., 6 figs., 1 tab

  17. Drivers for Welfare Innovation

    DEFF Research Database (Denmark)

    Wegener, Charlotte

    2015-01-01

    Innovation has become a key goal towards which teaching and workplace learning needs to be directed. Now perceived as germane and even necessary in almost all kinds of welfare work, the innovation potential in everyday practices and ways of allowing for employer creativity have become a highly...... on the empirical material, the paper proposes a ‘driver’ model for context sensitive research of innovation in welfare workplaces. The model involves three elements which can be regarded as drivers for innovation: i) craft (i.e. professional skills and knowledge), ii) levers (i.e. experiments and adjustment...

  18. Behavioral modelling and predistortion of wideband wireless transmitters

    CERN Document Server

    Ghannouchi, Fadhel M; Helaoui, Mohamed

    2015-01-01

    Covers theoretical and practical aspects related to the behavioral modelling and predistortion of wireless transmitters and power amplifiers. It includes simulation software that enables the users to apply the theory presented in the book. In the first section, the reader is given the general background of nonlinear dynamic systems along with their behavioral modelling from all its aspects. In the second part, a comprehensive compilation of behavioral models formulations and structures is provided including memory polynomial based models, box oriented models such as Hammerstein-based and Wiene

  19. Animal behavior models of the mechanisms underlying antipsychotic atypicality.

    NARCIS (Netherlands)

    Geyer, M.A.; Ellenbroek, B.A.

    2003-01-01

    This review describes the animal behavior models that provide insight into the mechanisms underlying the critical differences between the actions of typical vs. atypical antipsychotic drugs. Although many of these models are capable of differentiating between antipsychotic and other psychotropic

  20. Trojan detection model based on network behavior analysis

    International Nuclear Information System (INIS)

    Liu Junrong; Liu Baoxu; Wang Wenjin

    2012-01-01

    Based on the analysis of existing Trojan detection technology, this paper presents a Trojan detection model based on network behavior analysis. First of all, we abstract description of the Trojan network behavior, then according to certain rules to establish the characteristic behavior library, and then use the support vector machine algorithm to determine whether a Trojan invasion. Finally, through the intrusion detection experiments, shows that this model can effectively detect Trojans. (authors)

  1. Understanding Eating Behaviors through Parental Communication and the Integrative Model of Behavioral Prediction.

    Science.gov (United States)

    Scheinfeld, Emily; Shim, Minsun

    2017-05-01

    Emerging adulthood (EA) is an important yet overlooked period for developing long-term health behaviors. During these years, emerging adults adopt health behaviors that persist throughout life. This study applies the Integrative Model of Behavioral Prediction (IMBP) to examine the role of childhood parental communication in predicting engagement in healthful eating during EA. Participants included 239 college students, ages 18 to 25, from a large university in the southern United States. Participants were recruited and data collection occurred spring 2012. Participants responded to measures to assess perceived parental communication, eating behaviors, attitudes, subjective norms, and behavioral control over healthful eating. SEM and mediation analyses were used to address the hypotheses posited. Data demonstrated that perceived parent-child communication - specifically, its quality and target-specific content - significantly predicted emerging adults' eating behaviors, mediated through subjective norm and perceived behavioral control. This study sets the stage for further exploration and understanding of different ways parental communication influences emerging adults' healthy behavior enactment.

  2. Cognitive Models as Bridge between Brain and Behavior.

    Science.gov (United States)

    Love, Bradley C

    2016-04-01

    How can disparate neural and behavioral measures be integrated? Turner and colleagues propose joint modeling as a solution. Joint modeling mutually constrains the interpretation of brain and behavioral measures by exploiting their covariation structure. Simultaneous estimation allows for more accurate prediction than would be possible by considering these measures in isolation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Generalised additive models to investigate environmental drivers of Antarctic minke whale (Balaenoptera bonaerensis) spatial density in austral summer

    NARCIS (Netherlands)

    Beekmans, B.W.P.M.; Forcada, J.; Murphy, E.J.; Baar, H.J.W.; Bathmann, U.V.; Fleming, A.H.

    2010-01-01

    There is a need to characterise the physical environment associated with Antarctic minke whale density in order to understand long-term changes in minke whale distribution and density in open waters of the Southern Ocean during austral summer months. To investigate environmental drivers of Antarctic

  4. Experimental Research in Boost Driver with EDLCs

    Science.gov (United States)

    Matsumoto, Hirokazu

    The supply used in servo systems tends to have a high voltage in order to reduce loss and improve the response of motor drives. We propose a new boost motor driver that comprises EDLCs. The proposed driver has a simple structure, wherein the EDLCs are connected in series to the supply, and comprises a charge circuit to charge the EDLCs. The proposed driver has three advantages over conventional boost drivers. The first advantage is that the driver can easily attain the stable boost voltage. The second advantage is that the driver can reduce input power peaks. In a servo system, the input power peaks become greater than the rated power in order to accelerate the motor rapidly. This implies that the equipments that supply power to servo systems must have sufficient power capacity to satisfy the power peaks. The proposed driver can suppress the increase of the power capacity of supply facilities. The third advantage is that the driver can store almost all of the regenerative energy. Conventional drivers have a braking resistor to suppress the increase in the DC link voltage. This causes a considerable reduction in the efficiency. The proposed driver is more efficient than conventional drivers. In this study, the experimental results confirmed the effectiveness of the proposed driver and showed that the drive performance of the proposed driver is the same as that of a conventional driver. Furthermore, it was confirmed that the results of the simulation of a model of the EDLC module, whose capacitance is dependent on the frequency, correspond well with the experimental results.

  5. Final Report on the Fuel Saving Effectiveness of Various Driver Feedback Approaches

    Energy Technology Data Exchange (ETDEWEB)

    Gonder, J.; Earleywine, M.; Sparks, W.

    2011-03-01

    This final report quantifies the fuel-savings opportunities from specific driving behavior changes, identifies factors that influence drivers' receptiveness to adopting fuel-saving behaviors, and assesses various driver feedback approaches.

  6. Modeling and Analyzing Academic Researcher Behavior

    Directory of Open Access Journals (Sweden)

    Phuc Huu Nguyen

    2016-12-01

    Full Text Available Abstract. This paper suggests a theoretical framework for analyzing the mechanism of the behavior of academic researchers whose interests are tangled and vary widely in academic factors (the intrinsic satisfaction in conducting research, the improvement in individual research ability, etc. or non-academic factors (career rewards, financial rewards, etc.. Furthermore, each researcher also has his/her different academic stances in their preferences about academic freedom and academic entrepreneurship. Understanding the behavior of academic researchers will contribute to nurture young researchers, to improve the standard of research and education as well as to boost collaboration in academia-industry. In particular, as open innovation is increasingly in need of the involvement of university researchers, to establish a successful approach to entice researchers into enterprises’ research, companies must comprehend the behavior of university researchers who have multiple complex motivations. The paper explores academic researchers' behaviors through optimizing their utility functions, i.e. the satisfaction obtained by their research outputs. This paper characterizes these outputs as the results of researchers' 3C: Competence (the ability to implement the research, Commitment (the effort to do the research, and Contribution (finding meaning in the research. Most of the previous research utilized the empirical methods to study researcher's motivation. Without adopting economic theory into the analysis, the past literature could not offer a deeper understanding of researcher's behavior. Our contribution is important both conceptually and practically because it provides the first theoretical framework to study the mechanism of researcher's behavior. Keywords: Academia-Industry, researcher behavior, ulrich model’s 3C.

  7. Testing the Validity of a Cognitive Behavioral Model for Gambling Behavior.

    Science.gov (United States)

    Raylu, Namrata; Oei, Tian Po S; Loo, Jasmine M Y; Tsai, Jung-Shun

    2016-06-01

    Currently, cognitive behavioral therapies appear to be one of the most studied treatments for gambling problems and studies show it is effective in treating gambling problems. However, cognitive behavior models have not been widely tested using statistical means. Thus, the aim of this study was to test the validity of the pathways postulated in the cognitive behavioral theory of gambling behavior using structural equation modeling (AMOS 20). Several questionnaires assessing a range of gambling specific variables (e.g., gambling urges, cognitions and behaviors) and gambling correlates (e.g., psychological states, and coping styles) were distributed to 969 participants from the community. Results showed that negative psychological states (i.e., depression, anxiety and stress) only directly predicted gambling behavior, whereas gambling urges predicted gambling behavior directly as well as indirectly via gambling cognitions. Avoidance coping predicted gambling behavior only indirectly via gambling cognitions. Negative psychological states were significantly related to gambling cognitions as well as avoidance coping. In addition, significant gender differences were also found. The results provided confirmation for the validity of the pathways postulated in the cognitive behavioral theory of gambling behavior. It also highlighted the importance of gender differences in conceptualizing gambling behavior.

  8. Model of Collective Fish Behavior with Hydrodynamic Interactions

    Science.gov (United States)

    Filella, Audrey; Nadal, François; Sire, Clément; Kanso, Eva; Eloy, Christophe

    2018-05-01

    Fish schooling is often modeled with self-propelled particles subject to phenomenological behavioral rules. Although fish are known to sense and exploit flow features, these models usually neglect hydrodynamics. Here, we propose a novel model that couples behavioral rules with far-field hydrodynamic interactions. We show that (1) a new "collective turning" phase emerges, (2) on average, individuals swim faster thanks to the fluid, and (3) the flow enhances behavioral noise. The results of this model suggest that hydrodynamic effects should be considered to fully understand the collective dynamics of fish.

  9. Modeling Chaotic Behavior of Chittagong Stock Indices

    Directory of Open Access Journals (Sweden)

    Shipra Banik

    2012-01-01

    Full Text Available Stock market prediction is an important area of financial forecasting, which attracts great interest to stock buyers and sellers, stock investors, policy makers, applied researchers, and many others who are involved in the capital market. In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. Paying attention to the applied econometric noises because our considered series are time series, we predict Chittagong stock indices for the period from January 1, 2005 to May 5, 2011. We have used well-known models such as, the genetic algorithm (GA model and the adaptive network fuzzy integrated system (ANFIS model as soft computing forecasting models. Very widely used forecasting models in applied time series econometrics, namely, the generalized autoregressive conditional heteroscedastic (GARCH model is considered as time series model. Our findings have revealed that the use of soft computing models is more successful than the considered time series model.

  10. Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research.

    Science.gov (United States)

    Spruijt-Metz, Donna; Hekler, Eric; Saranummi, Niilo; Intille, Stephen; Korhonen, Ilkka; Nilsen, Wendy; Rivera, Daniel E; Spring, Bonnie; Michie, Susan; Asch, David A; Sanna, Alberto; Salcedo, Vicente Traver; Kukakfa, Rita; Pavel, Misha

    2015-09-01

    Adverse and suboptimal health behaviors and habits are responsible for approximately 40 % of preventable deaths, in addition to their unfavorable effects on quality of life and economics. Our current understanding of human behavior is largely based on static "snapshots" of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social, personal, and environmental states. This paper first discusses how new technologies (i.e., mobile sensors, smartphones, ubiquitous computing, and cloud-enabled processing/computing) and emerging systems modeling techniques enable the development of new, dynamic, and empirical models of human behavior that could facilitate just-in-time adaptive, scalable interventions. The paper then describes concrete steps to the creation of robust dynamic mathematical models of behavior including: (1) establishing "gold standard" measures, (2) the creation of a behavioral ontology for shared language and understanding tools that both enable dynamic theorizing across disciplines, (3) the development of data sharing resources, and (4) facilitating improved sharing of mathematical models and tools to support rapid aggregation of the models. We conclude with the discussion of what might be incorporated into a "knowledge commons," which could help to bring together these disparate activities into a unified system and structure for organizing knowledge about behavior.

  11. German taxi drivers' experiences and expressions of driving anger: Are the driving anger scale and the driving anger expression inventory valid measures?

    Science.gov (United States)

    Brandenburg, Stefan; Oehl, Michael; Seigies, Kristin

    2017-11-17

    The objective of this article was 2-fold: firstly, we wanted to examine whether the original Driving Anger Scale (DAS) and the original Driving Anger Expression Inventory (DAX) apply to German professional taxi drivers because these scales have previously been given to professional and particularly to nonprofessional drivers in different countries. Secondly, we wanted to examine possible differences in driving anger experience and expression between professional German taxi drivers and nonprofessional German drivers. We applied German versions of the DAS, the DAX, and the State-Trait Anger Expression Inventory (STAXI) to a sample of 138 professional German taxi drivers. We then compared their ratings to the ratings of a sample of 1,136 nonprofessional German drivers (Oehl and Brandenburg n.d. ). Regarding our first objective, confirmatory factor analysis shows that the model fit of the DAS is better for nonprofessional drivers than for professional drivers. The DAX applies neither to professional nor to nonprofessional German drivers properly. Consequently, we suggest modified shorter versions of both scales for professional drivers. The STAXI applies to both professional and nonprofessional drivers. With respect to our second objective, we show that professional drivers experience significantly less driving anger than nonprofessional drivers, but they express more driving anger. We conclude that the STAXI can be applied to professional German taxi drivers. In contrast, for the DAS and the DAX we found particular shorter versions for professional taxi drivers. Especially for the DAX, most statements were too strong for German drivers to agree to. They do not show behaviors related to driving anger expression as they are described in the DAX. These problems with the original American DAX items are in line with several other studies in different countries. Future investigations should examine whether (professional) drivers from further countries express their anger

  12. Modeling Land-Use Decision Behavior with Bayesian Belief Networks

    Directory of Open Access Journals (Sweden)

    Inge Aalders

    2008-06-01

    Full Text Available The ability to incorporate and manage the different drivers of land-use change in a modeling process is one of the key challenges because they are complex and are both quantitative and qualitative in nature. This paper uses Bayesian belief networks (BBN to incorporate characteristics of land managers in the modeling process and to enhance our understanding of land-use change based on the limited and disparate sources of information. One of the two models based on spatial data represented land managers in the form of a quantitative variable, the area of individual holdings, whereas the other model included qualitative data from a survey of land managers. Random samples from the spatial data provided evidence of the relationship between the different variables, which I used to develop the BBN structure. The model was tested for four different posterior probability distributions, and results showed that the trained and learned models are better at predicting land use than the uniform and random models. The inference from the model demonstrated the constraints that biophysical characteristics impose on land managers; for older land managers without heirs, there is a higher probability of the land use being arable agriculture. The results show the benefits of incorporating a more complex notion of land managers in land-use models, and of using different empirical data sources in the modeling process. Future research should focus on incorporating more complex social processes into the modeling structure, as well as incorporating spatio-temporal dynamics in a BBN.

  13. Rasmussen's model of human behavior in laparoscopy training.

    Science.gov (United States)

    Wentink, M; Stassen, L P S; Alwayn, I; Hosman, R J A W; Stassen, H G

    2003-08-01

    Compared to aviation, where virtual reality (VR) training has been standardized and simulators have proven their benefits, the objectives, needs, and means of VR training in minimally invasive surgery (MIS) still have to be established. The aim of the study presented is to introduce Rasmussen's model of human behavior as a practical framework for the definition of the training objectives, needs, and means in MIS. Rasmussen distinguishes three levels of human behavior: skill-, rule-, and knowledge-based behaviour. The training needs of a laparoscopic novice can be determined by identifying the specific skill-, rule-, and knowledge-based behavior that is required for performing safe laparoscopy. Future objectives of VR laparoscopy trainers should address all three levels of behavior. Although most commercially available simulators for laparoscopy aim at training skill-based behavior, especially the training of knowledge-based behavior during complications in surgery will improve safety levels. However, the cost and complexity of a training means increases when the training objectives proceed from the training of skill-based behavior to the training of complex knowledge-based behavior. In aviation, human behavior models have been used successfully to integrate the training of skill-, rule-, and knowledge-based behavior in a full flight simulator. Understanding surgeon behavior is one of the first steps towards a future full-scale laparoscopy simulator.

  14. Modeling User Behavior and Attention in Search

    Science.gov (United States)

    Huang, Jeff

    2013-01-01

    In Web search, query and click log data are easy to collect but they fail to capture user behaviors that do not lead to clicks. As search engines reach the limits inherent in click data and are hungry for more data in a competitive environment, mining cursor movements, hovering, and scrolling becomes important. This dissertation investigates how…

  15. Modeling cultural behavior for military virtual training

    NARCIS (Netherlands)

    Kerbusch, P.; Schram, J.; Bosch, K. van den

    2011-01-01

    Soldiers on mission in areas with unfamiliar cultures must be able to take into account the norms of the local culture when assessing a situation, and must be able to adapt their behavior accordingly. Innovative technologies provide opportunity to train the required skills in an interactive and

  16. Modeling Cultural Behavior for Military Virtual Training

    NARCIS (Netherlands)

    Bosch, K. van den; Kerbusch, P.J.M.; Schram, J.

    2012-01-01

    Soldiers on mission in areas with unfamiliar cultures must be able to take into account the norms of the local culture when assessing a situation, and must be able to adapt their behavior accordingly. Innovative technologies provide opportunity to train the required skills in an interactive and

  17. Modeling Behavior and Variation for Crowd Animation

    Science.gov (United States)

    2009-08-01

    characters and environments with- out having to design new behavior graphs. For example, we generated animations for a skateboarder and a horse using...also have motion data for a skateboarder and a horse. Their graphs are similar to the one in Figure 3.3 right. For the skateboarder , there are five

  18. Integration of Theory of Planned Behavior and Norm Activation Model on Student Behavior Model Using Cars for Traveling to Campus

    Directory of Open Access Journals (Sweden)

    Setiawan, R.

    2014-01-01

    Full Text Available Although there are clear environmental, economic, and social drawbacks in using private vehicles, students still choose cars to get to campus. This study reports an investigation of psychological factors influencing this behavior from the perspective of the Theory of Planned Behavior and Norm Activation Model. Students from three different university campuses in Surabaya, Indonesia, (n = 312 completed a survey on their car commuting behavior. Results indicated that perceived behavioral control and personal norm were the strongest factors that influence behavioral intention. Attitude, subjective norm, perceived behavioral control, and personal norm explain 62.7% variance of the behavioral intention. In turn, behavioral intention explains 42.5% of the variance of the actual car use. Implications of these findings are that in order to alter the use of car, university should implement both structural and psychological interventions. Effective interventions should be designed to raise the awareness of negative aspects of car use.

  19. Gap Acceptance Behavior Model for Non-signalized

    OpenAIRE

    Fajaruddin Bin Mustakim

    2015-01-01

    The paper proposes field studies that were performed to determine the critical gap on the multiple rural roadways Malaysia, at non-signalized T-intersection by using The Raff and Logic Method. Critical gap between passenger car and motorcycle have been determined.   There are quite number of studied doing gap acceptance behavior model for passenger car however still few research on gap acceptance behavior model for motorcycle. Thus in this paper, logistic regression models were developed to p...

  20. Social Cognitive Antecedents of Fruit and Vegetable Consumption in Truck Drivers: A Sequential Mediation Analysis.

    Science.gov (United States)

    Hamilton, Kyra; Vayro, Caitlin; Schwarzer, Ralf

    2015-01-01

    To examine a mechanism by which social cognitive factors may predict fruit and vegetable consumption in long-haul truck drivers. Dietary self-efficacy, positive outcome expectancies, and intentions were assessed in 148 Australian truck drivers, and 1 week later they reported their fruit and vegetable consumption. A theory-guided sequential mediation model was specified that postulated self-efficacy and intention as mediators between outcome expectancies and behavior. The hypothesized model was confirmed. A direct effect of outcome expectancies was no longer present when mediators were included, and all indirect effects were significant, including the 2-mediator chain (β = .15; P role of outcome expectancies and self-efficacy are important to consider for understanding and predicting healthy eating intentions in truck drivers. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

  1. An extended heterogeneous car-following model accounting for anticipation driving behavior and mixed maximum speeds

    Science.gov (United States)

    Sun, Fengxin; Wang, Jufeng; Cheng, Rongjun; Ge, Hongxia

    2018-02-01

    The optimal driving speeds of the different vehicles may be different for the same headway. In the optimal velocity function of the optimal velocity (OV) model, the maximum speed vmax is an important parameter determining the optimal driving speed. A vehicle with higher maximum speed is more willing to drive faster than that with lower maximum speed in similar situation. By incorporating the anticipation driving behavior of relative velocity and mixed maximum speeds of different percentages into optimal velocity function, an extended heterogeneous car-following model is presented in this paper. The analytical linear stable condition for this extended heterogeneous traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulted from the cooperation between anticipation driving behavior and heterogeneous maximum speeds in the optimal velocity function. The analytical and numerical results all demonstrate that strengthening driver's anticipation effect can improve the stability of heterogeneous traffic flow, and increasing the lowest value in the mixed maximum speeds will result in more instability, but increasing the value or proportion of the part already having higher maximum speed will cause different stabilities at high or low traffic densities.

  2. Modeling electric bicycle's lane-changing and retrograde behaviors

    Science.gov (United States)

    Tang, Tie-Qiao; Luo, Xiao-Feng; Zhang, Jian; Chen, Liang

    2018-01-01

    Recently, electric bicycle (EB) has been one important traffic tool due to its own merits. However, EB's motion behaviors (especially at a signalized/non-signalized intersection) are more complex than those of vehicle since it always has lane-changing and retrograde behaviors. In this paper, we propose a model to explore EB's lane-changing and retrograde behaviors on a road with a signalized intersection. The numerical results indicate that the proposed model can qualitatively describe each EB's lane-changing and retrograde behaviors near a signalized intersection, and that lane-changing and retrograde behaviors have prominent impacts on the signalized intersection (i.e., prominent jams and congestions occur). The above results show that EB should be controlled as a vehicle, i.e., lane-changing and retrograde behaviors at a signalized intersection should strictly be prohibited to improve the operational efficiency and traffic safety at the signalized intersection.

  3. Examination of Supplemental Driver Training and Online Basic Driver Education

    Science.gov (United States)

    2012-06-01

    This report describes supplemental driver training programs and online basic driver education. It coves supplemental driver training that : focused on knowledge and skills beyond those normally found in traditional driver education delivered in the U...

  4. Evaluating Older Drivers' Skills

    Science.gov (United States)

    2013-05-01

    Research has demonstrated that older drivers pose a higher risk of involvement in fatal crashes at intersections than : younger drivers. Age-triggered restrictions are problematic as research shows that the majority of older people : have unimpaired ...

  5. Online driver's license renewal.

    Science.gov (United States)

    2015-09-01

    The Kentucky Department of Vehicle Regulation is exploring the possibility of developing and implementing online : drivers license renewal. The objective of this project was to: 1) evaluate online drivers license and REAL ID renewal : programs ...

  6. Performance of fire behavior fuel models developed for the Rothermel Surface Fire Spread Model

    Science.gov (United States)

    Robert Ziel; W. Matt Jolly

    2009-01-01

    In 2005, 40 new fire behavior fuel models were published for use with the Rothermel Surface Fire Spread Model. These new models are intended to augment the original 13 developed in 1972 and 1976. As a compiled set of quantitative fuel descriptions that serve as input to the Rothermel model, the selected fire behavior fuel model has always been critical to the resulting...

  7. Modeling pedestrian shopping behavior using principles of bounded rationality: model comparison and validation

    NARCIS (Netherlands)

    Zhu, W.; Timmermans, H.J.P.

    2011-01-01

    Models of geographical choice behavior have been dominantly based on rational choice models, which assume that decision makers are utility-maximizers. Rational choice models may be less appropriate as behavioral models when modeling decisions in complex environments in which decision makers may

  8. Impacts of Changing Climatic Drivers and Land use features on Future Stormwater Runoff in the Northwest Florida Basin: A Large-Scale Hydrologic Modeling Assessment

    Science.gov (United States)

    Khan, M.; Abdul-Aziz, O. I.

    2017-12-01

    Potential changes in climatic drivers and land cover features can significantly influence the stormwater budget in the Northwest Florida Basin. We investigated the hydro-climatic and land use sensitivities of stormwater runoff by developing a large-scale process-based rainfall-runoff model for the large basin by using the EPA Storm Water Management Model (SWMM 5.1). Climatic and hydrologic variables, as well as land use/cover features were incorporated into the model to account for the key processes of coastal hydrology and its dynamic interactions with groundwater and sea levels. We calibrated and validated the model by historical daily streamflow observations during 2009-2012 at four major rivers in the basin. Downscaled climatic drivers (precipitation, temperature, solar radiation) projected by twenty GCMs-RCMs under CMIP5, along with the projected future land use/cover features were also incorporated into the model. The basin storm runoff was then simulated for the historical (2000s = 1976-2005) and two future periods (2050s = 2030-2059, and 2080s = 2070-2099). Comparative evaluation of the historical and future scenarios leads to important guidelines for stormwater management in Northwest Florida and similar regions under a changing climate and environment.

  9. Understanding and Modeling Freight Stakeholder Behavior

    Science.gov (United States)

    2012-04-01

    This project developed a conceptual model of private-sector freight stakeholder decisions and interactions for : forecasting freight demands in response to key policy variables. Using East Central Wisconsin as a study area, empirical : models were de...

  10. eSPEM - A SPEM Extension for Enactable Behavior Modeling

    Science.gov (United States)

    Ellner, Ralf; Al-Hilank, Samir; Drexler, Johannes; Jung, Martin; Kips, Detlef; Philippsen, Michael

    OMG's SPEM - by means of its (semi-)formal notation - allows for a detailed description of development processes and methodologies, but can only be used for a rather coarse description of their behavior. Concepts for a more fine-grained behavior model are considered out of scope of the SPEM standard and have to be provided by other standards like BPDM/BPMN or UML. However, a coarse granularity of the behavior model often impedes a computer-aided enactment of a process model. Therefore, in this paper we present eSPEM, an extension of SPEM, that is based on the UML meta-model and focused on fine-grained behavior and life-cycle modeling and thereby supports automated enactment of development processes.

  11. Developing robotic behavior using a genetic programming model

    International Nuclear Information System (INIS)

    Pryor, R.J.

    1998-01-01

    This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

  12. A simplified model of choice behavior under uncertainty

    Directory of Open Access Journals (Sweden)

    Ching-Hung Lin

    2016-08-01

    Full Text Available The Iowa Gambling Task (IGT has been standardized as a clinical assessment tool (Bechara, 2007. Nonetheless, numerous research groups have attempted to modify IGT models to optimize parameters for predicting the choice behavior of normal controls and patients. A decade ago, most researchers considered the expected utility (EU model (Busemeyer and Stout, 2002 to be the optimal model for predicting choice behavior under uncertainty. However, in recent years, studies have demonstrated the prospect utility (PU models (Ahn et al., 2008 to be more effective than the EU models in the IGT. Nevertheless, after some preliminary tests, we propose that Ahn et al. (2008 PU model is not optimal due to some incompatible results between our behavioral and modeling data. This study aims to modify Ahn et al. (2008 PU model to a simplified model and collected 145 subjects’ IGT performance as the benchmark data for comparison. In our simplified PU model, the best goodness-of-fit was found mostly while α approaching zero. More specifically, we retested the key parameters α, λ , and A in the PU model. Notably, the power of influence of the parameters α, λ, and A has a hierarchical order in terms of manipulating the goodness-of-fit in the PU model. Additionally, we found that the parameters λ and A may be ineffective when the parameter α is close to zero in the PU model. The present simplified model demonstrated that decision makers mostly adopted the strategy of gain-stay-loss-shift rather than foreseeing the long-term outcome. However, there still have other behavioral variables that are not well revealed under these dynamic uncertainty situations. Therefore, the optimal behavioral models may not have been found. In short, the best model for predicting choice behavior under dynamic-uncertainty situations should be further evaluated.

  13. Animal Models of Compulsive Eating Behavior

    OpenAIRE

    Matteo Di Segni; Enrico Patrono; Loris Patella; Stefano Puglisi-Allegra; Rossella Ventura

    2014-01-01

    Eating disorders are multifactorial conditions that can involve a combination of genetic, metabolic, environmental, and behavioral factors. Studies in humans and laboratory animals show that eating can also be regulated by factors unrelated to metabolic control. Several studies suggest a link between stress, access to highly palatable food, and eating disorders. Eating “comfort foods” in response to a negative emotional state, for example, suggests that some individuals overeat to self-medica...

  14. System Behavior Models: A Survey of Approaches

    Science.gov (United States)

    2016-06-01

    OF FIGURES Spiral Model .................................................................................................3 Figure 1. Approaches in... spiral model was chosen for researching and structuring this thesis, shown in Figure 1. This approach allowed multiple iterations of source material...applications and refining through iteration. 3 Spiral Model Figure 1. D. SCOPE The research is limited to a literature review, limited

  15. A Culture-Behavior-Brain Loop Model of Human Development.

    Science.gov (United States)

    Han, Shihui; Ma, Yina

    2015-11-01

    Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Ontology and modeling patterns for state-based behavior representation

    Science.gov (United States)

    Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.; hide

    2015-01-01

    This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.

  17. Modeling detour behavior of pedestrian dynamics under different conditions

    Science.gov (United States)

    Qu, Yunchao; Xiao, Yao; Wu, Jianjun; Tang, Tao; Gao, Ziyou

    2018-02-01

    Pedestrian simulation approach has been widely used to reveal the human behavior and evaluate the performance of crowd evacuation. In the existing pedestrian simulation models, the social force model is capable of predicting many collective phenomena. Detour behavior occurs in many cases, and the important behavior is a dominate factor of the crowd evacuation efficiency. However, limited attention has been attracted for analyzing and modeling the characteristics of detour behavior. In this paper, a modified social force model integrated by Voronoi diagram is proposed to calculate the detour direction and preferred velocity. Besides, with the consideration of locations and velocities of neighbor pedestrians, a Logit-based choice model is built to describe the detour direction choice. The proposed model is applied to analyze pedestrian dynamics in a corridor scenario with either unidirectional or bidirectional flow, and a building scenario in real-world. Simulation results show that the modified social force model including detour behavior could reduce the frequency of collision and deadlock, increase the average speed of the crowd, and predict more practical crowd dynamics with detour behavior. This model can also be potentially applied to understand the pedestrian dynamics and design emergent management strategies for crowd evacuations.

  18. Older drivers : a review.

    NARCIS (Netherlands)

    Hakamies-Blomqvist, L. Sirén, A. & Davidse, R.J.

    2004-01-01

    The proportion of senior citizens (aged 65+) will grow from about 15 per cent in the year 2000 to about 30 per cent in the year 2050. The share of older drivers in the driver population will grow even faster because of increasing licensing rates among the ageing population. Older drivers do not have

  19. A hierarchical modeling of information seeking behavior of school ...

    African Journals Online (AJOL)

    The aim of this study was to investigate the information seeking behavior of school teachers in the public primary schools of rural areas of Nigeria and to draw up a model of their information-seeking behavior. A Cross-sectional survey design research was employed to carry out the research. Findings showed that the ...

  20. A Behavioral Decision Making Modeling Approach Towards Hedging Services

    NARCIS (Netherlands)

    Pennings, J.M.E.; Candel, M.J.J.M.; Egelkraut, T.M.

    2003-01-01

    This paper takes a behavioral approach toward the market for hedging services. A behavioral decision-making model is developed that provides insight into how and why owner-managers decide the way they do regarding hedging services. Insight into those choice processes reveals information needed by