WorldWideScience

Sample records for modeling driver behavior

  1. 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.

  2. 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.

  3. 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...

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Ching-Han Yang

    2018-03-01

    Full Text Available 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. Improving driver safety with behavioral countermeasures.

    Science.gov (United States)

    2011-09-30

    "The purpose of this project was to provide MDOT with insight regarding the effectiveness of potential implementations of behavioral countermeasures for increasing driver safety in Michigan. The Center for Driver Evaluation, Education, and Research a...

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. Determinants of seat belt use among drivers in Sabzevar, Iran: a comparison of theory of planned behavior and health belief model.

    Science.gov (United States)

    Ali, Mehri; Haidar, Nadrian; Ali, Morowatisharifabad Mohammad; Maryam, Akolechy

    2011-02-01

    Although seat belt use can significantly decrease the risk of injury, few car drivers make use of seat belts in Iran. The aim of this study was to test the utility and efficiencyof the theory of planned behavior (TPB) and the health beliefmodel (HBM) in predicting intention to use a seat belt among car drivers in Sabzevar, Iran. A cross-sectional, correlational design was employed. Cluster sampling was used to recruit 340 drivers to participate in the study. A self-administered questionnaire was applied to investigate variables of interest. Reliability and validity of the instruments were examined. The statistical analyses of the data included t test, one-way analysis of variance (ANOVA), bivariate correlation, and stepwise regression. All TPB and HBM variables were related to intention to use a seat belt in car drivers. All TPB (perceived behavioral control, subjective norms, and attitude) and HBM (perceived susceptibility and severity, benefits and barriers, and cues to action) variables were statistically significant predictors of seat belt use intention and accounted for 37.9 and 15.4 percent of the variation, respectively. Our results showed that the rate of seat belt use in Iran as a developing country is very low. Thus, developing and implementing effective interventional programs in order to promote seat belt use among car drivers is recommended. The findings of this study provide preliminary support for the TPB model as a more effective framework than HBM for examining seat belt use in car drivers. Our results demonstrated that TPB has greater predictive utility than HBM in seat belt use intention.

  18. Driver behavior at urban roads in China

    NARCIS (Netherlands)

    Li, J.; van Zuylen, H.J.; van der Horst, E.

    2014-01-01

    Driver behavior in China shows remarkable differences from that in western countries. In this study, six focus groups were organized to investigate Chinese drivers’ attitudes, expectations, intended actions, their preferences, and habits in different situations in urban areas. The outcomes show that

  19. 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.

  20. 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.

  1. Prediction of helmet use among Iranian motorcycle drivers: an application of the health belief model and the theory of planned behavior.

    Science.gov (United States)

    Aghamolaei, Teamur; Tavafian, Sedigheh Sadat; Madani, Abdoulhossain

    2011-06-01

    The aim of this study was to investigate the predictors of self-reported motorcycle helmet use in a sample of motorcycle riders in Bandar Abbas, Iran. The theory of planed behavior and the health belief model served as the conceptual framework for the study. In total, 221 male motorcycle drivers participated in this cross-sectional study. A self-administered questionnaire, including demographic characteristics and items related to both the theory of planned behavior and the health belief model constructs, was used to collect data. The mean age of the subjects was 26.8 years (SD = 7.2). Multiple regression analyses revealed that perceived behavioral control significantly predicted the intention to use a motorcycle helmet (R(2)= 0.47, F = 19.5, p action significantly predicted motorcycle helmet use (R(2)= 0.35, F = 19.5, p action were the most likely to use a motorcycle helmet.

  2. 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

  3. THE DIFFERENCES OF DRIVING BEHAVIOR AMONG DIFFERENT DRIVER AGE GROUPS AT SIGNALIZED INTERSECTIONS

    Directory of Open Access Journals (Sweden)

    Jian John LU, Ph.D., P.E.

    2000-01-01

    Full Text Available Over the past few years the population of older drivers has substantially increased across the United States. Older drivers are a group of special interest because of their potential age-related deficiencies. It is essential to understand their driving behavior and adjust the conditions of roadway systems according to their requirements. Likewise, driving behavior of older drivers needs to be considered in order to adequately estimate capacities at intersections. In the past few years, research projects were performed by the University of South Florida to analyze the differences of driving behavior among different driver age groups. Typically, the driving behavior of older drivers was evaluated by analyzing their start-up lost time and saturation headway at signalized intersections as compared to young and mid-age driver groups. Research results were based on data collected from signalized intersections with different land-use types. These intersections are located in west and central Florida where the elderly population has been increasing rapidly in recent years. From the results it was found that the presence of older drivers significantly reduced intersection capacity at all study sites because of their higher lost times and lower saturation flow rates. Therefore, driving behavior of older drivers should be considered in designing intersections located in places with a significant older driver population. In the research, models were developed to predict start-up lost time and saturation headway values generated by older drivers. Then, the variation in capacities with an increasing percentage of older drivers in the traffic stream was modeled. Finally, adjustment factors for different percentages of older drivers were developed to adjust intersection capacity. These factors are believed to account for the presence of older drivers in the traffic stream. The adjustment factors may be used in capacity analysis and design procedures for

  4. Influencing Driver Behavior on Nigerian Roads | Ogwude | Journal ...

    African Journals Online (AJOL)

    This paper argues that influencing driver behavior is a major strategy for improving safe road usage in Nigeria. It uses the findings of a recent study conducted by the author to show the facets of driver behavior which contribute to incidence of road crashes and should therefore be controlled. As these factors derive from the ...

  5. 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

    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...... 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......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...

  6. Public Transportation Driver's Aggressive Behavior in Highly Traffic Jam

    OpenAIRE

    Triany, Novia; Prabowo, Hendro

    2008-01-01

    The aim of this study is to know the description of public transportation driver aggresive behavior and factors that might be influencing that behavior. This study is a case study with single subject with interview and observation as the method pf the study and helped by some of research tools such as map, graphic test and camera. The participant of this study is public transportation driver Bekasi city. The result shows that factors influencing the aggresive behavior are external and interna...

  7. 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.

  8. Driver eye-scanning behavior at intersections at night.

    Science.gov (United States)

    2009-10-01

    This research project analyzed drivers eye scanning behavior at night when approaching signalized : and unsignalized intersections using the data from a head-mounted eye-tracking system during open road : driving on a prescribed route. During the ...

  9. 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...

  10. Evidence that implementation intentions reduce drivers' speeding behavior: testing a new intervention to change driver behavior.

    Science.gov (United States)

    Brewster, Sarah E; Elliott, Mark A; Kelly, Steve W

    2015-01-01

    Implementation intentions have the potential to break unwanted habits and help individuals behave in line with their goal intentions. We tested the effects of implementation intentions in the context of drivers' speeding behavior. A randomized controlled design was used. Speeding behavior, goal intentions and theoretically derived motivational pre-cursors of goal intentions were measured at both baseline and follow-up (one month later) using self-report questionnaires. Immediately following the baseline questionnaire, the experimental (intervention) group (N=117) specified implementation intentions using a volitional help sheet, which required the participants to link critical situations in which they were tempted to speed with goal-directed responses to resist the temptation. The control group (N=126) instead received general information about the risks of speeding. In support of the hypotheses, the experimental group reported exceeding the speed limit significantly less often at follow-up than did the control group. This effect was specific to 'inclined abstainers' (i.e., participants who reported speeding more than they intended to at baseline and were therefore motivated to reduce their speeding) and could not be attributed to any changes in goal intentions to speed or any other measured motivational construct. Also in line with the hypotheses, implementation intentions attenuated the past-subsequent speeding behavior relationship and augmented the goal intention - subsequent speeding behavior relationship. The findings imply that implementation intentions are effective at reducing speeding and that they do so by weakening the effect of habit, thereby helping drivers to behave in accordance with their existing goal intentions. The volitional help sheet used in this study is an effective tool for promoting implementation intentions to reduce speeding. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. 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.

  12. 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...

  13. Subjective experienced health as a driver of health care behavior

    NARCIS (Netherlands)

    Bloem, S.; Stalpers, J.

    2012-01-01

    This paper describes the key role of the subjective experience of health as the driver of health related behavior. Individuals vary greatly in terms of behaviors related to health. Insights into these interindividual differences are of great importance for all parties involved in health care,

  14. 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.

  15. Analysis of driver merging behavior at lane drops on freeways.

    Science.gov (United States)

    2013-12-01

    Lane changing assistance systems advise drivers on safe gaps for making mandatory lane changes at lane drops. In this : study, such a system was developed using a Bayes classifier and a decision tree to model lane changes. Detailed vehicle : trajecto...

  16. 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.

  17. 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

    The Driver Behavior Questionnaire (DBQ) is one of the most widely used instruments for measuring selfreported driving behaviors. Despite the popularity of the DBQ, the applicability of the DBQ in different driver groups has remained mostly unexamined. The present study measured aberrant driving...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. How do attitudes, personality traits, and driver behaviors relate to pedestrian behaviors?: A Turkish case.

    Science.gov (United States)

    Şimşekoğlu, Özlem

    2015-01-01

    The present study aimed to investigate the role of pedestrian attitudes and personality traits (social conformity and empathy) on pedestrian behaviors in a Turkish sample. An equally important aim of the study was to examine the association between pedestrian and driver behaviors. The sample included 289 road users including pedestrians and drivers (169 females and 120 males). The participants' age ranged from 15 to 78 years (M = 32.00, SD = 13.89). Data were collected using a self-administered questionnaire. A regression analysis showed that increased age, high level of satisfaction with traffic infrastructure and environment, safer attitudes toward pedestrian violations, and empathy were negatively related to risky pedestrian behaviors, whereas social conformity was positively related. Attitudes were the strongest predictor of pedestrian behaviors. In addition, bivariate correlation analysis showed that all dimensions of pedestrian and driver behaviors were positively correlated with each other, which indicates that a tendency to take risks remains the same regardless of the road user role (i.e., driver vs. pedestrian). Attitudes are strong predictors of pedestrian behaviors. A tendency to take risks as a pedestrian and as a driver is correlated. Results are discussed for their implications to traffic safety campaigns targeting increased pedestrian safety.

  4. Analysis of driver's characteristics on a curved road in a lattice model

    Science.gov (United States)

    Kaur, Ramanpreet; Sharma, Sapna

    2017-04-01

    The present paper investigates the effect of driver's behavior on the curved road via lattice hydrodynamic approach. The basic model for straight road is extended for the curved road and the characteristics of driver's behavior is incorporated in the lattice model. The extended model is investigated theoretically by the means of linear stability analysis and the effect of curved road and intensity of influence of driver's behavior on the traffic flow stability is examined. Through nonlinear stability analysis, the modified Korteweg-de Vries (MKdV) equation near the critical point is derived to describe the evolution properties of traffic density waves by applying the reductive perturbation method. Furthermore, the numerical simulation is carried out to validate the theoretical results which indicates that the curved road has a negative influence on the stability of the traffic flow. It is also seen that the traffic jam on a curved road can be suppressed efficiently via taking into account aggressive drivers.

  5. 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.

  6. Cellphone Legislation and Self-Reported Behaviors Among Subgroups of Adolescent U.S. Drivers.

    Science.gov (United States)

    Rudisill, Toni M; Smith, Gordon; Chu, Haitao; Zhu, Motao

    2018-02-26

    The relationship between cellphone use while driving legislation and self-reported adolescent driver behavior is poorly understood, especially across demographic subgroups. This study investigated the relationship between statewide cellphone legislation and cellphone use behaviors across adolescent driver subgroups, including age (16/17 vs. 18), sex, race/ethnicity (white non-Hispanic and others), and rurality (urban or rural). Data from the 2011-2014 Traffic Safety Culture Index Surveys were combined with state legislation. The outcomes were self-reported texting and handheld cellphone conversations. The exposure was the presence of a texting or handheld cellphone ban applicable to all drivers (i.e., universal) in the drivers' state of residence. A multilevel, modified Poisson regression model was used to estimate the risk of engaging in these behaviors. Approximately 34% of respondents reported to have driven while conversing, and 37% texted and drove in the 30 days before the survey. Universal handheld calling bans were associated with lower occurrences of cellphone conversations across all groups except rural drivers. Overall, handheld cellphone bans were associated with 55% lower (adjusted risk ratio .45, 95% confidence interval .32-.63) occurrences of cellphone conversations. However, universal texting bans were not associated with fewer texting behaviors in any subgroup. Universal handheld calling bans may discourage adolescents from engaging in handheld phone conversations, whereas universal texting bans may not fully discourage texting behaviors. More interventional or educational work is necessary, particularly addressing texting while driving. Copyright © 2018 The Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  7. Enhancing digital driver models: identification of distinct postural strategies used by drivers.

    Science.gov (United States)

    Kyung, Gyouhyung; Nussbaum, Maury A; Babski-Reeves, Kari L

    2010-03-01

    Driver workspace design and evaluation is, in part, based on assumed driving postures of users and determines several ergonomic aspects of a vehicle, such as reach, visibility and postural comfort. Accurately predicting and specifying standard driving postures, hence, are necessary to improve the ergonomic quality of the driver workspace. In this study, a statistical clustering approach was employed to reduce driving posture simulation/prediction errors, assuming that drivers use several distinct postural strategies when interacting with automobiles. 2-D driving postures, described by 16 joint angles, were obtained from 38 participants with diverse demographics (age, gender) and anthropometrics (stature, body mass) and in two vehicle classes (sedans and SUVs). Based on the proximity of joint angle sets, cluster analysis yielded three predominant postural strategies in each vehicle class (i.e. 'lower limb flexed', 'upper limb flexed' and 'extended'). Mean angular differences between clusters ranged from 3.8 to 52.4 degrees for the majority of joints, supporting the practical relevance of the distinct clusters. The existence of such postural strategies should be considered when utilising digital human models (DHMs) to enhance and evaluate driver workspace design ergonomically and proactively. STATEMENT OF RELEVANCE: This study identified drivers' distinct postural strategies, based on actual drivers' behaviours. Such strategies can facilitate accurate positioning of DHMs and hence help design ergonomic driver workspaces.

  8. Influence of roadway geometric elements on driver behavior when overtaking bicycles on rural roads

    Directory of Open Access Journals (Sweden)

    Jeremy R. Chapman

    2014-02-01

    Full Text Available The objective of this research was to determine what influence geometric design elements of roadway may have on driver behavior during the overtaking maneuver. This was part of a larger research effort to eliminate crashes (and the resulting fatalities and injuries between bicycles and motorized vehicles. The data collection process produced 1151 observations with approximately 40 different independent variables for each data point through direct observation, sensor logging, or derivation from other independent variables. Prior research by the authors developed a means to collect real-time field data through the use of a bicycle-mounted data collection system. The collected data was then used to model lateral clearance distance between vehicles and bicycles. The developed model confirmed field observations that the lateral clearance distance provided by drivers changes with vehicle speed and oncoming vehicle presence. These observations were presented by the authors previously. The model shows that driver behavior can be adjusted by the inclusion, or exclusion, of geometric elements. Evaluating roadways (or roadway designs based on this model will enable stakeholders to identify those roadway segments where a paved shoulder would prove an effective safety countermeasure. This research will also enable roadway designers to better identify during the design phase those roadway segments that should be constructed with a paved shoulder.

  9. 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.

  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. 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 ...

  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. 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

  14. 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.

  15. National Survey of US Long-Haul Truck Driver Health and Injury: health behaviors.

    Science.gov (United States)

    Birdsey, Jan; Sieber, W Karl; Chen, Guang X; Hitchcock, Edward M; Lincoln, Jennifer E; Nakata, Akinori; Robinson, Cynthia F; Sweeney, Marie H

    2015-02-01

    To compare selected health behaviors and body mass index (modifiable risk factors) of US long-haul truck drivers to the US working population by sex. The National Survey of US Long-Haul Truck Driver Health and Injury interviewed a nationally representative sample of long-haul truck drivers (n = 1265) at truck stops. Age-adjusted results were compared with national health surveys. Compared with US workers, drivers had significantly higher body mass index, current cigarette use, and pack-years of smoking; lower prevalence of annual influenza vaccination; and generally lower alcohol consumption. Physical activity level was low for most drivers, and 25% had never had their cholesterol levels tested. Working conditions common to long-haul trucking may create significant barriers to certain healthy behaviors; thus, transportation and health professionals should address the unique work environment when developing interventions for long-haul drivers.

  16. Sitting biomechanics, part II: optimal car driver's seat and optimal driver's spinal model.

    Science.gov (United States)

    Harrison, D D; Harrison, S O; Croft, A C; Harrison, D E; Troyanovich, S J

    2000-01-01

    Driving has been associated with signs and symptoms caused by vibrations. Sitting causes the pelvis to rotate backwards and the lumbar lordosis to reduce. Lumbar support and armrests reduce disc pressure and electromyographically recorded values. However, the ideal driver's seat and an optimal seated spinal model have not been described. To determine an optimal automobile seat and an ideal spinal model of a driver. Information was obtained from peer-reviewed scientific journals and texts, automotive engineering reports, and the National Library of Medicine. Driving predisposes vehicle operators to low-back pain and degeneration. The optimal seat would have an adjustable seat back incline of 100 degrees from horizontal, a changeable depth of seat back to front edge of seat bottom, adjustable height, an adjustable seat bottom incline, firm (dense) foam in the seat bottom cushion, horizontally and vertically adjustable lumbar support, adjustable bilateral arm rests, adjustable head restraint with lordosis pad, seat shock absorbers to dampen frequencies in the 1 to 20 Hz range, and linear front-back travel of the seat enabling drivers of all sizes to reach the pedals. The lumbar support should be pulsating in depth to reduce static load. The seat back should be damped to reduce rebounding of the torso in rear-end impacts. The optimal driver's spinal model would be the average Harrison model in a 10 degrees posterior inclining seat back angle.

  17. 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.

  18. 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.

  19. A heuristic finite-state model of the human driver in a car-following situation

    Science.gov (United States)

    Burnham, G. O.; Bekey, G. A.

    1976-01-01

    An approach to modeling human driver behavior in single-lane car following which is based on a finite-state decision structure is considered. The specific strategy at each point in the decision tree was obtained from observations of typical driver behavior. The synthesis of the decision logic is based on position and velocity thresholds and four states defined by regions in the phase plane. The performance of the resulting assumed intuitively logical model was compared with actual freeway data. The match of the model to the data was optimized by adapting the model parameters using a modified PARTAN algorithm. The results indicate that the heuristic model behavior matches actual car-following performance better during deceleration and constant velocity phases than during acceleration periods.

  20. 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.

  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. 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.

  3. 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.

  4. 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.

  5. 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...

  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. Road rage experience and behavior: vehicle, exposure, and driver factors.

    Science.gov (United States)

    Smart, Reginald; Stoduto, Gina; Mann, Robert; Adlaf, Edward

    2004-12-01

    Road rage has generated increasing public concern. Research has shown that victimization and perpetration of road rage is more common among males and younger drivers. We aimed to extend the understanding of determinants of road rage to driving exposure and vehicle factors, based on a 20022003 population survey of 1,631 regular drivers in Ontario, Canada. Regression analyses revealed that number of times drivers reported experiencing road rage in the previous 12 months was significantly greater for males, younger respondents, and those residing in Toronto. Also, victimization was significantly greater for drivers who did all their driving on busy roads and increased with number of kilometers driven on a typical week; however, type of vehicle driven was not significant. Number of times road rage perpetration was reported in the past 12 months was significantly greater for males, younger respondents, and those residing in Toronto, and lower for those in the Eastern and Northern region. Road rage perpetration increased significantly with number of weekly kilometers driven and was significantly greater for drivers who are always on busy roads and lower for those who never drive on busy roads, and higher for high-performance vehicle drivers. Even after controlling for driving exposure, road rage victimization and perpetration were highest for drivers in Toronto, where the pace of life may be more demanding. As expected, high-performance vehicle drivers reported more road rage perpetration. These individuals may experience more frustration when they are prevented from using the full performance capacities of their vehicles by crowded urban roadways.

  8. 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...

  9. 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...

  10. 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

  11. Knowledge of Traffic Laws and Drivers Behavior on the Roads of Tripoli City, Libya

    OpenAIRE

    Hussin A.M. Yahia; Amiruddin Ismail

    2014-01-01

    This study aimed to examine the knowledge of traffic rules and laws among a sample of drivers from the city of Tripoli and their behavior with respect to the same. A random sample of 416 drivers was selected from various regions for Tripoli, namely: Tajura, Abo Saleem, City Centre and Janzour and administered a questionnaire that would elicit and record their knowledge and behavior regarding road rules and regulations. The study revealed that traffic accidents are most affected by and positiv...

  12. 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

  13. 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.

  14. Transport company safety climate-The impact on truck driver behavior and crash involvement.

    Science.gov (United States)

    Sullman, Mark J M; Stephens, Amanda N; Pajo, Karl

    2017-04-03

    The present study investigated the relationships between safety climate and driving behavior and crash involvement. A total of 339 company-employed truck drivers completed a questionnaire that measured their perceptions of safety climate, crash record, speed choice, and aberrant driving behaviors (errors, lapses, and violations). Although there was no direct relationship between the drivers' perceptions of safety climate and crash involvement, safety climate was a significant predictor of engagement in risky driving behaviors, which were in turn predictive of crash involvement. This research shows that safety climate may offer an important starting point for interventions aimed at reducing risky driving behavior and thus fewer vehicle collisions.

  15. 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

  16. Investigating the role of behavioral factors in non-fatal accidents of urban and suburban driver

    Directory of Open Access Journals (Sweden)

    P. Azad

    2015-09-01

    Full Text Available Introduction: Road accidents are of the most important events, which cause death and injury of a large number of people and impose huge economic losses. According to previous studies, human factors are the main cause of traffic accidents. The purpose of this study was to investigate the role of behavioral factors in driving-related non-fatal accidents. Material and Method: The present analytical study was carried out among 150 drivers of urban and suburban transportation system in Yazd province. The research tool was Driver Behavior Questionnaire (DBQ which is consisted of two sections: demographic information and driving behavior. Result: 83/9 % of the participants reported to use safety belt nearly always. The highest deliberate violations, slips, and mistakes were belonged to drivers with age group of 18-25. Moreover, deliberate violations had a significant relationship with rage (P < 0.05. Survey of behavioral factors in terms of vehicle ownership type showed that “deliberate violations” and “slips and mistakes” high among personal bus drivers and state-owned bus drivers, respectively, which shows the significant association between these behavioral factors and ownership type. What is more, rates of deliberate and unintentional violations and slips were higher among those with a history of two times incidents (P < 0.004. Conclusion: The results revealed that behavioral factors such as age, type of vehicle ownership, and accident history played a significant role in occurrence of traffic accidents.

  17. Effect of a community-based pedestrian injury prevention program on driver yielding behavior at marked crosswalks.

    Science.gov (United States)

    Sandt, Laura S; Marshall, Stephen W; Rodriguez, Daniel A; Evenson, Kelly R; Ennett, Susan T; Robinson, Whitney R

    2016-08-01

    Few studies have comprehensively evaluated the effectiveness of multi-faceted interventions intended to improve pedestrian safety. "Watch for Me NC" is a multi-faceted, community-based pedestrian safety program that includes widespread media and public engagement in combination with enhanced law enforcement activities (i.e., police outreach and targeted pedestrian safety operations conducted at marked crosswalks) and low-cost engineering improvements at selected crossings. The purpose of this study was to estimate the effect of the law enforcement and engineering improvement components of the program on motor vehicle driver behavior, specifically in terms of increased driver yielding to pedestrians in marked crosswalks. The study used a pre-post design with a control group, comparing crossing locations receiving enforcement and low-cost engineering treatments (enhanced locations) with locations that did not (standard locations) to examine changes in driver yielding over a 6-month period from 2013 to 2014. A total of 24,941 drivers were observed in 11,817 attempted crossing events at 16 crosswalks in five municipalities that were participating in the program. Observations of real pedestrians attempting to use the crosswalks ("naturalistic" crossing) were supplemented by observations of trained research staff attempting the same crossings following an established protocol ("staged" crossings). Generalized estimating equations (GEE) were used to model driver yielding rates, accounting for repeated observations at the crossing locations and controlling other factors that affect driver behavior in yielding to pedestrians in marked crosswalks. At crossings that did not receive enhancements (targeted police operations or low-cost engineering improvements), driver yielding rates did not change from before to after the Watch for Me NC program. However, yielding rates improved significantly (between 4 and 7 percentage points on average) at the enhanced locations. This was

  18. Mathematical models assuming selective recruitment fitted to data for driver mortality and seat belt use in Japan.

    Science.gov (United States)

    Nakahara, Shinji; Kawamura, Takashi; Ichikawa, Masao; Wakai, Susumu

    2006-01-01

    Previous research has indicated that unbelted drivers are at higher risk of involvement in fatal crashes than belted drivers, suggesting selective recruitment that high-risk drivers are unlikely to become belt users. However, how the risk of involvement in fatal crashes among unbelted drivers varies according to the level of seat belt use among general drivers has yet to be clearly quantified. We, therefore, developed mathematical models describing the risk of fatal crashes in relation to seat belt use among the general public, and explored how these models fitted to changes in driver mortality and changes in observed seat belt use using Japanese data. Mortality data between 1979 and 1994 were obtained from vital statistics, and mortality data in the daytime and nighttime between 1980 and 2001 and belt use data between 1979 and 2001 were obtained from the National Police Agency. Regardless of the data set analyzed, exponential models, assuming that high-risk drivers would gradually become belt users in order of increasing risk as seat belt use among general motorists reached high levels, showed the best fit. Our models provide an insight into behavioral changes among high-risk drivers and support the selective recruitment hypothesis.

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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.

  4. A model of driver steering control incorporating the driver's sensing of steering torque

    Science.gov (United States)

    Kim, Namho; Cole, David J.

    2011-10-01

    Steering feel, or steering torque feedback, is widely regarded as an important aspect of the handling quality of a vehicle. Despite this, there is little theoretical understanding of its role. This paper describes an initial attempt to model the role of steering torque feedback arising from lateral tyre forces. The path-following control of a nonlinear vehicle model is implemented using a time-varying model predictive controller. A series of Kalman filters are used to represent the driver's ability to generate estimates of the system states from noisy sensory measurements, including the steering torque. It is found that under constant road friction conditions, the steering torque feedback reduces path-following errors provided the friction is sufficiently high to prevent frequent saturation of the tyres. When the driver model is extended to allow identification of, and adaptation to, a varying friction condition, it is found that the steering torque assists in the accurate identification of the friction condition. The simulation results give insight into the role of steering torque feedback arising from lateral tyre forces. The paper concludes with recommendations for further work.

  5. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve.

    Science.gov (United States)

    Li, Yi; Chen, Yuren

    2016-12-30

    To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers' perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers' perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers' perception-response time.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. A method to model anticipatory postural control in driver braking events

    NARCIS (Netherlands)

    Osth, J.; Eliasson, E.; Happee, R.; Brolin, K.

    2014-01-01

    Human body models (HBMs) for vehicle occupant simulations have recently been extended with active muscles and postural control strategies. Feedback control has been used to model occupant responses to autonomous braking interventions. However, driver postural responses during driver initiated

  12. Healthcare quality maturity assessment model based on quality drivers.

    Science.gov (United States)

    Ramadan, Nadia; Arafeh, Mazen

    2016-04-18

    Purpose - Healthcare providers differ in their readiness and maturity levels regarding quality and quality management systems applications. The purpose of this paper is to serve as a useful quantitative quality maturity-level assessment tool for healthcare organizations. Design/methodology/approach - The model proposes five quality maturity levels (chaotic, primitive, structured, mature and proficient) based on six quality drivers: top management, people, operations, culture, quality focus and accreditation. Findings - Healthcare managers can apply the model to identify the status quo, quality shortcomings and evaluating ongoing progress. Practical implications - The model has been incorporated in an interactive Excel worksheet that visually displays the quality maturity-level risk meter. The tool has been applied successfully to local hospitals. Originality/value - The proposed six quality driver scales appear to measure healthcare provider maturity levels on a single quality meter.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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,…

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. The Scent of Blood: A Driver of Human Behavior?

    Science.gov (United States)

    Moran, James K; Dietrich, Daniel R; Elbert, Thomas; Pause, Bettina M; Kübler, Lisa; Weierstall, Roland

    2015-01-01

    The scent of blood is potentially one of the most fundamental and survival-relevant olfactory cues in humans. This experiment tests the first human parameters of perceptual threshold and emotional ratings in men and women of an artificially simulated smell of fresh blood in contact with the skin. We hypothesize that this scent of blood, with its association with injury, danger, death, and nutrition will be a critical cue activating fundamental motivational systems relating to either predatory approach behavior or prey-like withdrawal behavior, or both. The results show that perceptual thresholds are unimodally distributed for both sexes, with women being more sensitive. Furthermore, both women and men's emotional responses to simulated blood scent divide strongly into positive and negative valence ratings, with negative ratings in women having a strong arousal component. For women, this split is related to the phase of their menstrual cycle and oral contraception (OC). Future research will investigate whether this split in both genders is context-dependent or trait-like.

  6. 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...

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve

    OpenAIRE

    Li, Yi; Chen, Yuren

    2016-01-01

    To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers’ perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers’ vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanica...

  15. 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

  16. 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

  17. 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.

  18. HIV risk behaviors differ by workplace stability among Mexican female sex workers with truck driver clientele.

    Science.gov (United States)

    Chen, Nadine E; Strathdee, Steffanie A; Rangel, Gudelia; Patterson, Thomas L; Uribe-Salas, Felipe J; Rosen, Perth; Villalobos, Jorge; Brouwer, Kimberly C

    2012-12-28

    In a study of female sex workers (FSW) servicing truck driver clients in Mexican border cities, we evaluated differences in HIV/STI risk behaviors by workplace. Cross-sectional study of FSW servicing truck drivers in Mexico: 100 from Nuevo Laredo (U.S. border); 100 from Ciudad Hidalgo (Guatemalan border). Main outcome was unstable workplace, defined as primary place of sex work in a public place (street, vehicle, gas station, etc.) vs. stable workplace (bar, brothel, and hotel). Logistic regression was used to identify correlates associated with trading sex at unstable workplaces in the last month. Of the FSW surveyed, 18% reported an unstable workplace. The majority of FSW surveyed were young (trend towards lower condom use self-efficacy scores (OR 0.8 per unit increase, 95%CI 0.7-1.0). On multivariate regression, unstable workplace was associated with having majority/all truck driver clientele, being surveyed in Nuevo Laredo, and decreased odds of ever having an HIV test. Among Mexican FSW with truck driver clients, providing safe indoor spaces for sex work may help facilitate public health interventions that improve HIV/STI and reproductive health outcomes.

  19. 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...... is formulated as a set partitioning problem. The LP relaxation of the set partitioning formulation of the TDRP possesses strong integer properties. The proposed model is therefore solved via the LP relaxation and Branch & Price. Starting with a small set of drivers and train tasks assigned to the drivers within...

  20. Detecting fingerprints of landslide drivers: A MaxEnt model

    Science.gov (United States)

    Convertino, M.; Troccoli, A.; Catani, F.

    2013-09-01

    Landslides are important geomorphic events that sculpt river basins by eroding hillslopes and providing sediments to coastal areas. However, landslides are also hazardous events for socio-ecological systems in river basins causing enormous biodiversity, economic, and social impacts. We propose a probabilistic spatially explicit model for the prediction of landslide patterns based on a maximum entropy principle model (MAXENT). The model inputs are the centers of mass of historical landslides and environmental variables at the basin scale. The model has only three parameters requiring calibration: the threshold for the network extraction, the trade-off factor between model complexity and accuracy, and the threshold of landslide susceptibility. The calibration on a subset of observations detects the environmental drivers and their relative importance for landslides. We employ the model in the Arno basin, Italy, selected because of its widespread landslide dynamics and the large availability of landslide observations. The model reproduces the size distribution and location of over 27,500 historical landslides for the Arno basin with an accuracy of 86% obtained from the variable-landslide inference on about 37% of observed landslides. Future landslide patterns are predicted for 17 A1B and A2 rainfall scenarios and for a multimodel ensemble from 2000 to 2100. We show that potential landslide hazard is strongly correlated with variation in the 12 and 48 h rainfall with a return time of 10 years. As the climate gets wetter, the average probability of landslides gets higher which is shown by the landslide size distribution. Hence, the landslide size distribution is a fingerprint of the geomorphic effectiveness of rainfall as a function of climate change. MAXENT is proposed as a parsimonious model for the prediction of landslide patterns with respect to more complex models. The need for very accurately sampled and delineated landslides is lower than for other prediction

  1. 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

  2. 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...

  3. 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.

  4. 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...

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. The influence of clear zone size and roadside vegetation on driver behavior.

    Science.gov (United States)

    Fitzpatrick, Cole D; Harrington, Curt P; Knodler, Michael A; Romoser, Matthew R E

    2014-06-01

    Roadside vegetation provides numerous environmental and psychological benefits to drivers. Previous studies have shown that natural landscapes can effectively lower crash rates and cause less frustration and stress to the driver. However, run-off-the-road crashes resulting in a collision with a tree are twice as likely to result in a fatality, reinforcing the need to examine the placement of vegetation within the clear zone. This study explores the relationship between the size of the clear zone and the presence of roadside vegetation on vehicle speed and lateral position. A static evaluation, distributed electronically to 100 licensed drivers, was utilized to gather speed selections for both real and virtual roads containing four combinations of clear zone sizes and roadside vegetation densities. A case study was included in the static evaluation to investigate the presence of utility poles near the edge of the road on speed selection. Validation of the static evaluation was performed by a field data collection on the same roadways shown to participants in the evaluation. The speeds observed in the field for roadways with medium clear zone/dense vegetation or large clear zone/spare vegetation correlated with the speeds chosen by static evaluation participants. Further field data were obtained on vehicle speeds and lateral positions for additional roads demonstrating the same clear zone size/vegetation density combinations. This study successfully demonstrates the relationship between clear zone design and driver behavior, which could improve clear zone design practices and thus roadway safety. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

  10. Non-planar driver's side rearview mirrors: A survey of mirror types and european driver experience and a driver behavior study on the influence of experience and driver age on gap acceptance and vehicle detection (final report)

    NARCIS (Netherlands)

    Vos, A.P. de

    2000-01-01

    Some European drivers have been using different types of convex, driver-side rear-view mirrors which provide a wider field-of-view than flat mirrors, but produce a minified image. With a minified image, some drivers may have difficulty judging distances and approach speeds. To assess the potential

  11. Hybrid Model for Early Onset Prediction of Driver Fatigue with Observable Cues

    Directory of Open Access Journals (Sweden)

    Mingheng Zhang

    2014-01-01

    Full Text Available This paper presents a hybrid model for early onset prediction of driver fatigue, which is the major reason of severe traffic accidents. The proposed method divides the prediction problem into three stages, that is, SVM-based model for predicting the early onset driver fatigue state, GA-based model for optimizing the parameters in the SVM, and PCA-based model for reducing the dimensionality of the complex features datasets. The model and algorithm are illustrated with driving experiment data and comparison results also show that the hybrid method can generally provide a better performance for driver fatigue state prediction.

  12. 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...... 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...

  13. 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.

  14. A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes.

    Science.gov (United States)

    Chen, Cong; Zhang, Guohui; Tarefder, Rafiqul; Ma, Jianming; Wei, Heng; Guan, Hongzhi

    2015-07-01

    Rear-end crash is one of the most common types of traffic crashes in the U.S. A good understanding of its characteristics and contributing factors is of practical importance. Previously, both multinomial Logit models and Bayesian network methods have been used in crash modeling and analysis, respectively, although each of them has its own application restrictions and limitations. In this study, a hybrid approach is developed to combine multinomial logit models and Bayesian network methods for comprehensively analyzing driver injury severities in rear-end crashes based on state-wide crash data collected in New Mexico from 2010 to 2011. A multinomial logit model is developed to investigate and identify significant contributing factors for rear-end crash driver injury severities classified into three categories: no injury, injury, and fatality. Then, the identified significant factors are utilized to establish a Bayesian network to explicitly formulate statistical associations between injury severity outcomes and explanatory attributes, including driver behavior, demographic features, vehicle factors, geometric and environmental characteristics, etc. The test results demonstrate that the proposed hybrid approach performs reasonably well. The Bayesian network reference analyses indicate that the factors including truck-involvement, inferior lighting conditions, windy weather conditions, the number of vehicles involved, etc. could significantly increase driver injury severities in rear-end crashes. The developed methodology and estimation results provide insights for developing effective countermeasures to reduce rear-end crash injury severities and improve traffic system safety performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Creation of the Driver Fixed Heel Point (FHP) CAD Accommodation Model for Military Ground Vehicle Design

    Science.gov (United States)

    2016-08-04

    DRIVER FIXED HEEL POINT (FHP) CAD ACCOMMODATION MODEL FOR MILITARY GROUND VEHICLE DESIGN Frank J. Huston II Gale L. Zielinski US Army, Tank ...Registration No. -Technical Report- U.S. Army Tank Automotive Research, Development, and Engineering Center Detroit Arsenal Warren, Michigan 48397...Institute, Ann Arbor, MI UNCLASSIFIED: Distribution Statement A Approved for Public Release Creation of the Driver Fixed Heel Point (FHP) CAD

  16. 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.

  17. Heavy-truck drivers' following behavior with intervention of an integrated, in-vehicle crash warning system: a field evaluation.

    Science.gov (United States)

    Bao, Shan; LeBlanc, David J; Sayer, James R; Flannagan, Carol

    2012-10-01

    This study is designed to evaluate heavy-truck drivers' following behavior and how a crash warning system influences their headway maintenance. Rear-end crashes are one of the major crash types involving heavy trucks and are more likely than other crash types to result in fatalities. Previous studies have observed positive effects of in-vehicle crash warning systems in passenger car drivers. Although heavy-truck drivers are generally more experienced, driver-related errors are still the leading factors contributing to heavy-truck-related rear-end crashes. Data from a 10-month naturalistic driving study were used. Participants were 18 professional heavy-truck drivers who received warnings during the last 8 months of the study (treatment period) but not during the first 2 months (baseline period). Time headway and driver's brake reaction time were extracted and compared with condition variables, including one between-subjects variable (driver shift) and five within-subjects variables (treatment condition, roadway types, traffic density, wiper state, and trailer configuration). The presence of warnings resulted in a 0.28-s increase of mean time headway with dense on-road traffic and a 0.20-s increase with wipers on. Drivers also responded to the forward conflicts significantly faster (by 0.26 s, a 15% enhancement) in the treatment condition compared with responses in the baseline condition. Positive effects on heavy-truck drivers' following performance were observed with the warning system. The installation of such in-vehicle crash warning systems can help heavy-truck drivers keep longer headway distances in challenging situations and respond quicker to potential traffic conflicts, therefore possibly increasing heavy-truck longitudinal driving safety.

  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. 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

  20. 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.)

  1. 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.

  2. 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...... and capacitors are given based on the proposed thermal modelling process, and the datasheet thermal impedance models and the global ambient temperature....

  3. Conceptual models for linking Drivers, Limits and Mobility

    DEFF Research Database (Denmark)

    Gudmundsson, Henrik

    Driven by factors such as urban development, lifestyle changes, and growth in long distance travel transport has been the fastest growing source of greenhouse gas emissions worldwide. At the same time increase in transport demand generates congestion in urban areas posing challenges to maintainin...... results from the Drivers and Limits research project....

  4. 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

  5. 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

  6. HIV epidemic drivers in South Africa: A model-based evaluation of ...

    African Journals Online (AJOL)

    HIV epidemic drivers in South Africa: A model-based evaluation of factors accounting for inter-provincial differences in HIV prevalence and incidence trends. Leigh F. Johnson, Rob E. Dorrington, Haroon Moolla ...

  7. CROSS-STUDY RESEARCH ON UTILITY AND VALIDITY OF DRIVING SIMULATOR FOR DRIVER BEHAVIOR ANALYSIS

    Directory of Open Access Journals (Sweden)

    Michal Matowicki

    2017-12-01

    Full Text Available Driving is one of the most ordinary and universal everyday tasks and, at the same time, one of the most complex and dangerous. It requires a full range of sensory, perceptual, cognitive, and motor functions, all of which can be affected by a wide range of stressors and experience levels. Therefore, exploring of human behaviour while controlling a vehicle is a crucial task in improving traffic safety. Experimental studies can always be conducted with on-road tests, however, using a simulator is safer and more cost-effective. The main goal of this paper is to demonstrate if and under what conditions could a driving simulator provide sufficient results required for a proper study of driver behavior. It discusses its limits and advantages. Overall, the research reviewed in this paper indicates that simulator driving behaviour approximates (relative validity of speed and lateral position of vehicle on road, but does not exactly replicate (absolute validity, on-road driving behaviour.

  8. 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...

  9. An application of signal detection theory for understanding driver behavior at highway-rail grade crossings

    Science.gov (United States)

    2009-10-19

    We used signal detection theory to examine if grade crossing warning devices were effective because they increased drivers' sensitivity to a train's approach or because they encouraged drivers to stop. We estimated d' and a for eight warning devices ...

  10. A modified two-lane traffic model considering drivers' personality

    Science.gov (United States)

    Zhu, H. B.; Zhang, N. X.; Wu, W. J.

    2015-06-01

    Based on the two-lane traffic model proposed by Chowdhury et al., a modified traffic model (R-STCA model, for short) is presented, in which the new symmetric lane changing rules are introduced by considering driving behavioral difference and dynamic headway. After the numerical simulation, a broad scattering of simulated points is exhibited in the moderate density region on the flow-density plane. The synchronized flow phase accompanied with the wide moving jam phase is reproduced. The spatial-temporal profiles indicate that the vehicles move according to the R-STCA model can change lane more easily and more realistically. Then vehicles are convenient to get rid of the slow vehicles that turn into plugs ahead, and hence the capacity increases. Furthermore the phenomenon of the high speed car-following is discovered by using the R-STCA model, which has been already observed in the traffic measured data. All these results indicate that the presented model is reasonable and more realistic.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. Driver behavior during bicycle passing maneuvers in response to a Share the Road sign treatment.

    Science.gov (United States)

    Kay, Jonathan J; Savolainen, Peter T; Gates, Timothy J; Datta, Tapan K

    2014-09-01

    The interaction of motorists and bicyclists, particularly during passing maneuvers, is an area of concern to the bicycle safety community as there is a general perception that motor vehicle drivers may not share the road effectively with bicyclists. This is a particular concern on road sections with centerline rumble strips where motorists are prone to crowd bicyclists during passing events. One potential countermeasure to address this concern is the use of a bicycle warning sign with a "Share the Road" plaque. This paper presents the results of a controlled field evaluation of this sign treatment, which involved an examination of driver behavior while overtaking bicyclists. A series of field studies were conducted concurrently on two segments of a high-speed, rural two-lane highway. These segments were similar in terms of roadway geometry, traffic volumes, and other relevant factors, except that one of the segments included centerline rumble strips while the other did not. A before-and-after study design was utilized to examine changes in motor vehicle lateral placement and speed at the time of the passing event as they relate to the presence of centerline rumble strips and the sign treatment. Centerline rumble strips generally shifted vehicles closer to the bicyclists during passing maneuvers, though the magnitude of this effect was marginal. The sign treatment was found to shift motor vehicles away from the rightmost lane positions, though the signs did not significantly affect the mean buffer distance between the bicyclists and passing motorists or the propensity of crowding events during passing. The sign treatment also resulted in a 2.5miles/h (4.0km/h) reduction in vehicle speeds. Vehicle type, bicyclist position, and the presence of opposing traffic were also found to affect lateral placement and speed selection during passing maneuvers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. 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.

  20. 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.

  1. 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.

  2. 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

    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...... 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...

  3. 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.

  4. 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.

  5. A method to model anticipatory postural control in driver braking events.

    Science.gov (United States)

    Östh, Jonas; Eliasson, Erik; Happee, Riender; Brolin, Karin

    2014-09-01

    Human body models (HBMs) for vehicle occupant simulations have recently been extended with active muscles and postural control strategies. Feedback control has been used to model occupant responses to autonomous braking interventions. However, driver postural responses during driver initiated braking differ greatly from autonomous braking. In the present study, an anticipatory postural response was hypothesized, modelled in a whole-body HBM with feedback controlled muscles, and validated using existing volunteer data. The anticipatory response was modelled as a time dependent change in the reference value for the feedback controllers, which generates correcting moments to counteract the braking deceleration. The results showed that, in 11 m/s(2) driver braking simulations, including the anticipatory postural response reduced the peak forward displacement of the head by 100mm, of the shoulder by 30 mm, while the peak head flexion rotation was reduced by 18°. The HBM kinematic response was within a one standard deviation corridor of corresponding test data from volunteers performing maximum braking. It was concluded that the hypothesized anticipatory responses can be modelled by changing the reference positions of the individual joint feedback controllers that regulate muscle activation levels. The addition of anticipatory postural control muscle activations appears to explain the difference in occupant kinematics between driver and autonomous braking. This method of modelling postural reactions can be applied to the simulation of other driver voluntary actions, such as emergency avoidance by steering. Copyright © 2014. Published by Elsevier B.V.

  6. Research on optimal driver steering model based on Multi-Point preview

    Science.gov (United States)

    Gu, Jun; Ma, Aijing

    2017-08-01

    In this paper, multi-point preview control algorithm is applied to driver steering control model. This paper builds multi-point preview road model in the form of state shift register. Based on the linear quadratic regulator (LQR) optimal control theory it optimizes driver steering control model with multi-point preview. Meanwhile, in the Matlab Simulink environment, based on vehicle system dynamics and optimal control theory, different preview points and weighted coefficients are simulated to study the influence of driver steering model. The simulation results show that the multi-point preview control mode has excellent driving performance. And in this paper, the main parameters affecting the preview control algorithm such as speed, preview weighted coefficients and the number of preview points and so on are discussed.

  7. 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

  8. A mediation model linking dispatcher leadership and work ownership with safety climate as predictors of truck driver safety performance.

    Science.gov (United States)

    Zohar, Dov; Huang, Yueng-hsiang; Lee, Jin; Robertson, Michelle

    2014-01-01

    The study was designed to test the effect of safety climate on safety behavior among lone employees whose work environment promotes individual rather than consensual or shared climate perceptions. The paper presents a mediation path model linking psychological (individual-level) safety climate antecedents and consequences as predictors of driving safety of long-haul truck drivers. Climate antecedents included dispatcher (distant) leadership and driver work ownership, two contextual attributes of lone work, whereas its proximal consequence included driving safety. Using a prospective design, safety outcomes, consisting of hard-braking frequency (i.e. traffic near-miss events) were collected six months after survey completion, using GPS-based truck deceleration data. Results supported the hypothesized model, indicating that distant leadership style and work ownership promote psychological safety climate perceptions, with subsequent prediction of hard-braking events mediated by driving safety. Theoretical and practical implications for studying safety climate among lone workers in general and professional drivers in particular are discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. 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...

  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. Modeling Key Drivers of Cholera Transmission Dynamics Provides New Perspectives for Parasitology.

    Science.gov (United States)

    Rinaldo, Andrea; Bertuzzo, Enrico; Blokesch, Melanie; Mari, Lorenzo; Gatto, Marino

    2017-08-01

    Hydroclimatological and anthropogenic factors are key drivers of waterborne disease transmission. Information on human settlements and host mobility on waterways along which pathogens and hosts disperse, and relevant hydroclimatological processes, can be acquired remotely and included in spatially explicit mathematical models of disease transmission. In the case of epidemic cholera, such models allowed the description of complex disease patterns and provided insight into the course of ongoing epidemics. The inclusion of spatial information in models of disease transmission can aid in emergency management and the assessment of alternative interventions. Here, we review the study of drivers of transmission via spatially explicit approaches and argue that, because many parasitic waterborne diseases share the same drivers as cholera, similar principles may apply. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. 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.

  13. TARDEC FIXED HEEL POINT (FHP): DRIVER CAD ACCOMMODATION MODEL VERIFICATION RERPOT

    Science.gov (United States)

    2017-11-09

    Distribution Statement A. Approve for public release; distribution is unlimited | P a g e 4 REVISION HISTORY ...34 10.1.2 M&S Use History ...the CAD model was compared to the outputs of the UMTRI Soldier Driver Accommodation (2017) model spreadsheet; and boundary manikin hip and eye

  14. Assessment of the Role of Training and Licensing Systems in Changing the Young Driver's Behavior

    Directory of Open Access Journals (Sweden)

    Sudip Barua

    2014-03-01

    Full Text Available Young driver crashes are over represented in any country's crash statistics. This problem is more acute in developing countries where the law enforcement is not strict and the licensing structure is not well developed. According to World Health Organization (WHO road crashes are the single greatest cause of death for men aged 15-29 years old. More than 8500 young drivers die each year in the Organization for Economic Co-operation and Development (OECD countries and the death rates for young drivers are doubled than the older aged drivers. Young driver crashes and deaths cause great economic, social cost on individuals, families and societies. Many research studies have been conducted to find out the causes of crash and deaths. These found that the conventional youth training schemes help young learner to develop their driving skills and knowledge, meanwhile they do not help to gain real road driving experience. Research shows that the lack of driving experience, higher order perception and maturity increase young driver crash exposure. To this end, Graduated Driver Licensing System (GDLS have been developed. GDLS helps young drivers to focus on road driving experience and it divided the whole licensing process into different phases. It also helps the young drivers to get supervised driving experience which help them to accumulate driving hours to get the provisional license. The GDLS helps not only in gaining experience in driving but also in developing the higher order perception (hazard perception which is very much needed during driving. This paper discusses a number of driver's licensing systems and training programs and highlights the need for a licensing system that focus not only on the development of better hazard perception and understanding the road environment for young drivers but also on some other factors that affect road safety. It is argued that the consultation of community concerning the development of a licensing system is

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Virtual testing of driver OOP scenarios: effect of modeling detail on injury response

    NARCIS (Netherlands)

    Bosch-Rekveldt, M.G.C.; Hoof, J.F.A.M. van

    2004-01-01

    This study investigates the relevance of certain parameters for virtual testing of the driver's side OOP problem and attempts to answer the following questions: Which level of detail is needed in the airbag models to assess occupants' injury values for OOP scenarios? What is the influence of the

  3. 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.

  4. 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

  5. How the Interpretation of Drivers' Behavior in Virtual Environment Can Become a Road Design Tool: A Case Study

    Directory of Open Access Journals (Sweden)

    Marco Pasetto

    2011-01-01

    Full Text Available Driving is the result of a psychological process that translates data, signals and direct/indirect messages into behavior, which is continuously adapted to the exchange of varying stimuli between man, environment and vehicle. These stimuli are at times not perceived and at others perceived but not understood by the driver, even if they derive from tools (vertical signs, horizontal marking specifically conceived for his safety. The result is unsafe behavior of vehicle drivers. For this reason, the road environment needs to be radically redesigned. The paper describes a research, based on real and virtual environment surveys, aimed to better understand drivers' action-reaction mechanisms inside different scenarios, in order to gain informations useful for a correct organization (design of the road space. The driving simulator can help in developing, from road to laboratory, the study of new road design tools (geometrical, compositional, constructive ones, street furniture, etc., because it can be used to evaluate solutions before their usefulness is proved on the road.

  6. Mathematical models of human behavior

    DEFF Research Database (Denmark)

    Møllgaard, Anders Edsberg

    During the last 15 years there has been an explosion in human behavioral data caused by the emergence of cheap electronics and online platforms. This has spawned a whole new research field called computational social science, which has a quantitative approach to the study of human behavior. Most...... studies have considered data sets with just one behavioral variable such as email communication. The Social Fabric interdisciplinary research project is an attempt to collect a more complete data set on human behavior by providing 1000 smartphones with pre-installed data collection software to students...... 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...

  7. 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.

  8. 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

  9. 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.

  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.

  11. The use of systems models to identify food waste drivers

    NARCIS (Netherlands)

    Grainger, Matthew James; Aramyan, Lusine; Logatcheva, Katja; Piras, Simone; Righi, Simone; Setti, Marco; Vittuari, Matteo; Stewart, Gavin Bruce

    2018-01-01

    In developed countries, the largest share of food waste is produced at household level. Most studies on consumers’ food waste use models that identify covariates as significant when in fact they may not be, particularly where these models use many variables. Here, using EU-level Eurobarometer data

  12. 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.

  13. 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.

  14. 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)

  15. Development of Prototype Driver Models for Highway Design: Research Update

    Science.gov (United States)

    1999-06-01

    One of the high-priority research areas of the Federal Highway Administration (FHWA) is the development of the Interactive Highway Safety Design Model (IHSDM). The goal of the IHSDM research program is to develop a systematic approach that will allow...

  16. Gap acceptance and Driver behavior at intersections in Minna, North Central Nigeria

    Directory of Open Access Journals (Sweden)

    P. N. Ndoke

    2010-06-01

    Full Text Available The headways, spacing distributions and gap acceptance were measured from two main intersections in Minna, Central Nigeria/The average critical gap and spacing for stadium junction are 2.39 seconds and 11.08m respectively, and that of Mustapha hospital junction are 2.28 seconds and 9.56m respectively. The gap size at the intersections ranges between 1 and 57 seconds. Drivers accept gaps ranging from 2.89 to 3.72 seconds with an average of 3.2 seconds at Mustapha hospital junction and the average time of movement is 2.06 seconds. Similarly, drivers accept gaps ranging from 3.60 seconds and 4.5 seconds with an average of 4.05 seconds at Stadium Junction, and the average time of movement is 2.69 seconds. Comparing these values with the respective critical gaps from the Highway Capacity Manual shows that only values from stadium junction get close. This shows that the delays at the intersections are due mostly to driver impatience and intolerance which at times lead to accidents at the intersections. Hence, it can be concluded that traffic accidents at the intersections are due mostly to driver judgment rather than gap availability.

  17. Model Transformation in context of Driver Assistance System

    OpenAIRE

    Kappattanavar, Abhishek Mallikarjuna

    2016-01-01

    In today’s world we see that Embedded Systems forms a major part in the life of a human being. Almost every device today has an electronic chip embedded in it. When it comes to automotive, these electronic devices are multiplying. This has resulted in innovative methods of developing Embedded Systems. Among them, Model Based Development has become very popular and a standard way of developing embedded systems. Now, we can see that most embedded systems, especially the automotive systems, are ...

  18. Stability analysis of automobile driver steering control

    Science.gov (United States)

    Allen, R. W.

    1981-01-01

    In steering an automobile, the driver must basically control the direction of the car's trajectory (heading angle) and the lateral deviation of the car relative to a delineated pathway. A previously published linear control model of driver steering behavior which is analyzed from a stability point of view is considered. A simple approximate expression for a stability parameter, phase margin, is derived in terms of various driver and vehicle control parameters, and boundaries for stability are discussed. A field test study is reviewed that includes the measurement of driver steering control parameters. Phase margins derived for a range of vehicle characteristics are found to be generally consistent with known adaptive properties of the human operator. The implications of these results are discussed in terms of driver adaptive behavior.

  19. Analogue Behavioral Modeling of GTO

    Directory of Open Access Journals (Sweden)

    Y. Azzouz

    2011-01-01

    Full Text Available An analog behavioral model of high power gate turn-off thyristor (GTO is developed in this paper. The fundamental methodology for the modeling of this power electronic circuit is based on the use of the realistic diode consideration of non-linear junctions. This modeling technique enables to perform different simulations taking into account the turn-on and turn-off transient behaviors in real-time. The equivalent circuits were simulated with analog software developed in our laboratory. It was shown that the tested simple and compact model allows the generation of accurate physical characteristics of power thyristors under dynamic conditions. The model understudy was validated with analog simulations based on operational amplifier devices.

  20. Emergence of multiple ocean ecosystem drivers in a large ensemble suite with an Earth system model

    Science.gov (United States)

    Rodgers, K. B.; Lin, J.; Frölicher, T. L.

    2015-06-01

    Marine ecosystems are increasingly stressed by human-induced changes. Marine ecosystem drivers that contribute to stressing ecosystems - including warming, acidification, deoxygenation and perturbations to biological productivity - can co-occur in space and time, but detecting their trends is complicated by the presence of noise associated with natural variability in the climate system. Here we use large initial-condition ensemble simulations with an Earth system model under a historical/RCP8.5 (representative concentration pathway 8.5) scenario over 1950-2100 to consider emergence characteristics for the four individual and combined drivers. Using a 1-standard-deviation (67% confidence) threshold of signal to noise to define emergence with a 30-year trend window, we show that ocean acidification emerges much earlier than other drivers, namely during the 20th century over most of the global ocean. For biological productivity, the anthropogenic signal does not emerge from the noise over most of the global ocean before the end of the 21st century. The early emergence pattern for sea surface temperature in low latitudes is reversed from that of subsurface oxygen inventories, where emergence occurs earlier in the Southern Ocean. For the combined multiple-driver field, 41% of the global ocean exhibits emergence for the 2005-2014 period, and 63% for the 2075-2084 period. The combined multiple-driver field reveals emergence patterns by the end of this century that are relatively high over much of the Southern Ocean, North Pacific, and Atlantic, but relatively low over the tropics and the South Pacific. For the case of two drivers, the tropics including habitats of coral reefs emerges earliest, with this driven by the joint effects of acidification and warming. It is precisely in the regions with pronounced emergence characteristics where marine ecosystems may be expected to be pushed outside of their comfort zone determined by the degree of natural background variability

  1. 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.

  2. 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

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

    Science.gov (United States)

    Zhang, Sihai; Wang, Zhiyang

    2016-01-01

    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 data analysis in

  4. 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

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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.

  10. Considerations on the implementation and modeling of an active mass driver with electric torsional servomotor

    Science.gov (United States)

    Ubertini, Filippo; Venanzi, Ilaria; Comanducci, Gabriele

    2015-06-01

    The current trend in full-scale applications of active mass drivers for mitigating buildings' vibrations is to rely on the use of electric servomotors and low friction transmission devices. While similar full-scale applications have been recently documented, there is still the need for deepening the understanding of the behavior of such active mass drivers, especially as it concerns their reliability in the case of extreme loading events. This paper presents some considerations arisen in the physical implementation of a prototype active mass driver system, fabricated by coupling an electric torsional servomotor with a ball screw transmission device, using state-of-the-art electronics and a high speed digital communication protocol between controller and servomotor drive. The prototype actuator is mounted on top of a scaled-down five-story frame structure, subjected to base excitation provided by a sliding table actuated by an electrodynamic shaker. The equations of motion are rigorously derived, at first, by considering the torque of the servomotor as the control input, in agreement with other literature work. Then, they are extended to the case where the servomotor operates under kinematic control, that is, by commanding its angular velocity instead of its torque, including control-structure-interaction effects. Experiments are carried out by employing an inherently stable collocated skyhook control algorithm, proving, on the one hand, the control effectiveness of the device but also revealing, on the other hand, the possibility of closed-loop system instability at high gains. Theoretical interpretation of the results clarifies that the dynamic behavior of the actuator plays a central role in determining its control effectiveness and is responsible for the observed stability issues, operating similarly to time delay effects. Numerical extension to the case of earthquake excitation confirms the control effectiveness of the device and highlights that different

  11. [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.

  12. Comparative analysis of driver's brake perception-reaction time at signalized intersections with and without countdown timer using parametric duration models.

    Science.gov (United States)

    Fu, Chuanyun; Zhang, Yaping; Bie, Yiming; Hu, Liwei

    2016-10-01

    Countdown timers display the time left on the current signal, which makes drivers be more ready to react to the phase change. However, previous related studies have rarely explored the effects of countdown timer on driver's brake perception-reaction time (BPRT) to yellow light. The goal of this study was therefore to characterize and model driver's BPRT to yellow signal at signalized intersections with and without countdown timer. BPRT data for "first-to-stop" vehicles after yellow onset within the transitional zone were collected through on-site observation at six signalized intersections in Harbin, China. Statistical analysis showed that the observed 15th, 50th, and 85th percentile BPRTs without countdown timer were 0.52, 0.84, and 1.26s, respectively. The observed 15th, 50th, and 85th percentile BPRTs with countdown timer were 0.32, 1.20, and 2.52s, respectively. Log-logistic distribution appeared to best fit the BPRT without countdown timer, while Weibull distribution seemed to best fit the BPRT with countdown timer. After that, a Log-logistic accelerated failure time (AFT) duration model was developed to model driver's BPRT without countdown timer, whereas a Weibull AFT duration model was established to model driver's BPRT with countdown timer. Three significant factors affecting the BPRT identified in both AFT models included yellow-onset distance from the stop line, yellow-onset approach speed, and deceleration rate. No matter whether the presence of countdown timer or not, BPRT increased as yellow-onset distance to the stop line or deceleration rate increased, but decreased as yellow-onset speed increased. The impairment of driver's BPRT due to countdown timer appeared to increase with yellow-onset distance to the stop line or deceleration rate, but decrease with yellow-onset speed. An increase in driver's BPRT because of countdown timer may induce risky driving behaviors (i.e., stop abruptly, or even violate traffic signal), revealing a weakness of

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

    Science.gov (United States)

    Szczepaniak, Jan; Tanaś, Wojciech; Pawłowski, Tadeusz; Kromulski, Jacek

    2014-01-01

    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.

  14. Modeling cognitive load effects of conversation between a passenger and driver.

    Science.gov (United States)

    Tillman, Gabriel; Strayer, David; Eidels, Ami; Heathcote, Andrew

    2017-08-01

    Cognitive load from secondary tasks is a source of distraction causing injuries and fatalities on the roadway. The Detection Response Task (DRT) is an international standard for assessing cognitive load on drivers' attention that can be performed as a secondary task with little to no measurable effect on the primary driving task. We investigated whether decrements in DRT performance were related to the rate of information processing, levels of response caution, or the non-decision processing of drivers. We had pairs of participants take part in the DRT while performing a simulated driving task, manipulated cognitive load via the conversation between driver and passenger, and observed associated slowing in DRT response time. Fits of the single-bound diffusion model indicated that slowing was mediated by an increase in response caution. We propose the novel hypothesis that, rather than the DRT's sensitivity to cognitive load being a direct result of a loss of information processing capacity to other tasks, it is an indirect result of a general tendency to be more cautious when making responses in more demanding situations.

  15. Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

    Science.gov (United States)

    Wang, I-Ming; Zhang, Bin; Yang, Xia; Zhu, Jun; Stepaniants, Serguei; Zhang, Chunsheng; Meng, Qingying; Peters, Mette; He, Yudong; Ni, Chester; Slipetz, Deborah; Crackower, Michael A; Houshyar, Hani; Tan, Christopher M; Asante-Appiah, Ernest; O'Neill, Gary; Luo, Mingjuan Jane; Thieringer, Rolf; Yuan, Jeffrey; Chiu, Chi-Sung; Lum, Pek Yee; Lamb, John; Boie, Yves; Wilkinson, Hilary A; Schadt, Eric E; Dai, Hongyue; Roberts, Christopher

    2012-07-17

    Common inflammatome gene signatures as well as disease-specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co-expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue-specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response-related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non-drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.

  16. 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.

  17. 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.

  18. 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)

  19. Fit and frustration as drivers of targeted counterproductive work behaviors: A multifoci perspective.

    Science.gov (United States)

    Harold, Crystal M; Oh, In-Sue; Holtz, Brian C; Han, Soojung; Giacalone, Robert A

    2016-11-01

    In this article, the authors integrate the theory of work adjustment (Dawis, England, & Lofquist, 1964) and the stressor emotion model of counterproductive work behaviors (CWBs; Spector & Fox, 2005) to examine workplace frustration as an intervening mechanism that mediates relations between person-environment (P-E) fit and CWBs. Moreover, we adopt a multifoci perspective to estimate effects for multiple fit, frustration, and CWB foci. We examine the nature of relations between fit, frustration, and CWB for like foci (target similar effects), as well as cross-foci effects. Study 1 examines proposed effects in a sample of 447 employee-coworker dyads. Study 2 uses a 3-wave survey design and tests effects in a sample of 669 employees. Results from both studies suggest that (a) frustration mediates the effects of P-E fit on CWBs and (b) the most consistent effects were observed among the variables with matching foci. Implications for research and practice are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  20. 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

  1. 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

  2. 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.

  3. Analysis of driver performance under reduced visibility

    Science.gov (United States)

    Kaeppler, W. D.

    1982-01-01

    Mathematical models describing vehicle dynamics as well as human behavior may be useful in evaluating driver performance and in establishing design criteria for vehicles more compatible with man. In 1977, a two level model of driver steering behavior was developed, but its parameters were identified for clear visibility conditions only. Since driver performance degrades under conditions of reduced visibility, e.g., fog, the two level model should be investigated to determine its applicability to such conditions. The data analysis of a recently performed driving simulation experiment showed that the model still performed reasonably well under fog conditions, although there was a degradation in its predictive capacity during fog. Some additional parameters affecting anticipation and lag time may improve the model's performance for reduced visibility conditions.

  4. Crowd Human Behavior for Modeling and Simulation

    Science.gov (United States)

    2009-08-06

    Crowd Human Behavior for Modeling and Simulation Elizabeth Mezzacappa, Ph.D. & Gordon Cooke, MEME Target Behavioral Response Laboratory, ARDEC...TYPE Conference Presentation 3. DATES COVERED 00-00-2008 to 00-00-2009 4. TITLE AND SUBTITLE Crowd Human Behavior for Modeling and Simulation...34understanding human behavior " and "model validation and verification" and will focus on modeling and simulation of crowds from a social scientist???s

  5. Modeling software behavior a craftsman's approach

    CERN Document Server

    Jorgensen, Paul C

    2009-01-01

    A common problem with most texts on requirements specifications is that they emphasize structural models to the near exclusion of behavioral models-focusing on what the software is, rather than what it does. If they do cover behavioral models, the coverage is brief and usually focused on a single model. Modeling Software Behavior: A Craftsman's Approach provides detailed treatment of various models of software behavior that support early analysis, comprehension, and model-based testing. Based on the popular and continually evolving course on requirements specification models taught by the auth

  6. Razvoj modela vozača za upravljanje vozilom tokom pravolinijskog kretanja / Development of driver model for vehicle control during a straight line motion

    Directory of Open Access Journals (Sweden)

    Miroslav Demić

    2007-04-01

    Full Text Available Upravljanje vozilom na pravolinijskom putu spada u specijalan slučaj analize dinamičkog sistema vozač - vozilo - okruženje, jer podužno kretanje vozila podrazumeva aktivno učešće vozača u uslovima koji su definisani parametrima puta i vozila. U savremenoj literaturi postoje pokušaji modeliranja pomenutog sistema u uslovima pravolinijskog kretanja, ali, do sada, nije definisan opšteprihvaćeni model vozača. Problem se usložava činjenicom da se u razmatranje mora uzeti i veoma složeno ponašanje motora i transmisije u dinamičkim uslovima. U radu je modeliran sistem vozač - vozilo u uslovima pravolinijskog kretanja radi praćenja zadate, najčešće, promenljive brzine vozila. / To drive the vehicle on a straight line road can be put as a special case analysis of a Driver-Vehicle-Environment dynamical system, because longitudinal vehicle motion means that active driver participates in the conditions defined by road and vehicle parameters. In contemporary literature, there are some attempts of modeling the mentioned system in the case of a straight line drive, but, so far, there is no generally accepted model of a driver. It should be mentioned that the problem is more complex with fact that a very complex motor and transmission behavior must be assumed in dynamic conditions. There are some attempts of modeling the driver and vehicle in the case of straight line driving, with a goal of tracking the given, frequently variable vehicle speed.

  7. Modelling land cover change in the Brazilian Amazon: temporal changes in drivers and calibration issues.

    Science.gov (United States)

    Rosa, Isabel M D; Purves, Drew; Carreiras, João M B; Ewers, Robert M

    Land cover change (LCC) models are used in many studies of human impacts on the environment, but knowing how well these models predict observed changes in the landscape is a challenge. We used nearly three decades of LCC maps to run several LCC simulations to: (1) determine which parameters associated with drivers of LCC (e.g. roads) get selected for which transition (forest to deforested, regeneration to deforested or deforested to regeneration); (2) investigate how the parameter values vary through time with respect to the different activities (e.g. farming); and (3) quantify the influence of choosing a particular time period for model calibration and validation on the performance of LCC models. We found that deforestation of primary forests tends to occur along roads (included in 95 % of models) and outside protected areas (included in all models), reflecting farming establishment. Regeneration tends to occur far from roads (included in 78 % of the models) and inside protected areas (included in 38 % of the models), reflecting the processes of land abandonment. Our temporal analysis of model parameters revealed a degree of variation through time (e.g. effectiveness of protected areas rose by 73 %, p  change was heavily dependent on the year used for calibration ( p  change through time and exert their influence on model predictions.

  8. 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

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

    NARCIS (Netherlands)

    Arts, J.W.C.; Frambach, R.T.; Bijmolt, T.H.A.

    2011-01-01

    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

  10. Impacts of weather versus climate and driver uncertainty on multi-centennial ecosystem model simulations

    Science.gov (United States)

    Rollinson, C.; Simkins, J.; Fer, I.; Desai, A. R.; Dietze, M.

    2017-12-01

    Simulations of ecosystem dynamics and comparisons with empirical data require accurate, continuous, and often sub-daily meteorology records that are spatially aligned to the scale of the empirical data. A wealth of meteorology data for the past, present, and future is available through site-specific observations, modern reanalysis products, and gridded GCM simulations. However, these products are mismatched in spatial and temporal resolution, often with both different means and seasonal patterns. We have designed and implemented a two-step meteorological downscaling and ensemble generation method that combines multiple meteorology data products through debiasing and temporal downscaling protocols. Our methodology is designed to preserve the covariance among seven meteorological variables for use as drivers in ecosystem model simulations: temperature, precipitation, short- and longwave radiation, surface pressure, humidity, and wind. Furthermore, our method propagates uncertainty through the downscaling process and results in ensembles of meteorology that can be compared to paleoclimate reconstructions and used to analyze the effects of both high- and low-frequency climate anomalies on ecosystem dynamics. Using a multiple linear regression approach, we have combined hourly, 0.125-degree gridded data from the NLDAS (1980-present) with CRUNCEP (1901-2010) and CMIP5 historical (1850-2005), past millennium (850-1849), and future (1950-2100) GCM simulations. This has resulted in an ensemble of continuous, hourly-resolved meteorology from from the paleo era into the future with variability in weather events as well as low-frequency climatic changes. We investigate the influence of extreme sub-daily weather phenomena versus long-term climatic changes in an ensemble of ecosystem models that range in atmospheric and biological complexity. Through data assimilation with paleoclimate reconstructions of past climate, we can improve data-model comparisons using observations of

  11. [Assessment of accelerated aging among automobile drivers using model of the biological age based on physical work capacity].

    Science.gov (United States)

    Bashkireva, A S

    2012-01-01

    The studies of biological age, aging rate, physical work capacity in professional drivers were conducted. The examination revealed peculiarities of system organization of functions, which determine the physical 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 on physical work capacity model. The results point at the premature decrease of the physical work capacity in professional drivers. The premature contraction of the range of cardio-vascular system adaptive reactions on submaximum physical load in the drivers as compared with control group was revealed. It was proved that premature age-related changes of physiologic indices in drivers are just "risk indicators", while long driving experience is a real risk factor, accelerating the ageing process. The "risk group" with manifestations of accelerating ageing 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 ageing prevention among working population was demonstrated.

  12. 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

  13. 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.

  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. Using multilevel models to identify drivers of landscape-genetic structure among management areas.

    Science.gov (United States)

    Dudaniec, Rachael Y; Rhodes, Jonathan R; Worthington Wilmer, Jessica; Lyons, Mitchell; Lee, Kristen E; McAlpine, Clive A; Carrick, Frank N

    2013-07-01

    Landscape genetics offers a powerful approach to understanding species' dispersal patterns. However, a central obstacle is to account for ecological processes operating at multiple spatial scales, while keeping research outcomes applicable to conservation management. We address this challenge by applying a novel multilevel regression approach to model landscape drivers of genetic structure at both the resolution of individuals and at a spatial resolution relevant to management (i.e. local government management areas: LGAs) for the koala (Phascolartos cinereus) in Australia. Our approach allows for the simultaneous incorporation of drivers of landscape-genetic relationships operating at multiple spatial resolutions. Using microsatellite data for 1106 koalas, we show that, at the individual resolution, foliage projective cover (FPC) facilitates high gene flow (i.e. low resistance) until it falls below approximately 30%. Out of six additional land-cover variables, only highways and freeways further explained genetic distance after accounting for the effect of FPC. At the LGA resolution, there was significant variation in isolation-by-resistance (IBR) relationships in terms of their slopes and intercepts. This was predominantly explained by the average resistance distance among LGAs, with a weaker effect of historical forest cover. Rates of recent landscape change did not further explain variation in IBR relationships among LGAs. By using a novel multilevel model, we disentangle the effect of landscape resistance on gene flow at the fine resolution (i.e. among individuals) from effects occurring at coarser resolutions (i.e. among LGAs). This has important implications for our ability to identify appropriate scale-dependent management actions. © 2013 John Wiley & Sons Ltd.

  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. 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.

  19. 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.

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

    Science.gov (United States)

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

    2018-03-01

    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. Published by Elsevier B.V.

  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. 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,

  4. 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.

  5. 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.

  6. An Interactionist Model of Creative Behavior.

    Science.gov (United States)

    Woodman, Richard W.; Schoenfeldt, Lyle F.

    1990-01-01

    An interactionist model of creative behavior is proposed, combining elements of the personality, cognitive, and social psychology perspectives on creativity. The model considers the interplay of factors including antecedent conditions, creative behavior, consequences, the individual, cognitive style/ability, personality traits, contextual…

  7. 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

  8. Modeling Architectural Patterns' Behavior Using Architectural Primitives

    NARCIS (Netherlands)

    Kamal, Ahmad Waqas; Avgeriou, Paris; Morrison, R; Balasubramaniam, D; Falkner, K

    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

  9. Mathematical models of behavior of individual animals.

    Science.gov (United States)

    Tsibulsky, Vladimir L; Norman, Andrew B

    2007-01-01

    This review is focused on mathematical modeling of behaviors of a whole organism with special emphasis on models with a clearly scientific approach to the problem that helps to understand the mechanisms underlying behavior. The aim is to provide an overview of old and contemporary mathematical models without complex mathematical details. Only deterministic and stochastic, but not statistical models are reviewed. All mathematical models of behavior can be divided into two main classes. First, models that are based on the principle of teleological determinism assume that subjects choose the behavior that will lead them to a better payoff in the future. Examples are game theories and operant behavior models both of which are based on the matching law. The second class of models are based on the principle of causal determinism, which assume that subjects do not choose from a set of possibilities but rather are compelled to perform a predetermined behavior in response to specific stimuli. Examples are perception and discrimination models, drug effects models and individual-based population models. A brief overview of the utility of each mathematical model is provided for each section.

  10. 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

  11. Modeling of direct beam extraction for a high-charge-state fusion driver

    Science.gov (United States)

    Anderson, O. A.; Grant Logan, B.

    A newly proposed type of multicharged ion source offers the possibility of an economically advantageous high-charge-state fusion driver. Multiphoton absorption in an intense uniform laser focus can give multiple charge states of high purity, simplifying or eliminating the need for charge-state separation downstream. Very large currents (hundreds of amperes) can be extracted from this type of source. Several arrangements are possible. For example, the laser plasma could be tailored for storage in a magnetic bucket, with beam extracted from the bucket. A different approach, described in this report, is direct beam extraction from the expanding laser plasma. We discuss extraction and focusing for the particular case of a 4.1 MV beam of Xe 16+ ions. The maximum duration of the beam pulse is limited by the total charge in the plasma, while the practical pulse length is determined by the range of plasma radii over which good beam optics can be achieved. The extraction electrode contains a solenoid for beam focusing. Our design studies were carried out first with an envelope code and then with a self-consistent particle code. Results from our initial model showed that hundreds of amperes could be extracted, but that most of this current missed the solenoid entrance or was intercepted by the wall and that only a few amperes were able to pass through. We conclude with an improved design which increases the surviving beam to more than 70 A.

  12. 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.

  13. 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.

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Stabilization strategies of a general nonlinear car-following model with varying reaction-time delay of the drivers.

    Science.gov (United States)

    Li, Shukai; Yang, Lixing; Gao, Ziyou; Li, Keping

    2014-11-01

    In this paper, the stabilization strategies of a general nonlinear car-following model with reaction-time delay of the drivers are investigated. The reaction-time delay of the driver is time varying and bounded. By using the Lyapunov stability theory, the sufficient condition for the existence of the state feedback control strategy for the stability of the car-following model is given in the form of linear matrix inequality, under which the traffic jam can be well suppressed with respect to the varying reaction-time delay. Moreover, by considering the external disturbance for the running cars, the robust state feedback control strategy is designed, which ensures robust stability and a smaller prescribed H∞ disturbance attenuation level for the traffic flow. Numerical examples are given to illustrate the effectiveness of the proposed methods. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Behavior Analysis of Elderly using Topic Models

    NARCIS (Netherlands)

    Rieping, K.; Englebienne, G.; Kröse, B.

    2014-01-01

    This paper describes two new topic models for the analysis of human behavior in homes that are equipped with sensor networks. The models are based on Latent Dirichlet Allocation (LDA) topic models and can detect patterns in sensor data in an unsupervised manner. LDA-Gaussian, the first variation of

  2. Punishment models of addictive behavior

    NARCIS (Netherlands)

    Vanderschuren, L.J.M.J.; Minnaard, A.M.; Smeets, J.A.S.; Lesscher, H.M.B.

    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

  3. A behavior change model for internet interventions.

    Science.gov (United States)

    Ritterband, Lee M; Thorndike, Frances P; Cox, Daniel J; Kovatchev, Boris P; Gonder-Frederick, Linda A

    2009-08-01

    The Internet has become a major component to health care and has important implications for the future of the health care system. One of the most notable aspects of the Web is its ability to provide efficient, interactive, and tailored content to the user. Given the wide reach and extensive capabilities of the Internet, researchers in behavioral medicine have been using it to develop and deliver interactive and comprehensive treatment programs with the ultimate goal of impacting patient behavior and reducing unwanted symptoms. To date, however, many of these interventions have not been grounded in theory or developed from behavior change models, and no overarching model to explain behavior change in Internet interventions has yet been published. The purpose of this article is to propose a model to help guide future Internet intervention development and predict and explain behavior changes and symptom improvement produced by Internet interventions. The model purports that effective Internet interventions produce (and maintain) behavior change and symptom improvement via nine nonlinear steps: the user, influenced by environmental factors, affects website use and adherence, which is influenced by support and website characteristics. Website use leads to behavior change and symptom improvement through various mechanisms of change. The improvements are sustained via treatment maintenance. By grounding Internet intervention research within a scientific framework, developers can plan feasible, informed, and testable Internet interventions, and this form of treatment will become more firmly established.

  4. 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......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......, (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...

  5. 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

  6. The relationship between trait anxiety and driving behavior with regard to self-reported Iranian accident involving drivers

    Directory of Open Access Journals (Sweden)

    Siamak Pourabdian

    2013-01-01

    Conclusions: It can be concluded from the results (according to the relation between TA with error and lapses factor that the rate of TA is destructive effective on the memory performance and process in the drivers and cause absent minded and memory imperfect function and process in these people during the driving.

  7. Modeling ecological drivers in marine viral communities using comparative metagenomics and network analyses.

    Science.gov (United States)

    Hurwitz, Bonnie L; Westveld, Anton H; Brum, Jennifer R; Sullivan, Matthew B

    2014-07-22

    Long-standing questions in marine viral ecology are centered on understanding how viral assemblages change along gradients in space and time. However, investigating these fundamental ecological questions has been challenging due to incomplete representation of naturally occurring viral diversity in single gene- or morphology-based studies and an inability to identify up to 90% of reads in viral metagenomes (viromes). Although protein clustering techniques provide a significant advance by helping organize this unknown metagenomic sequence space, they typically use only ∼75% of the data and rely on assembly methods not yet tuned for naturally occurring sequence variation. Here, we introduce an annotation- and assembly-free strategy for comparative metagenomics that combines shared k-mer and social network analyses (regression modeling). This robust statistical framework enables visualization of complex sample networks and determination of ecological factors driving community structure. Application to 32 viromes from the Pacific Ocean Virome dataset identified clusters of samples broadly delineated by photic zone and revealed that geographic region, depth, and proximity to shore were significant predictors of community structure. Within subsets of this dataset, depth, season, and oxygen concentration were significant drivers of viral community structure at a single open ocean station, whereas variability along onshore-offshore transects was driven by oxygen concentration in an area with an oxygen minimum zone and not depth or proximity to shore, as might be expected. Together these results demonstrate that this highly scalable approach using complete metagenomic network-based comparisons can both test and generate hypotheses for ecological investigation of viral and microbial communities in nature.

  8. Biosocial models of adolescent problem behaviors.

    Science.gov (United States)

    Udry, J R

    1990-01-01

    This paper develops a biosocial model of adolescent age-graded norm violations ("problem behaviors"), combining a traditional social control model with a biological model using steroid hormones. Subjects were 101 white boys drawn from the 8th-, 9th-, and 10th-grade rosters of selected public schools, and ranging in age from 13 to 16. Subjects completed self-administered questionnaires and provided blood samples which were assayed for the behaviorally relevant hormones. Boys' problem behavior shows strong hormone effects. Social and biological variables have both additive and indirect effects. Using a biosocial model leads to conclusions which are different from those which would have been drawn from the sociological model alone.

  9. 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.

  10. Assessing Chinese coach drivers' fitness to drive: The development of a toolkit based on cognition measurements.

    Science.gov (United States)

    Wang, Huarong; Mo, Xian; Wang, Ying; Liu, Ruixue; Qiu, Peiyu; Dai, Jiajun

    2016-10-01

    Road traffic accidents resulting in group deaths and injuries are often related to coach drivers' inappropriate operations and behaviors. Thus, the evaluation of coach drivers' fitness to drive is an important measure for improving the safety of public transportation. Previous related research focused on drivers' age and health condition. Comprehensive studies about commercial drivers' cognitive capacities are limited. This study developed a toolkit consisting of nine cognition measurements across driver perception/sensation, attention, and reaction. A total of 1413 licensed coach drivers in Jiangsu Province, China were investigated and tested. Results indicated that drivers with accident history within three years performed overwhelmingly worse (p<0.001) on dark adaptation, dynamic visual acuity, depth perception, attention concentration, attention span, and significantly worse (p<0.05) on reaction to complex tasks compared with drivers with clear accident records. These findings supported that in the assessment of fitness to drive, cognitive capacities are sensitive to the detection of drivers with accident proneness. We first developed a simple evaluation model based on the percentile distribution of all single measurements, which defined the normal range of "fit-to-drive" by eliminating a 5% tail of each measurement. A comprehensive evaluation model was later constructed based on the kernel principal component analysis, in which the eliminated 5% tail was calculated from on integrated index. Methods to categorizing qualified, good, and excellent coach drivers and criteria for evaluating and training Chinese coach drivers' fitness to drive were also proposed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. 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, ...

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. Modeling behavioral considerations related to information security.

    Energy Technology Data Exchange (ETDEWEB)

    Martinez-Moyano, I. J.; Conrad, S. H.; Andersen, D. F. (Decision and Information Sciences); (SNL); (Univ. at Albany)

    2011-01-01

    The authors present experimental and simulation results of an outcome-based learning model for the identification of threats to security systems. This model integrates judgment, decision-making, and learning theories to provide a unified framework for the behavioral study of upcoming threats.

  17. 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.

  18. 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.

  19. 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....

  20. 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...

  1. 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

  2. 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

  3. 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

  4. Accurate diode behavioral model with reverse recovery

    Science.gov (United States)

    Banáš, Stanislav; Divín, Jan; Dobeš, Josef; Paňko, Václav

    2018-01-01

    This paper deals with the comprehensive behavioral model of p-n junction diode containing reverse recovery effect, applicable to all standard SPICE simulators supporting Verilog-A language. The model has been successfully used in several production designs, which require its full complexity, robustness and set of tuning parameters comparable with standard compact SPICE diode model. The model is like standard compact model scalable with area and temperature and can be used as a stand-alone diode or as a part of more complex device macro-model, e.g. LDMOS, JFET, bipolar transistor. The paper briefly presents the state of the art followed by the chapter describing the model development and achieved solutions. During precise model verification some of them were found non-robust or poorly converging and replaced by more robust solutions, demonstrated in the paper. The measurement results of different technologies and different devices compared with a simulation using the new behavioral model are presented as the model validation. The comparison of model validation in time and frequency domains demonstrates that the implemented reverse recovery effect with correctly extracted parameters improves the model simulation results not only in switching from ON to OFF state, which is often published, but also its impedance/admittance frequency dependency in GHz range. Finally the model parameter extraction and the comparison with SPICE compact models containing reverse recovery effect is presented.

  5. 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.

  6. 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.

  7. 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.

  8. Modelling Spatial Patterns and Drivers of Wildfires in Honduras Using Remote Sensing and Geographic Information Systems

    Science.gov (United States)

    Valdez Vasquez, M. C.; Chen, C. F.; Chiang, S. H.

    2016-12-01

    Forests in Honduras are one of the most important resources as they provide a wide range of environmental, economic, and social benefits. However, they are endangered as a result of the relentless occurrence of wildfires during the dry season. Despite the knowledge acquired by the population concerning the effects of wildfires, the frequency is increasing, a pattern attributable to the numerous ignition sources linked to human activity. The purpose of this study is to integrate the wildfire occurrences throughout the 2010-2015 period with a series of anthropogenic and non-anthropogenic variables using the random forest algorithm (RF). We use a series of variables that represent the anthropogenic activity, the flammability of vegetation, climatic conditions, and topography. To represent the anthropogenic activity, we included the continuous distances to rivers, roads, and settlements. To characterize the vegetation flammability, we used the normalized difference vegetation index (NDVI) and the normalized multi-band drought index (NMDI) acquired from MODIS surface reflectance data. Additionally, we included the topographical variables elevation, slope, and solar radiation derived from the ASTER global digital elevation model (GDEM V2). To represent the climatic conditions, we employed the land surface temperature (LST) product from the MODIS sensor and the WorldClim precipitation data. We analyzed the explanatory variables through native RF variable importance analysis and jackknife test, and the results revealed that the dry fuel conditions and low precipitation combined with the proximity to non-paved roads were the major drivers of wildfires. Furthermore, we predicted the areas with highest wildfire susceptibility, which are located mainly in the central and eastern regions of the country, within coniferous and mixed forests. Results acquired were validated using the area under the receiver operating characteristic (ROC) curve and the point biserial correlation

  9. 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

  10. 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

    control maneuvers are considered: “no avoidance maneuvers”, “braking”, “steering”, “braking & steering”, and “other maneuvers”. The importance of avoidance maneuvers derives from the key role of responsible, proactive and state-aware road users within the concept of sustainable safety systems, as well......This 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 attributes. Five alternative actions involving emergency lateral and speed...... maneuvers, (iii) fatigue and distractions have a greater negative impact on the tendency to engage in crash avoidance maneuvers than alcohol consumption, (iv) difficult road conditions increase the propensity to perform crash avoidance maneuvers, (v) visual obstruction and artificial illumination have...

  11. 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...... of the predictive models required for the design of work supports systems, that is,information systems serving as the human-work interface. Three basic issues are in focus: 1.) Some fundamental problems in analysis and modeling modern dynamic work systems caused by the adaptive nature of human behavior; 2.......) 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....

  12. 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

  13. Behavioral effects in room evacuation models

    Science.gov (United States)

    Dossetti, V.; Bouzat, S.; Kuperman, M. N.

    2017-08-01

    In this work we study a model for the evacuation of pedestrians from an enclosure considering a continuous space substrate and discrete time. We analyze the influence of behavioral features that affect the use of the empty space, that can be linked to the attitudes or characters of the pedestrians. We study how the interaction of different behavioral profiles affects the needed time to evacuate completely a room and the occurrence of clogging. We find that neither fully egotistic nor fully cooperative attitudes are optimal from the point of view of the crowd. In contrast, intermediate behaviors provide lower evacuation times. This leads us to identify some phenomena closely analogous to the faster-is-slower effect. The proposed model allows for distinguishing between the role of the attitudes in the search for empty space and the attitudes in the conflicts.

  14. 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.

  15. 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.

  16. 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.

  17. 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....

  18. Quality assessment of human behavior models

    NARCIS (Netherlands)

    Doesburg, W.A. van

    2007-01-01

    Accurate and efficient models of human behavior offer great potential in military and crisis management applications. However, little attention has been given to the man ner in which it can be determined if this potential is actually realized. In this study a quality assessment approach that

  19. 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...

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

    OpenAIRE

    Babak Moeini; Forouzan Rezapur-Shahkolai; Javad Faradmal; Mokhtar Soheylizad

    2014-01-01

    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...

  1. 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

  2. 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.

  3. 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.

  4. Applying incentive sensitization models to behavioral addiction.

    Science.gov (United States)

    Rømer Thomsen, Kristine; Fjorback, Lone O; Møller, Arne; Lou, Hans C

    2014-09-01

    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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. A Cellular Automata Traffic Flow Model considering Bus Lane Changing Behavior with Scheduling Parameters

    Directory of Open Access Journals (Sweden)

    Zun-dong Zhang

    2015-01-01

    Full Text Available According to different driving behavioral characteristics of bus drivers, a cellular automata traffic model considering the bus lane changing behavior with scheduling parameters is proposed in this paper. Traffic bottleneck problems caused by bus stops are simulated in multiple lanes roads with no-bay bus stations. With the mixed traffic flow composed of different bus arrival rate, flow-density graph, density distribution graph, and temporal-spatial graph are presented. Furthermore, the mixed traffic flow characteristics are analyzed. Numerical experiment results show that the proposed model can generate a variety of complicated realistic phenomena in the traffic system with bus stops and provide theoretical basis for better using of traffic flow model.

  10. 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

  11. Modeling Workplace Bullying Behaviors Using Catastrophe Theory

    OpenAIRE

    Escartín Solanelles, Jordi; Ceja, Lucía; Navarro Cid, José; Zapf, D.

    2013-01-01

    Workplace bullying is defined as negative behaviors directed at organizational members or their work context that occur regularly and repeatedly over a period of time. Employees' perceptions of psychosocial safety climate, workplace bullying victimization, and workplace bullying perpetration were assessed within a sample of nearly 5,000 workers. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes in workplace bullying. More specifically, the prese...

  12. 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.

  13. Animal models of compulsive eating behavior.

    Science.gov (United States)

    Di Segni, Matteo; Patrono, Enrico; Patella, Loris; Puglisi-Allegra, Stefano; Ventura, Rossella

    2014-10-22

    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-medicate. Clinical data suggest that some individuals may develop addiction-like behaviors from consuming palatable foods. Based on this observation, "food addiction" has emerged as an area of intense scientific research. A growing body of evidence suggests that some aspects of food addiction, such as compulsive eating behavior, can be modeled in animals. Moreover, several areas of the brain, including various neurotransmitter systems, are involved in the reinforcement effects of both food and drugs, suggesting that natural and pharmacological stimuli activate similar neural systems. In addition, several recent studies have identified a putative connection between neural circuits activated in the seeking and intake of both palatable food and drugs. The development of well-characterized animal models will increase our understanding of the etiological factors of food addiction and will help identify the neural substrates involved in eating disorders such as compulsive overeating. Such models will facilitate the development and validation of targeted pharmacological therapies.

  14. Animal Models of Compulsive Eating Behavior

    Directory of Open Access Journals (Sweden)

    Matteo Di Segni

    2014-10-01

    Full Text Available 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-medicate. Clinical data suggest that some individuals may develop addiction-like behaviors from consuming palatable foods. Based on this observation, “food addiction” has emerged as an area of intense scientific research. A growing body of evidence suggests that some aspects of food addiction, such as compulsive eating behavior, can be modeled in animals. Moreover, several areas of the brain, including various neurotransmitter systems, are involved in the reinforcement effects of both food and drugs, suggesting that natural and pharmacological stimuli activate similar neural systems. In addition, several recent studies have identified a putative connection between neural circuits activated in the seeking and intake of both palatable food and drugs. The development of well-characterized animal models will increase our understanding of the etiological factors of food addiction and will help identify the neural substrates involved in eating disorders such as compulsive overeating. Such models will facilitate the development and validation of targeted pharmacological therapies.

  15. 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, panalysis 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. Generalized behavioral framework for choice models of social influence: Behavioral and data concerns in travel behavior

    NARCIS (Netherlands)

    M. Maness; C. Cirillo; E.R. Dugundji (Elenna)

    2015-01-01

    htmlabstractOver the past two decades, transportation has begun a shift from an individual focus to a social focus. Accordingly, discrete choice models have begun to integrate social context into its framework. Social influence, the process of having one’s behavior be affected by others, has been

  5. 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

  6. 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.

  7. 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.

  8. 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

    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...... of a low-complexity behavioral model of a railway turnout capable of capturing the dominant dynamics due to the ballast and railpad components. Measured rail accelerations, acquired through a receptance test carried out on the switch panel of a turnout of the Danish railway network, have been utilized...

  9. 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.

  10. Free Vibration Response of a Frame Structural Model Controlled by a Nonlinear Active Mass Driver System

    Directory of Open Access Journals (Sweden)

    Ilaria Venanzi

    2014-01-01

    Full Text Available Active control devices, such as active mass dampers, are mainly employed for the reduction of wind-induced vibrations in high-rise buildings, with the final aim of satisfying vibration serviceability limit state requirements and of meeting appropriate comfort criteria. When such active devices, normally operating under wind loads associated with short return periods, are subjected to seismic events, they can experience large amplitude vibrations and exceed stroke limits. This may lead to a reduced performance of the control system that can even worsen the performance of the whole structure. In this paper, a nonlinear control strategy based on a modified direct velocity feedback algorithm is proposed for handling stroke limits of an active mass driver (AMD system. In particular, a suitable nonlinear braking term proportional to the relative AMD velocity is included in the control law in order to slowdown the device in the proximity of the stroke limits. Experimental and numerical free vibration tests are carried out on a scaled-down five-story frame structure equipped with an AMD to demonstrate the effectiveness of the proposed control strategy.

  11. 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

  12. 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

  13. 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.

  14. Modeling of Transistor's Tracking Behavior in Compact Models

    Directory of Open Access Journals (Sweden)

    Ning Lu

    2011-01-01

    Full Text Available We present a novel method to model the tracking behavior of semiconductor transistors undergoing across-chip variations in a compact Monte Carlo model for SPICE simulations and show an enablement of simultaneous (−1/2 tracking relations among transistors on a chip at any poly density, any gate pitch, and any physical location for the first time. At smaller separations, our modeled tracking relation versus physical location reduces to Pelgrom's characterization on device's distance-dependent mismatch. Our method is very compact, since we do not use a matrix or a set of eigen solutions to represent correlations among transistors.

  15. 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.

  16. 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

  17. 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.

  18. 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)

  19. 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

  20. 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.

  1. 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.

  2. Mandatory Physician Reporting of At-Risk Drivers: The Older Driver Example.

    Science.gov (United States)

    Agimi, Yll; Albert, Steven M; Youk, Ada O; Documet, Patricia I; Steiner, Claudia A

    2017-01-09

    In a number of states, physicians are mandated by state law to report at-risk drivers to licensing authorities. Often these patients are older adult drivers who may exhibit unsafe driving behaviors, have functional/cognitive impairments, or are diagnosed with conditions such as Alzheimer's disease and/or seizure disorders. The hypothesis that mandatory physician reporting laws reduce the rate of crash-related hospitalizations among older adult drivers was tested. Using retrospective data (2004-2009), this study identified 176,066 older driver crash-related hospitalizations, from the State Inpatient Databases. Three age-specific negative binomial generalized estimating equation models were used to estimate the effect of physician reporting laws on state's incidence rate of crash-related hospitalizations among older drivers. No evidence was found for an independent association between mandatory physician reporting laws and a lower crash hospitalization rate among any of the age groups examined. The main predictor of interest, mandatory physician reporting, failed to explain any significant variation in crash hospitalization rates, when adjusting for other state-specific laws and characteristics. Vision testing at in-person license renewal was a significant predictor of lower crash hospitalization rate, ranging from incidence rate ratio of 0.77 (95% confidence interval 0.62-0.94) among 60- to 64-year olds to 0.83 (95% confidence interval 0.67-0.97) among 80- to 84-year olds. Physician reporting laws and age-based licensing requirements are often at odds with older driver's need to maintain independence. This study examines this balance and finds no evidence of the benefits of mandatory physician reporting requirements on driver crash hospitalizations, suggesting that physician mandates do not yet yield significant older driver safety benefits, possibly to the detriment of older driver's well-being and independence. © The Author 2017. Published by Oxford University

  3. 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.

  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. 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

  6. 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...

  7. 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

  8. 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...

  9. 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

  10. 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...

  11. 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...

  12. 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

    This paper develops an extension to established production- and supply chain management focused internationalisation models. It applies explorative case studies in Danish and Chinese engineering firms to discover how the globalisation process of product development differs from Danish and Chinese...... 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...

  13. 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...

  14. Process-oriented modelling to identify main drivers of erosion-induced carbon fluxes

    Science.gov (United States)

    Wilken, Florian; Sommer, Michael; Van Oost, Kristof; Bens, Oliver; Fiener, Peter

    2017-05-01

    Coupled modelling of soil erosion, carbon redistribution, and turnover has received great attention over the last decades due to large uncertainties regarding erosion-induced carbon fluxes. For a process-oriented representation of event dynamics, coupled soil-carbon erosion models have been developed. However, there are currently few models that represent tillage erosion, preferential water erosion, and transport of different carbon fractions (e.g. mineral bound carbon, carbon encapsulated by soil aggregates). We couple a process-oriented multi-class sediment transport model with a carbon turnover model (MCST-C) to identify relevant redistribution processes for carbon dynamics. The model is applied for two arable catchments (3.7 and 7.8 ha) located in the Tertiary Hills about 40 km north of Munich, Germany. Our findings indicate the following: (i) redistribution by tillage has a large effect on erosion-induced vertical carbon fluxes and has a large carbon sequestration potential; (ii) water erosion has a minor effect on vertical fluxes, but episodic soil organic carbon (SOC) delivery controls the long-term erosion-induced carbon balance; (iii) delivered sediments are highly enriched in SOC compared to the parent soil, and sediment delivery is driven by event size and catchment connectivity; and (iv) soil aggregation enhances SOC deposition due to the transformation of highly mobile carbon-rich fine primary particles into rather immobile soil aggregates.

  15. 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.

  16. On Spatially Explicit Models of Cholera Epidemics: Hydrologic controls, environmental drivers, human-mediated transmissions (Invited)

    Science.gov (United States)

    Rinaldo, A.; Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.

    2010-12-01

    A recently proposed model for cholera epidemics is examined. The model accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links which are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of water-borne pathogens. The results of a large-scale application to the Kwa Zulu (Natal) epidemics of 2001-2002 will be discussed. Useful theoretical results derived in the spatially-explicit context will also be reviewed (like e.g. the exact derivation of the speed of propagation for traveling fronts of epidemics on regular lattices endowed with uniform population density). Network effects will be discussed. The analysis of the limit case of uniformly distributed population density proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, it is shown that the ratio between spreading and disease outbreak timescales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the SIR-like type. Our results suggest that in many cases of real-life epidemiological interest timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. Finally, a view on further developments includes: hydrologically improved aquatic reservoir models for pathogens; human mobility patterns affecting disease propagation; double-peak emergence and seasonality in the spatially explicit epidemic context.

  17. 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

    , 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...

  18. Modelling environmental drivers of black band disease outbreaks in populations of foliose corals in the genus Montipora

    Directory of Open Access Journals (Sweden)

    Carla C.M. Chen

    2017-06-01

    Full Text Available Seawater temperature anomalies associated with warming climate have been linked to increases in coral disease outbreaks that have contributed to coral reef declines globally. However, little is known about how seasonal scale variations in environmental factors influence disease dynamics at the level of individual coral colonies. In this study, we applied a multi-state Markov model (MSM to investigate the dynamics of black band disease (BBD developing from apparently healthy corals and/or a precursor-stage, termed ‘cyanobacterial patches’ (CP, in relation to seasonal variation in light and seawater temperature at two reef sites around Pelorus Island in the central sector of the Great Barrier Reef. The model predicted that the proportion of colonies transitioning from BBD to Healthy states within three months was approximately 57%, but 5.6% of BBD cases resulted in whole colony mortality. According to our modelling, healthy coral colonies were more susceptible to BBD during summer months when light levels were at their maxima and seawater temperatures were either rising or at their maxima. In contrast, CP mostly occurred during spring, when both light and seawater temperatures were rising. This suggests that environmental drivers for healthy coral colonies transitioning into a CP state are different from those driving transitions into BBD. Our model predicts that (1 the transition from healthy to CP state is best explained by increasing light, (2 the transition between Healthy to BBD occurs more frequently from early to late summer, (3 20% of CP infected corals developed BBD, although light and temperature appeared to have limited impact on this state transition, and (4 the number of transitions from Healthy to BBD differed significantly between the two study sites, potentially reflecting differences in localised wave action regimes.

  19. 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.

  20. A cellular automation model accounting for bicycle's group behavior

    Science.gov (United States)

    Tang, Tie-Qiao; Rui, Ying-Xu; Zhang, Jian; Shang, Hua-Yan

    2018-02-01

    Recently, bicycle has become an important traffic tool in China, again. Due to the merits of bicycle, the group behavior widely exists in urban traffic system. However, little effort has been made to explore the impacts of the group behavior on bicycle flow. In this paper, we propose a CA (cellular automaton) model with group behavior to explore the complex traffic phenomena caused by shoulder group behavior and following group behavior on an open road. The numerical results illustrate that the proposed model can qualitatively describe the impacts of the two kinds of group behaviors on bicycle flow and that the effects are related to the mode and size of group behaviors. The results can help us to better understand the impacts of the bicycle's group behaviors on urban traffic system and effectively control the bicycle's group behavior.

  1. 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.

  2. 21st Century Change Drivers: Considerations for Constructing Transformative Models of Special Education Teacher Development

    Science.gov (United States)

    Rock, Marcia L.; Spooner, Fred; Nagro, Sarah; Vasquez, Eleazar; Dunn, Cari; Leko, Melinda; Luckner, John; Bausch, Margaret; Donehower, Claire; Jones, Jennie L.

    2016-01-01

    Contemporary challenges confronting special education teachers include, in part, workload, role ambiguity, evaluation, and shortages. Based on these and other challenges, the piece-meal fragmented approach to pre- and in-service training, which exists currently, needs to be replaced with 21st century models of special education teacher development…

  3. 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.

  4. Land Use as a Driver of Patterns of Rodenticide Exposure in Modeled Kit Fox Populations.

    Directory of Open Access Journals (Sweden)

    Theresa M Nogeire

    Full Text Available Although rodenticides are increasingly regulated, they nonetheless cause poisonings in many non-target wildlife species. Second-generation anticoagulant rodenticide use is common in agricultural and residential landscapes. Here, we use an individual-based population model to assess potential population-wide effects of rodenticide exposures on the endangered San Joaquin kit fox (Vulpes macrotis mutica. We estimate likelihood of rodenticide exposure across the species range for each land cover type based on a database of reported pesticide use and literature. Using a spatially-explicit population model, we find that 36% of modeled kit foxes are likely exposed, resulting in a 7-18% decline in the range-wide modeled kit fox population that can be linked to rodenticide use. Exposures of kit foxes in low-density developed areas accounted for 70% of the population-wide exposures to rodenticides. We conclude that exposures of non-target kit foxes could be greatly mitigated by reducing the use of second-generation anticoagulant rodenticides in low-density developed areas near vulnerable populations.

  5. 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.

  6. 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.

  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. Cognitive-Operative Model of Intelligent Learning Systems Behavior

    Science.gov (United States)

    Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; Mora-Torres, Martha; de Arriaga, Fernando; Escarela-Perez, Rafael

    2010-01-01

    In this paper behavior during the teaching-learning process is modeled by means of a fuzzy cognitive map. The elements used to model such behavior are part of a generic didactic model, which emphasizes the use of cognitive and operative strategies as part of the student-tutor interaction. Examples of possible initial scenarios for the…

  9. Sensitivity of fire behavior simulations to fuel model variations

    Science.gov (United States)

    Lucy A. Salazar

    1985-01-01

    Stylized fuel models, or numerical descriptions of fuel arrays, are used as inputs to fire behavior simulation models. These fuel models are often chosen on the basis of generalized fuel descriptions, which are related to field observations. Site-specific observations of fuels or fire behavior in the field are not readily available or necessary for most fire management...

  10. 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

  11. Modelling drivers of mangrove propagule dispersal and restoration of abandoned shrimp farms

    Science.gov (United States)

    Di Nitto, D.; Erftemeijer, P. L. A.; van Beek, J. K. L.; Dahdouh-Guebas, F.; Higazi, L.; Quisthoudt, K.; Jayatissa, L. P.; Koedam, N.

    2013-07-01

    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 value of propagule

  12. Case-Based Reasoning for Human Behavior Modeling

    Science.gov (United States)

    2006-02-16

    edition may be used. Case Based Reasoning for Human Behavior Modeling CDRL A002 for Contract N00014-03-C-0178 February 16, 2006 Document...maintaining a useful repository demand that reuse be supported for human behavior modeling even if other model construction aids are also available...et al. (2001). Results of the Common Human Behavior Representation And Interchange System (CHRIS) Workshop. Fall 2001 Simulation Interoperability

  13. State-Space Modelling of the Drivers of Movement Behaviour in Sympatric Species.

    Directory of Open Access Journals (Sweden)

    F J Pérez-Barbería

    Full Text Available Understanding animal movement behaviour is key to furthering our knowledge on intra- and inter-specific competition, group cohesion, energy expenditure, habitat use, the spread of zoonotic diseases or species management. We used a radial basis function surface approximation subject to minimum description length constraint to uncover the state-space dynamical systems from time series data. This approximation allowed us to infer structure from a mathematical model of the movement behaviour of sheep and red deer, and the effect of density, thermal stress and vegetation type. Animal movement was recorded using GPS collars deployed in sheep and deer grazing a large experimental plot in winter and summer. Information on the thermal stress to which animals were exposed was estimated using the power consumption of mechanical heated models and meteorological records of a network of stations in the plot. Thermal stress was higher in deer than in sheep, with less differences between species in summer. Deer travelled more distance than sheep, and both species travelled more in summer than in winter; deer travel distance showed less seasonal differences than sheep. Animal movement was better predicted in deer than in sheep and in winter than in summer; both species showed a swarming behaviour in group cohesion, stronger in deer. At shorter separation distances swarming repulsion was stronger between species than within species. At longer separation distances inter-specific attraction was weaker than intra-specific; there was a positive density-dependent effect on swarming, and stronger in deer than in sheep. There was not clear evidence which species attracted or repelled the other; attraction between deer at long separation distances was stronger when the model accounted for thermal stress, but in general the dynamic movement behaviour was hardly affected by the thermal stress. Vegetation type affected intra-species interactions but had little effect on

  14. State-Space Modelling of the Drivers of Movement Behaviour in Sympatric Species.

    Science.gov (United States)

    Pérez-Barbería, F J; Small, M; Hooper, R J; Aldezabal, A; Soriguer-Escofet, R; Bakken, G S; Gordon, I J

    2015-01-01

    Understanding animal movement behaviour is key to furthering our knowledge on intra- and inter-specific competition, group cohesion, energy expenditure, habitat use, the spread of zoonotic diseases or species management. We used a radial basis function surface approximation subject to minimum description length constraint to uncover the state-space dynamical systems from time series data. This approximation allowed us to infer structure from a mathematical model of the movement behaviour of sheep and red deer, and the effect of density, thermal stress and vegetation type. Animal movement was recorded using GPS collars deployed in sheep and deer grazing a large experimental plot in winter and summer. Information on the thermal stress to which animals were exposed was estimated using the power consumption of mechanical heated models and meteorological records of a network of stations in the plot. Thermal stress was higher in deer than in sheep, with less differences between species in summer. Deer travelled more distance than sheep, and both species travelled more in summer than in winter; deer travel distance showed less seasonal differences than sheep. Animal movement was better predicted in deer than in sheep and in winter than in summer; both species showed a swarming behaviour in group cohesion, stronger in deer. At shorter separation distances swarming repulsion was stronger between species than within species. At longer separation distances inter-specific attraction was weaker than intra-specific; there was a positive density-dependent effect on swarming, and stronger in deer than in sheep. There was not clear evidence which species attracted or repelled the other; attraction between deer at long separation distances was stronger when the model accounted for thermal stress, but in general the dynamic movement behaviour was hardly affected by the thermal stress. Vegetation type affected intra-species interactions but had little effect on inter

  15. 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

  16. Assessing Environmental Drivers of DOC Fluxes in the Shark River Estuary: Modeling the Effects of Climate, Hydrology and Water Management

    Science.gov (United States)

    Regier, P.; Briceno, H.; Jaffe, R.

    2016-02-01

    Urban and agricultural development of the South Florida peninsula has disrupted freshwater flow in the Everglades, a hydrologically connected ecosystem stretching from central Florida to the Gulf of Mexico. Current system-scale restoration efforts aim to restore natural hydrologic regimes to reestablish pre-drainage ecosystem functioning through increased water availability, quality and timing. However, it is uncertain how hydrologic restoration combined with climate change will affect the downstream section of the system, including the mangrove estuaries of Everglades National Park. Aquatic transport of carbon, primarily as dissolved organic carbon (DOC), plays a critical role in biogeochemical cycling and food-web dynamics, and will be affected both by water management policies and climate change. To better understand DOC dynamics in these estuaries and how hydrology, climate and water management may affect them, 14 years of monthly data collected in the Shark River estuary were used to build a DOC flux model. Multi-variate methods were applied to long-term data-sets for hydrology, water quality and climate to untangle the interconnected environmental drivers that control DOC export at intra and inter-annual scales. DOC fluxes were determined to be primarily controlled by hydrology but also by seasonality and long-term climate patterns. Next, a 4-component model (salinity, inflow, rainfall, Atlantic Multidecadal Oscillation) capable of predicting DOC fluxes (R2=0.78, p<0.0001, n=161) was established. Finally, potential climate change scenarios for the Everglades were applied to this model to assess DOC flux variations in response to climate and restoration variables. Although global predictions anticipate that DOC export will generally increase in the future, the majority of scenario runs indicated that DOC export from the Everglades is expected to decrease due to changes in rainfall, evapotranspiration, inflows and sea-level rise.

  17. 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)

  18. 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.

  19. 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

  20. Psychological drivers in doping: the life-cycle model of performance enhancement.

    Science.gov (United States)

    Petróczi, Andrea; Aidman, Eugene

    2008-03-10

    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. 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. 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. 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 intervention. The model suggests that, instead of focusing on the actual engagement in prohibited

  1. 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

  2. Mammary-Stem-Cell-Based Somatic Mouse Models Reveal Breast Cancer Drivers Causing Cell Fate Dysregulation

    Directory of Open Access Journals (Sweden)

    Zheng Zhang

    2016-09-01

    Full Text Available Cancer genomics has provided an unprecedented opportunity for understanding genetic causes of human cancer. However, distinguishing which mutations are functionally relevant to cancer pathogenesis remains a major challenge. We describe here a mammary stem cell (MaSC organoid-based approach for rapid generation of somatic genetically engineered mouse models (GEMMs. By using RNAi and CRISPR-mediated genome engineering in MaSC-GEMMs, we have discovered that inactivation of Ptpn22 or Mll3, two genes mutated in human breast cancer, greatly accelerated PI3K-driven mammary tumorigenesis. Using these tumor models, we have also identified genetic alterations promoting tumor metastasis and causing resistance to PI3K-targeted therapy. Both Ptpn22 and Mll3 inactivation resulted in disruption of mammary gland differentiation and an increase in stem cell activity. Mechanistically, Mll3 deletion enhanced stem cell activity through activation of the HIF pathway. Thus, our study has established a robust in vivo platform for functional cancer genomics and has discovered functional breast cancer mutations.

  3. 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

    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 halothermodynamic sea ice model including gas physics and carbon biogeochemistry. The ice-ocean fluxes, and vertical transport...... 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...... 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...

  4. A refined cellular automaton model to rectify impractical vehicular movement behavior

    Science.gov (United States)

    Lan, Lawrence W.; Chiou, Yu-Chiun; Lin, Zih-Shin; Hsu, Chih-Cheng

    2009-09-01

    When implementing cellular automata (CA) into a traffic simulation, one common defect yet to be rectified is the abrupt deceleration when vehicles encounter stationary obstacles or traffic jams. To be more in line with real world vehicular movement, this paper proposes a piecewise-linear movement to replace the conventional particle-hopping movement adopted in most previous CA models. Upon this adjustment and coupled with refined cell system, a new CA model is developed using the rationale of Forbes’ et al. car-following concept. The proposed CA model is validated on a two-lane freeway mainline context. It shows that this model can fix the unrealistic deceleration behaviors, and thus can reflect genuine driver behavior in the real world. The model is also capable of revealing Kerner’s three-phase traffic patterns and phase transitions among them. Furthermore, the proposed CA model is applied to simulate a highway work zone wherein traffic efficiency (maximum flow rates) and safety (speed deviations) impacted by various control schemes are tested.

  5. Behavior modeling through CHAOS for simulation of dismounted soldier operations

    NARCIS (Netherlands)

    Ubink, E.; Aldershoff, F.; Lotens, W.A.; Woering, A.

    2003-01-01

    One of the major challenges in human behavior modeling for military applications is dealing with all factors that can influence behavior and performance. In a military context, behavior and performance are influenced by the task at hand, the internal (cognitive and physiological) and external

  6. Estimating total manoeuvring time of drivers using Gamma ...

    African Journals Online (AJOL)

    The ages of drivers, service period of vehicles, and pavement conditions were also obtained by interviewing the drivers. A model of cumul-ative response times of driver-vehicle-road interaction developed indicated that TMT was contributed by the interactions of driver perception-reaction time, steering time and vehicle ...

  7. DIRECT operational field test evaluation natural use study. Part 3, Evaluation of driver behavior and measurement of effectiveness of DIRECT communications technologies based on vehicle tracking around incidents

    Science.gov (United States)

    1998-08-01

    Vehicle tracking systems were installed on all DIRECT vehicles to help investigate the : relationships between the drivers actual travel experiences and their opinions about the : systems they used. The purpose of this report is to look more caref...

  8. Tumoral stem cell reprogramming as a driver of cancer: Theory, biological models, implications in cancer therapy.

    Science.gov (United States)

    Vicente-Dueñas, Carolina; Hauer, Julia; Ruiz-Roca, Lucía; Ingenhag, Deborah; Rodríguez-Meira, Alba; Auer, Franziska; Borkhardt, Arndt; Sánchez-García, Isidro

    2015-06-01

    Cancer is a clonal malignant disease originated in a single cell and characterized by the accumulation of partially differentiated cells that are phenotypically reminiscent of normal stages of differentiation. According to current models, therapeutic strategies that block oncogene activity are likely to selectively target tumor cells. However, recent evidences have revealed that cancer stem cells could arise through a tumor stem cell reprogramming mechanism, suggesting that genetic lesions that initiate the cancer process might be dispensable for tumor progression and maintenance. This review addresses the impact of these results toward a better understanding of cancer development and proposes new approaches to treat cancer in the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. 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.

  10. 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

  11. The Integrated Gateway Model: a catalytic approach to behavior change.

    Science.gov (United States)

    Schwandt, Hilary M; Skinner, Joanna; Takruri, Adel; Storey, Douglas

    2015-08-01

    To develop and test an Integrated Gateway Model of behaviors and factors leading to subsequent positive reproductive, maternal, and child health behaviors. A secondary analysis was conducted using previously published household survey data collected from men (n=5551; 2011) and women (n=16144; 2011) in Nigeria and women in Egypt (n=2240; 2004-2007). The number of health behaviors each potential gateway behavior predicted was assessed by multivariate regression, adjusting for potential confounders. The influence of gateway factors on gateway behaviors was tested via interaction terms. Gateway behaviors and factors were ranked by the number of health outcomes predicted, both separately and synergistically. The key gateway behavior identified in both datasets was spousal communication about family planning, whereas the key gateway factor was exposure to family planning messages. The model could facilitate innovative research and programming that in turn might promote cascades of positive behaviors in reproductive, maternal, and child health. Copyright © 2015. Published by Elsevier Ireland Ltd.

  12. Compliance with traffic laws by traffic police officers, non-traffic police officers, and civilian drivers.

    Science.gov (United States)

    Rosenbloom, Tova; Pereg, Avihu; Perlman, Amotz

    2014-01-01

    The policy of a public organization, such as police, may shape the norms and the behavior of the citizens. In line with this, police officers are expected by the public to comply with traffic laws and serve as an example for the citizenry. This study used on-site observations of civilian and police driver, comparing police officers' compliance with traffic laws to that of civilians. We compared driver compliance with traffic laws for drivers in 3 groups of vehicles: traffic police cars, non-traffic police cars, and civilian cars. Four hundred sixty-six vehicles were observed and compared by vehicle type and whether a uniform was worn by the driver. We observed safety belt usage, signaling before turning, cellular phone usage, and giving way to traffic (measured by merging time). We found evidence that generally drivers in police cars use seat belts while driving more that drivers in civilian cars do. In particular, more traffic police car drivers used seat belts than non-traffic police car drivers do. In addition, drivers in civilian cars and non-traffic police cars waited longer periods of time before merging right into traffic compared to traffic police car drivers. Our findings supported the notion that on-duty police officers, and traffic police officers in particular, adhere more closely to traffic laws compared to civilian drivers. As the general public compliance with traffic laws is affected by the police perceived legitimacy, the publication of these results can both boost public cooperation with the police and encourage police officers to continue providing positive role models to the public.

  13. Driver Anger Scale (DAS Among Car Drivers: How Serious Are They?

    Directory of Open Access Journals (Sweden)

    Ambak Kamarudin

    2017-01-01

    Full Text Available Nowadays, anger while driving on the road is a crucial issue in Malaysia. The anger of driver may lead to traffic crashes. Road accident issue is an important agenda in every country. Driver behaviour and attitude such as impatience, hasty and hot-tempered on the road has become one of the causes in road accidents. Uncontrolled anger will affect the behavior of oneself during driving and could cause an individual to display aggressive attitude. Therefore, this study is aimed to identify contributing factor in anger of drivers and evaluate the Driver Anger Scale (DAS in Batu Pahat, Johor. In addition, this study also analyzes the relationship between driver anger and the factor of DAS. Cross sectional study method was conducted in this study by distributing 250 questionnaires to car drivers. The data collectied was analyzed by descriptive, chi-square test, correlation and regression analysis using Statistical Package for Social Sciences (SPSS version 20.0. The findings show that the discourtesy was reported as the most dominant factor contributing to driver anger. As a recommendation, to overcome driver anger issue, the authorities should prepare an action plan, promote and nurture public to practice good driving behaviour. Moreover, curriculum and driver training lesson should be improved to create better attitude among drivers. Drivers also should change their driving attitude by becoming safe drivers and exhibiting defensive driving skills on the road.

  14. Standard fire behavior fuel models: a comprehensive set for use with Rothermel's surface fire spread model

    Science.gov (United States)

    Joe H. Scott; Robert E. Burgan

    2005-01-01

    This report describes a new set of standard fire behavior fuel models for use with Rothermel's surface fire spread model and the relationship of the new set to the original set of 13 fire behavior fuel models. To assist with transition to using the new fuel models, a fuel model selection guide, fuel model crosswalk, and set of fuel model photos are provided.

  15. Foreign ownership as a driver of qualiaty management in Slovak agribusiness: applying MBNQA model

    Directory of Open Access Journals (Sweden)

    Radovan Savov

    2017-06-01

    Full Text Available Despite attention being paid to quality management in the literature, little empirical research has been conducted on developing the link between adoption of quality management approach and business performance in agricultural enterprises, and moreover, only a few empirical studies have investigated this issue in Central and Eastern Europe. The conducted empirical survey examines the relationship between adopting the quality management approach and business performance from the perspective of agricultural enterprises in Slovakia. The empirical findings are based on 70 responses from agribusinesses in Slovak Republic. To measure the adopting of quality management approach the MBNQA model was used. The authors have used linear regression as an evaluation method. Based on the results it can be concluded the adopting of quality management approach is determined by ownership. The enterprises owned by the owner from abroad adopt the quality management approach more readily than the domestic ones. This study contributes to the European research that studies the relation between quality management and business performance of agribusinesses by means of an empirical investigation in agricultural organizations in a transition economy such as Slovakia.

  16. 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

  17. Social and Behavioral Science: Monitoring Social Foraging Behavior in a Biological Model System

    Science.gov (United States)

    2016-10-12

    stratification (i.e., caste system ) that characterizes both and leads to some actors in the groups being more susceptible to disease and other risks. The RFID...Social Foraging Behavior in a Biological Model System " The views, opinions and/or findings contained in this report are those of the author(s) and...reviewed journals: Final Report: "Social and Behavioral Science: Monitoring Social Foraging Behavior in a Biological Model System " Report Title The

  18. 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.)

  19. 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

  20. 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

  1. A path-following driver-vehicle model with neuromuscular dynamics, including measured and simulated responses to a step in steering angle overlay

    Science.gov (United States)

    Cole, David J.

    2012-04-01

    An existing driver-vehicle model with neuromuscular dynamics is improved in the areas of cognitive delay, intrinsic muscle dynamics and alpha-gamma co-activation. The model is used to investigate the influence of steering torque feedback and neuromuscular dynamics on the vehicle response to lateral force disturbances. When steering torque feedback is present, it is found that the longitudinal position of the lateral disturbance has a significant influence on whether the driver's reflex response reinforces or attenuates the effect of the disturbance. The response to angle and torque overlay inputs to the steering system is also investigated. The presence of the steering torque feedback reduced the disturbing effect of torque overlay and angle overlay inputs. Reflex action reduced the disturbing effect of a torque overlay input, but increased the disturbing effect of an angle overlay input. Experiments on a driving simulator showed that measured handwheel angle response to an angle overlay input was consistent with the response predicted by the model with reflex action. However, there was significant intra- and inter-subject variability. The results highlight the significance of a driver's neuromuscular dynamics in determining the vehicle response to disturbances.

  2. UAV Swarm Behavior Modeling for Early Exposure of Failure Modes

    Science.gov (United States)

    2016-09-01

    Figure 6. Swarm vs. Swarm Event Trace Graph .......................................................10 Figure 7. PACOM Crimson Viper 2010 Exercise ...method for modeling behaviors of the software, hardware, business processes, and other parts of the system. The event grammar models the behavior as a...ability to represent events in various patterns. Table 1 describes the various patterns in both natural language and MP event grammar . These

  3. 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.

  4. 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.

  5. Inovação & propriedade intelectual: panorama dos agentes motores de desenvolvimento e inovação Innovation & intellectual property: behavior of innovation and development drivers

    Directory of Open Access Journals (Sweden)

    Flávio Pietrobon-Costa

    2012-01-01

    producers, and innovation property agents. Indicators of economic growth, scientific production, and innovation generation of Brazil and Bahia State were analyzed investigating their relationships and observing, by time series, the behavior of drivers of development and innovation and their influences. It was found that that these three actors (or agents are interdependent and interactive. For a substantial investment in scientific research and intellectual property, the economic producers must be growth-oriented to achieve strong competitive advantage. For a sustainable development of human society, a simultaneous investment in scientific research, technology, and innovations is needed with continuous active support of innovation agents.

  6. Accounting for the Uncertainty Related to Building Occupants with Regards to Visual Comfort: A Literature Survey on Drivers and Models

    Directory of Open Access Journals (Sweden)

    Valentina Fabi

    2016-02-01

    Full Text Available The interactions between building occupants and control systems have a high influence on energy consumption and on indoor environmental quality. In the perspective of a future of “nearly-zero” energy buildings, it is crucial to analyse the energy-related interactions deeply to predict realistic energy use during the design stage. Since the reaction to thermal, acoustic, or visual stimuli is not the same for every human being, monitoring the behaviour inside buildings is an essential step to assert differences in energy consumption related to different interactions. Reliable information concerning occupants’ behaviours in a building could contribute to a better evaluation of building energy performances and design robustness, as well as supporting the development of occupants’ education to energy awareness. The present literature survey enlarges our understanding of which environmental conditions influence occupants’ manual controlling of the system in offices and by consequence the energy consumption. The purpose of this study was to investigate the possible drivers for light-switching to model occupant behaviour in office buildings. The probability of switching lighting systems on or off was related to the occupancy and differentiated for arrival, intermediate, and departure periods. The switching probability has been reported to be higher during the entering or the leaving time in relation to contextual variables. In the analysis of switch-on actions, users were often clustered between those who take daylight level into account and switch on lights only if necessary and people who totally disregard the natural lighting. This underlines the importance of how individuality is at the base of the definition of the different types of users.

  7. Dominant-submissive behavior as models of mania and depression.

    Science.gov (United States)

    Malatynska, Ewa; Knapp, Richard J

    2005-01-01

    This review examines the ways in which dominant-subordinate behavior in animals, as determined in laboratory studies, can be used to model depression and mania in humans. Affective disorders are mood illnesses with two opposite poles, melancholia (depression) and mania that are expressed to different degrees in affected individuals. Dominance and submissiveness are also two contrasting behavioral poles distributed as a continuum along an axis with less or more dominant or submissive animals. The premise of this article is that important elements of both mania and depression can be modeled in rats and mice based on observation of dominant and submissive behavior exhibited under well defined conditions. Studies from our own research, where dominance and submissiveness are defined in a competition test and measured as the relative success of two food-restricted rats to gain access to a feeder, have yielded a paradigm that we call the Dominant Submissive Relationship (DSR). This paradigm results in two models sensitive to drugs used to treat mood disorders. Specifically, drugs used to treat mania inhibit the dominant behavior of rats gaining access to food at the expense of an opponent (Reduction of Dominant Behavior Model or RDBM), whereas antidepressants counteract the behavior of rats losing such encounters; Reduction of Submissive Behavior Model (RSBM). The validation of these models, as well as their advantages and limitations, are discussed and compared with other animal paradigms that utilize animal social behavior to model human mood disturbances.

  8. The HEXACO Model of Personality and Risky Driving Behavior.

    Science.gov (United States)

    Burtăverde, Vlad; Chraif, Mihaela; Aniţei, Mihai; Dumitru, Daniela

    2017-04-01

    This research tested the association between the HEXACO personality model and risky driving behavior as well as the predictive power of the HEXACO model in explaining risky driving behavior compared with the Big Five model. In Sample 1, 227 undergraduate students completed measures of the HEXACO personality model, the Big Five model, and driving aggression. In Sample 2, 244 community respondents completed measures of the HEXACO personality model, the Big Five model, and driving styles. Results showed that the Honesty-Humility factor is an important addition to personality models that aim to explain risky driving behavior as being related to all forms of driving aggression as well as to maladaptive and adaptive driving styles and having incremental validity in predicting verbally aggressive expression, risky driving, high-velocity driving, and careful driving. Moreover, compared with the Big Five model, the HEXACO model had better predictive power of aggressive driving.

  9. Drivers for Welfare Innovation

    DEFF Research Database (Denmark)

    Wegener, Charlotte

    2015-01-01

    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......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...

  10. 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.

  11. Understanding hydro-climatic drivers of infectious diarrheal diseases in South Asia and their projected risks from regional climate models

    Science.gov (United States)

    Hasan, M. A.; Akanda, A. S.; Jutla, A.; Huq, A.; Colwell, R. R.

    2017-12-01

    Diarrheal diseases remain a major threat to global public health and are the second largest cause of death for children under the age of five. Cholera and Rotavirus diarrhea together comprise more than two-thirds of the diarrheal morbidity in South Asia. Recent studies have shown strong influences of hydrologic processes and climatic variabilities on the onset, intensity, and seasonality of the outbreaks of these diseases. However, our understanding of the propagation and manifestation of these diseases in a changing climate in vulnerable regions of the world are still limited. In this study, we build on our understanding of the role of the hydro-climatic drivers of diarrheal diseases in South Asia in recent decades to project the probable risks of the diseases in this century using the climate projection scenarios from dynamically downscaled climate models. To build the current model, we conducted a multivariate logistic regression assessment using 34 climate indices to examine the role of temperature and rainfall extremes over the seasonality of rotavirus and cholera over a South Asian country, Bangladesh. We utilize the availability of long and reliable time-series of cholera and rotavirus from Bangladesh and conducted a temporal and spatial analysis derived from both ground and satellite observations. For projecting the future risks of the diseases, we used five bias-corrected Regional Climate Model (RCM) results of the CMIP5 series under the RCP 4.5 scenario. Cholera risk shows a significantly higher rate of increase compared to Rotavirus in Bangladesh in the 21st century. As the disease is significantly influenced by extreme rainfall, majority projections showed a significant increase in flood-driven cholera risk. Most RCMs suggest a warmer winter in future years, suggesting reduced risk for Rotavirus. However, as the dryness of the climate is also highly correlated with rotavirus epidemics, the incremental risk of the disease due to drier winters would

  12. 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.

  13. Resolving key drivers of variability through an important circulation choke point in the western Mediterranean Sea; using gliders, models & satellite remote sensing

    Science.gov (United States)

    Heslop, Emma; Aguiar, Eva; Mourre, Baptiste; Juza, Mélanie; Escudier, Romain; Tintoré, Joaquín

    2017-04-01

    The Ibiza Channel plays an important role in the circulation of the Western Mediterranean Sea, it governs the north/south exchange of different water masses that are known to affect regional ecosystems and is influenced by variability in the different drivers that affect sub-basins to the north (N) and south (S). A complex system. In this study we use a multi-platform approach to resolve the key drivers of this variability, and gain insight into the inter-connection between the N and S of the Western Mediterranean Sea through this choke point. The 6-year glider time series from the quasi-continuous glider endurance line monitoring of the Ibiza Channel, undertaken by SOCIB (Balearic Coastal Ocean observing and Forecasting System), is used as the base from which to identify key sub-seasonal to inter-annual patterns and shifts in water mass properties and transport volumes. The glider data indicates the following key components in the variability of the N/S flow of different water mass through the channel; regional winter mode water production, change in intermediate water mass properties, northward flows of a fresher water mass and the basin-scale circulation. To resolve the drivers of these components of variability, the strength of combining datasets from different sources, glider, modeling, altimetry and moorings, is harnessed. To the north atmospheric forcing in the Gulf of Lions is a dominant driver, while to the south the mesoscale circulation patterns of the Atlantic Jet and Alboran gyres dominate the variability but do not appear to influence the fresher inflows. Evidence of a connection between the northern and southern sub-basins is however indicated. The study highlights importance of sub-seasonal variability and the scale of rapid change possible in the Mediterranean, as well as the benefits of leveraging high resolution glider datasets within a multi-platform and modelling study.

  14. 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.

  15. 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.

  16. An Ontology-Based Framework for Modeling User Behavior

    DEFF Research Database (Denmark)

    Razmerita, Liana

    2011-01-01

    This paper focuses on the role of user modeling and semantically enhanced representations for personalization. This paper presents a generic Ontology-based User Modeling framework (OntobUMf), its components, and its associated user modeling processes. This framework models the behavior of the users...... and classifies its users according to their behavior. The user ontology is the backbone of OntobUMf and has been designed according to the Information Management System Learning Information Package (IMS LIP). The user ontology includes a Behavior concept that extends IMS LIP specification and defines....... The results of this research may contribute to the development of other frameworks for modeling user behavior, other semantically enhanced user modeling frameworks, or other semantically enhanced information systems....

  17. 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.

  18. Modeling cancer driver events in vitro using barrier bypass-clonal expansion assays and massively parallel sequencing.

    Science.gov (United States)

    Huskova, H; Ardin, M; Weninger, A; Vargova, K; Barrin, S; Villar, S; Olivier, M; Stopka, T; Herceg, Z; Hollstein, M; Zavadil, J; Korenjak, M

    2017-10-26

    The information on candidate cancer driver alterations available from public databases is often descriptive and of limited mechanistic insight, which poses difficulties for reliable distinction between true driver and passenger events. To address this challenge, we performed in-depth analysis of whole-exome sequencing data from cell lines generated by a barrier bypass-clonal expansion (BBCE) protocol. The employed strategy is based on carcinogen-driven immortalization of primary mouse embryonic fibroblasts and recapitulates early steps of cell transformation. Among the mutated genes were almost 200 COSMIC Cancer Gene Census genes, many of which were recurrently affected in the set of 25 immortalized cell lines. The alterations affected pathways regulating DNA damage response and repair, transcription and chromatin structure, cell cycle and cell death, as well as developmental pathways. The functional impact of the mutations was strongly supported by the manifestation of several known cancer hotspot mutations among the identified alterations. We identified a new set of genes encoding subunits of the BAF chromatin remodeling complex that exhibited Ras-mediated dependence on PRC2 histone methyltransferase activity, a finding that is similar to what has been observed for other BAF subunits in cancer cells. Among the affected BAF complex subunits, we determined Smarcd2 and Smarcc1 as putative driver candidates not yet fully identified by large-scale cancer genome sequencing projects. In addition, Ep400 displayed characteristics of a driver gene in that it showed a mutually exclusive mutation pattern when compared with mutations in the Trrap subunit of the TIP60 complex, both in the cell line panel and in a human tumor data set. We propose that the information generated by deep sequencing of the BBCE cell lines coupled with phenotypic analysis of the mutant cells can yield mechanistic insights into driver events relevant to human cancer development.

  19. 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.

  20. 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.

  1. Human Performance Models of Pilot Behavior

    Science.gov (United States)

    Foyle, David C.; Hooey, Becky L.; Byrne, Michael D.; Deutsch, Stephen; Lebiere, Christian; Leiden, Ken; Wickens, Christopher D.; Corker, Kevin M.

    2005-01-01

    Five modeling teams from industry and academia were chosen by the NASA Aviation Safety and Security Program to develop human performance models (HPM) of pilots performing taxi operations and runway instrument approaches with and without advanced displays. One representative from each team will serve as a panelist to discuss their team s model architecture, augmentations and advancements to HPMs, and aviation-safety related lessons learned. Panelists will discuss how modeling results are influenced by a model s architecture and structure, the role of the external environment, specific modeling advances and future directions and challenges for human performance modeling in aviation.

  2. 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...

  3. 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

  4. 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

  5. A Neuropsychological Model of Mentally Tough Behavior.

    Science.gov (United States)

    Hardy, Lew; Bell, James; Beattie, Stuart

    2014-02-01

    Four studies were conducted with two primary objectives: (a) to conceptualize and measure mental toughness from a behavioral perspective and (b) to apply relevant personality theory to the examination of between-person differences in mentally tough behavior. Studies 1 (N = 305 participants from a range of different sports) and 2 (N = 110 high-level cricketers) focused on the development of an informant-rated mental toughness questionnaire that assessed individual differences in ability to maintain or enhance performance under pressure from a wide range of stressors. Studies 3 (N = 214) and 4 (N = 196) examined the relationship between reinforcement sensitivities and mentally tough behavior in high-level cricketers. The highest levels of mental toughness reported by coaches occurred when cricketers were sensitive to punishment and insensitive to reward. Study 4 suggested that such players are predisposed to identify threatening stimuli early, which gives them the best possible opportunity to prepare an effective response to the pressurized environments they encounter. The findings show that high-level cricketers who are punishment sensitive, but not reward sensitive, detect threat early and can maintain goal-directed behavior under pressure from a range of different stressors. © 2013 Wiley Periodicals, Inc.

  6. 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…

  7. Tradeoffs of vertical-cavity surface emitting lasers modeling for the development of driver circuits in short distance optical links

    Science.gov (United States)

    Sialm, Gion; Erni, Daniel; Vez, Dominique; Kromer, Christian; Ellinger, Frank; Bona, Gian-Luca; Morf, Thomas; Jäckel, Heinz

    2005-10-01

    In short-distance optical links, the development of driving circuits for vertical-cavity surface-emitting lasers (VCSELs) requires precise and computationally efficient VCSEL models. A small-signal model of a VCSEL is computationally efficient and simple to implement; however, it does not take into account the nonlinear output behavior of the VCSEL. In contrast, VCSEL models that are highly based on first principles cannot be implemented in standard circuit device simulators, because the simulation of eye diagrams becomes too time consuming. We present another approach using VCSEL models, which are based on the 1-D rate equations. Our analysis shows that they combine efficient extraction and short simulation time with an accurate calculation of eye diagrams over a wide range of ambient temperatures. As different implementations of the rate equations exist, tradeoffs between three different versions are presented and compared with measured GaAs oxide-confined VCSELs. The first model has a linear and the second a logarithmic function of the gain versus the carrier density. The third model considers the additional transport time for carriers to reach the active region with quantum wells. For parameter extraction, a minimum set of parameters is identified, which can be determined from fundamental measurements.

  8. 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...

  9. Traffic Behavior Recognition Using the Pachinko Allocation Model.

    Science.gov (United States)

    Huynh-The, Thien; Banos, Oresti; Le, Ba-Vui; Bui, Dinh-Mao; Yoon, Yongik; Lee, Sungyoung

    2015-07-03

    CCTV-based behavior recognition systems have gained considerable attention in recent years in the transportation surveillance domain for identifying unusual patterns, such as traffic jams, accidents, dangerous driving and other abnormal behaviors. In this paper, a novel approach for traffic behavior modeling is presented for video-based road surveillance. The proposed system combines the pachinko allocation model (PAM) and support vector machine (SVM) for a hierarchical representation and identification of traffic behavior. A background subtraction technique using Gaussian mixture models (GMMs) and an object tracking mechanism based on Kalman filters are utilized to firstly construct the object trajectories. Then, the sparse features comprising the locations and directions of the moving objects are modeled by PAMinto traffic topics, namely activities and behaviors. As a key innovation, PAM captures not only the correlation among the activities, but also among the behaviors based on the arbitrary directed acyclic graph (DAG). The SVM classifier is then utilized on top to train and recognize the traffic activity and behavior. The proposed model shows more flexibility and greater expressive power than the commonly-used latent Dirichlet allocation (LDA) approach, leading to a higher recognition accuracy in the behavior classification.

  10. Traffic Behavior Recognition Using the Pachinko Allocation Model

    Directory of Open Access Journals (Sweden)

    Thien Huynh-The

    2015-07-01

    Full Text Available CCTV-based behavior recognition systems have gained considerable attention in recent years in the transportation surveillance domain for identifying unusual patterns, such as traffic jams, accidents, dangerous driving and other abnormal behaviors. In this paper, a novel approach for traffic behavior modeling is presented for video-based road surveillance. The proposed system combines the pachinko allocation model (PAM and support vector machine (SVM for a hierarchical representation and identification of traffic behavior. A background subtraction technique using Gaussian mixture models (GMMs and an object tracking mechanism based on Kalman filters are utilized to firstly construct the object trajectories. Then, the sparse features comprising the locations and directions of the moving objects are modeled by PAMinto traffic topics, namely activities and behaviors. As a key innovation, PAM captures not only the correlation among the activities, but also among the behaviors based on the arbitrary directed acyclic graph (DAG. The SVM classifier is then utilized on top to train and recognize the traffic activity and behavior. The proposed model shows more flexibility and greater expressive power than the commonly-used latent Dirichlet allocation (LDA approach, leading to a higher recognition accuracy in the behavior classification.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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...

  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. 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.

  18. 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.

  19. System Behavior Models: A Survey of Approaches

    Science.gov (United States)

    2016-06-01

    the Petri model allowed a quick assessment of all potential states but was more cumbersome to build than the MP model. A comparison of approaches...identical state space results. The combined state space graph of the Petri model allowed a quick assessment of all potential states but was more...59 INITIAL DISTRIBUTION LIST ...................................................................................65 ix LIST

  20. 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...

  1. Behavioral Model of Photovoltaic Panel in Simulink

    Directory of Open Access Journals (Sweden)

    ZAPLATILEK, K.

    2011-11-01

    Full Text Available This article deals with creation and application of a model of photovoltaic panel in the MATLAB and Simulink environments. An original model of the real PV panel is applied using the model based design technique. A so-called physical model is also developed using the SimPowerSystems library. The described PV panel model is applied for maximum power optimization in the one-shot and the continuous modes. A few illustrating examples and source code parts are also presented.

  2. 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 ...

  3. 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

  4. How to model normative behavior in Petri nets

    NARCIS (Netherlands)

    J.-F. Raskin; Y-H. Tan (Yao-Hua); L.W.N. van der Torre

    1996-01-01

    textabstractIn this paper, we show how to extend the Petri net formalism to represent different types of behavior, in particular normative behavior. This extension is motivated by the use of Petri nets to model bureaucratic procedures, which contain normative aspects like obligations and

  5. Partner Influence in Diet and Exercise Behaviors: Testing Behavior Modeling, Social Control, and Normative Body Size

    Science.gov (United States)

    Ciciurkaite, Gabriele; Brady, Christy Freadreacea; Garcia, Justin

    2016-01-01

    Previous research has documented social contagion in obesity and related health behaviors, but less is known about the social processes underlying these patterns. Focusing on married or cohabitating couples, we simultaneously explore three potential social mechanisms influencing obesity: normative body size, social control, and behavior modeling. We analyze the association between partner characteristics and the obesity-related health behaviors of focal respondents, comparing the effects of partners’ body type, partners’ attempts to manage respondents’ eating behaviors, and partners’ own health behaviors on respondents’ health behaviors (physical activity, fruit and vegetable consumption, and fast food consumption). Data on 215 partners are extracted from a larger study of social mechanisms of obesity in family and community contexts conducted in 2011 in the United States. Negative binomial regression models indicate that partner behavior is significantly related to respondent behavior (p social control in this sample, though generalizations about the relevance of these processes may be inappropriate. These results underscore the importance of policies and interventions that target dyads and social groups, suggesting that adoption of exercise or diet modifications in one individual is likely to spread to others, creating a social environment characterized by mutual reinforcement of healthy behavior. PMID:28033428

  6. Exercise and older adults: changing behavior with the transtheoretical model.

    Science.gov (United States)

    Burbank, Patricia M; Reibe, Deborah; Padula, Cynthia A; Nigg, Claudio

    2002-01-01

    The loss of muscle strength, decreased flexibility and range of motion, and decreased sense of balance that frequently accompany aging contribute to falls and functional decline. Even in advanced old age, one can improve strength, decrease the risk of falls, improve cardiorespiratory fitness, and improve ability to live independently. The Transtheoretical Model (TTM) of behavior change is an internationally recognized model that holds much promise for health behavior changes of all types. This article outlines the effects of exercise on age-related changes in the musculoskeletal system and describes the TTM as a model useful to help older adults change their exercise behavior. Research studies are documented that support the effectiveness of the TTM in changing behavior. Application of the model is described with specific examples illustrated in two case studies.

  7. Puget Sound Recreational Shellfish Harvesting Survey - Model Intended Angler Behavior

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Collect and analyze survey data from recreational saltwater fishermen in Oregon and Washington. Model trip demand using stated frequency / contingent behavior data....

  8. Quantifying and Disaggregating Consumer Purchasing Behavior for Energy Systems Modeling

    Science.gov (United States)

    Consumer behaviors such as energy conservation, adoption of more efficient technologies, and fuel switching represent significant potential for greenhouse gas mitigation. Current efforts to model future energy outcomes have tended to use simplified economic assumptions ...

  9. A simple generative model of collective online behavior.

    Science.gov (United States)

    Gleeson, James P; Cellai, Davide; Onnela, Jukka-Pekka; Porter, Mason A; Reed-Tsochas, Felix

    2014-07-22

    Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates--even when using purely observational data without experimental design--that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior.

  10. Mathematical Models and the Experimental Analysis of Behavior

    Science.gov (United States)

    Mazur, James E.

    2006-01-01

    The use of mathematical models in the experimental analysis of behavior has increased over the years, and they offer several advantages. Mathematical models require theorists to be precise and unambiguous, often allowing comparisons of competing theories that sound similar when stated in words. Sometimes different mathematical models may make…

  11. 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...

  12. A MULTIPLE EQUATION MODEL OF HOUSEHOLD LOCATIONAL AND TRIPMAKING BEHAVIOR,

    Science.gov (United States)

    This Memorandum describes a multiple equation model of household locational and tripmaking behavior , to be used in RAND’s study of urban...workers were aggregated to 254 spatially separate workplace zones. The model explains four types of locational and tripmaking behavior for the white...workers employed in these 254 zones: residential space consumption , automobile ownership, modal choice, and length of journey-to-work. In all, the final

  13. 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 ...

  14. Engineering Student's Ethical Awareness and Behavior: A New Motivational Model.

    Science.gov (United States)

    Bairaktarova, Diana; Woodcock, Anna

    2017-08-01

    Professional communities are experiencing scandals involving unethical and illegal practices daily. Yet it should not take a national major structure failure to highlight the importance of ethical awareness and behavior, or the need for the development and practice of ethical behavior in engineering students. Development of ethical behavior skills in future engineers is a key competency for engineering schools as ethical behavior is a part of the professional identity and practice of engineers. While engineering educators have somewhat established instructional methods to teach engineering ethics, they still rely heavily on teaching ethical awareness, and pay little attention to how well ethical awareness predicts ethical behavior. However the ability to exercise ethical judgement does not mean that students are ethically educated or likely to behave in an ethical manner. This paper argues measuring ethical judgment is insufficient for evaluating the teaching of engineering ethics, because ethical awareness has not been demonstrated to translate into ethical behavior. The focus of this paper is to propose a model that correlates with both, ethical awareness and ethical behavior. This model integrates the theory of planned behavior, person and thing orientation, and spheres of control. Applying this model will allow educators to build confidence and trust in their students' ability to build a professional identity and be prepared for the engineering profession and practice.

  15. Towards a characterization of behavior-disease models.

    Directory of Open Access Journals (Sweden)

    Nicola Perra

    Full Text Available The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself. While models lacking this coupling can be extremely successful in mild epidemics, they obviously will be of limited use in situations where social disruption or behavioral alterations are induced in the population by knowledge of the disease. Here we propose a characterization of a set of prototypical mechanisms for self-initiated social distancing induced by local and non-local prevalence-based information available to individuals in the population. We characterize the effects of these mechanisms in the framework of a compartmental scheme that enlarges the basic SIR model by considering separate behavioral classes within the population. The transition of individuals in/out of behavioral classes is coupled with the spreading of the disease and provides a rich phase space with multiple epidemic peaks and tipping points. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.

  16. A Language for Modeling Cultural Norms, Biases and Stereotypes for Human Behavior Models

    National Research Council Canada - National Science Library

    Solomon, Steven; van Lent, Michael; Core, Mark; Carpenter, Paul; Rosenberg, Milton

    2008-01-01

    .... The Culturally-Affected Behavior project seeks to define a language for encoding ethnographic data in order to capture cultural knowledge and use that knowledge to affect human behavior models...

  17. Modeling a Consistent Behavior of PLC-Sensors

    Directory of Open Access Journals (Sweden)

    E. V. Kuzmin

    2014-01-01

    Full Text Available The article extends the cycle of papers dedicated to programming and verificatoin of PLC-programs by LTL-specification. This approach provides the availability of correctness analysis of PLC-programs by the model checking method.The model checking method needs to construct a finite model of a PLC program. For successful verification of required properties it is important to take into consideration that not all combinations of input signals from the sensors can occur while PLC works with a control object. This fact requires more advertence to the construction of the PLC-program model.In this paper we propose to describe a consistent behavior of sensors by three groups of LTL-formulas. They will affect the program model, approximating it to the actual behavior of the PLC program. The idea of LTL-requirements is shown by an example.A PLC program is a description of reactions on input signals from sensors, switches and buttons. In constructing a PLC-program model, the approach to modeling a consistent behavior of PLC sensors allows to focus on modeling precisely these reactions without an extension of the program model by additional structures for realization of a realistic behavior of sensors. The consistent behavior of sensors is taken into account only at the stage of checking a conformity of the programming model to required properties, i. e. a property satisfaction proof for the constructed model occurs with the condition that the model contains only such executions of the program that comply with the consistent behavior of sensors.

  18. The KdV-Burgers equation in a new continuum model with consideration of driverʼs forecast effect and numerical tests

    Science.gov (United States)

    Ge, Hong-Xia; Lai, Ling-Ling; Zheng, Peng-Jun; Cheng, Rong-Jun

    2013-12-01

    A new continuum traffic flow model is proposed based on an improved car-following model, which takes the driver's forecast effect into consideration. The backward travel problem is overcome by our model and the neutral stability condition of the new model is obtained through the linear stability analysis. Nonlinear analysis shows clearly that the density fluctuation in traffic flow leads to a variety of density waves and the Korteweg-de Vries-Burgers (KdV-Burgers) equation is derived to describe the traffic flow near the neutral stability line. The corresponding solution for traffic density wave is also derived. Finally, the numerical results show that our model can not only reproduce the evolution of small perturbation, but also improve the stability of traffic flow.

  19. The gravity model of labor migration behavior

    Science.gov (United States)

    Alexandr, Tarasyev; Alexandr, Tarasyev

    2017-07-01

    In this article, we present a dynamic inter-regional model, that is based on the gravity approach to migration and describes in continuous time the labor force dynamics between a number of conjugate regions. Our modification of the gravity migration model allows to explain the migration processes and to display the impact of migration on the regional economic development both for regions of origin and attraction. The application of our model allows to trace the dependency between salaries levels, total workforce, the number of vacancies and the number unemployed people in simulated regions. Due to the gravity component in our model the accuracy of prediction for migration flows is limited by the distance range between analyzed regions, so this model is tested on a number of conjugate neighbor regions. Future studies will be aimed at development of a multi-level dynamic model, which allows to construct a forecast for unemployment and vacancies trends on the first modeling level and to use these identified parameters on the second level for describing dynamic trajectories of migration flows.

  20. Multivariable modeling and multivariate analysis for the behavioral sciences

    CERN Document Server

    Everitt, Brian S

    2009-01-01

    Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences shows students how to apply statistical methods to behavioral science data in a sensible manner. Assuming some familiarity with introductory statistics, the book analyzes a host of real-world data to provide useful answers to real-life issues.The author begins by exploring the types and design of behavioral studies. He also explains how models are used in the analysis of data. After describing graphical methods, such as scatterplot matrices, the text covers simple linear regression, locally weighted regression, multip

  1. Modeling and simulating human teamwork behaviors using intelligent agents

    Science.gov (United States)

    Fan, Xiaocong; Yen, John

    2004-12-01

    Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

  2. Fractional Lorentz-Dirac Model and Its Dynamical Behaviors

    Science.gov (United States)

    Luo, Shao-Kai; Xu, Yan-Li

    2015-02-01

    In the paper, we construct a new kind of fractional dynamical model, i.e. the fractional Lorentz-Dirac model, and explore dynamical behaviors of the model. We find that the fractional Lorentz-Dirac model possesses Lie algebraic structure and satisfies generalized Poisson conservation law, and then a series of Poisson conserved quantities of the model are given. Further, the relation between conserved quantity and integral invariant of the model is studied, and it is proved that, using the Poisson conserved quantities, we can construct a series of integral invariants of the model. Finally, the stability for the manifolds of equilibrium state of the fractional Lorentz-Dirac model is studied.

  3. An Integrated Approach to Modeling Evacuation Behavior

    Science.gov (United States)

    2011-02-01

    A spate of recent hurricanes and other natural disasters have drawn a lot of attention to the evacuation decision of individuals. Here we focus on evacuation models that incorporate two economic phenomena that seem to be increasingly important in exp...

  4. Formal modeling of robot behavior with learning.

    Science.gov (United States)

    Kirwan, Ryan; Miller, Alice; Porr, Bernd; Di Prodi, P

    2013-11-01

    We present formal specification and verification of a robot moving in a complex network, using temporal sequence learning to avoid obstacles. Our aim is to demonstrate the benefit of using a formal approach to analyze such a system as a complementary approach to simulation. We first describe a classical closed-loop simulation of the system and compare this approach to one in which the system is analyzed using formal verification. We show that the formal verification has some advantages over classical simulation and finds deficiencies our classical simulation did not identify. Specifically we present a formal specification of the system, defined in the Promela modeling language and show how the associated model is verified using the Spin model checker. We then introduce an abstract model that is suitable for verifying the same properties for any environment with obstacles under a given set of assumptions. We outline how we can prove that our abstraction is sound: any property that holds for the abstracted model will hold in the original (unabstracted) model.

  5. Expression profiling of in vivo ductal carcinoma in situ progression models identified B cell lymphoma-9 as a molecular driver of breast cancer invasion

    OpenAIRE

    Elsarraj, Hanan S.; Hong, Yan; Valdez, Kelli E.; Michaels, Whitney; Hook, Marcus; Smith, William P.; Chien, Jeremy; Herschkowitz, Jason I.; Troester, Melissa A.; Beck, Moriah; Inciardi, Marc; Gatewood, Jason; May, Lisa; Cusick, Therese; McGinness, Marilee

    2015-01-01

    Introduction: There are an estimated 60,000 new cases of ductal carcinoma in situ (DCIS) each year. A lack of understanding in DCIS pathobiology has led to overtreatment of more than half of patients. We profiled the temporal molecular changes during DCIS transition to invasive ductal carcinoma (IDC) using in vivo DCIS progression models. These studies identified B cell lymphoma-9 (BCL9) as a potential molecular driver of early invasion. BCL9 is a newly found co-activator of Wnt-stimulated β-...

  6. Drivers of Change in Managed Water Resources: Modeling the Impacts of Climate and Socioeconomic Changes Using the US Midwest as a Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Voisin, Nathalie; Leung, Lai-Yung R.; Hejazi, Mohamad I.

    2016-08-01

    A global integrated assessment model including a water-demand model driven by socio-economics, is coupled in a one-way fashion with a land surface hydrology – routing – water resources management model. The integrated modeling framework is applied to the U.S. Upper Midwest (Missouri, Upper Mississippi, and Ohio) to advance understanding of the regional impacts of climate and socio-economic changes on integrated water resources. Implications for future flow regulation, water supply, and supply deficit are investigated using climate change projections with the B1 and A2 emission scenarios, which affect both natural flow and water demand. Changes in water demand are driven by socio-economic factors, energy and food demands, global markets and prices. The framework identifies the multiple spatial scales of interactions between the drivers of changes (natural flow and water demand) and the managed water resources (regulated flow, supply and supply deficit). The contribution of the different drivers of change are quantified regionally, and also evaluated locally, using covariances. The integrated framework shows that water supply deficit is more predictable over the Missouri than the other regions in the Midwest. The predictability of the supply deficit mostly comes from long term changes in water demand although changes in runoff has a greater contribution, comparable to the contribution of changes in demand, over shorter time periods. The integrated framework also shows that spatially, water demand drives local supply deficit. Using elasticity, the sensitivity of supply deficit to drivers of change is established. The supply deficit is found to be more sensitive to changes in runoff than to changes in demand regionally. It contrasts with the covariance analysis that shows that water demand is the dominant driver of supply deficit over the analysed periods. The elasticity indicates the level of mitigation needed to control the demand in order to reduce the

  7. Biosocial models of adolescent problem behavior: extension to panel design.

    Science.gov (United States)

    Drigotas, S M; Udry, J R

    1993-01-01

    We extended the biosocial model of problem behavior tested by Udry (1990) to a panel design, following a sample of over one hundred boys in adolescence for three years. We found the expected results for sociological variables, but weaker effects for testosterone than Udry found on cross-sectional data. Using panel models with lagged hormone effects, we identified relationships between Time-1 testosterone and problem behavior one year or more later. The relationship between testosterone and problem behavior was not present for subsequent measures of testosterone, either in cross-section or with time-lagged models. Therefore we cannot interpret the results as showing testosterone effects on problem behavior. Rather it appears that testosterone level in early adolescence is a marker for a more general growth trajectory of early development.

  8. Modeling synchronized calling behavior of Japanese tree frogs.

    Science.gov (United States)

    Aihara, Ikkyu

    2009-07-01

    We experimentally observed synchronized calling behavior of male Japanese tree frogs Hyla japonica; namely, while isolated single frogs called nearly periodically, a pair of interacting frogs called synchronously almost in antiphase or inphase. In this study, we propose two types of phase-oscillator models on different degrees of approximations, which can quantitatively explain the phase and frequency properties in the experiment. Moreover, it should be noted that, although the second model is obtained by fitting to the experimental data of the two synchronized states, the model can also explain the transitory dynamics in the interactive calling behavior, namely, the shift from a transient inphase state to a stable antiphase state. We also discuss the biological relevance of the estimated parameter values to calling behavior of Japanese tree frogs and the possible biological meanings of the synchronized calling behavior.

  9. Micromechanical modeling of rate-dependent behavior of Connective tissues.

    Science.gov (United States)

    Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

    2017-03-07

    In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Relevance of behavioral and social models to the study of consumer energy decision making and behavior

    Energy Technology Data Exchange (ETDEWEB)

    Burns, B.A.

    1980-11-01

    This report reviews social and behavioral science models and techniques for their possible use in understanding and predicting consumer energy decision making and behaviors. A number of models and techniques have been developed that address different aspects of the decision process, use different theoretical bases and approaches, and have been aimed at different audiences. Three major areas of discussion were selected: (1) models of adaptation to social change, (2) decision making and choice, and (3) diffusion of innovation. Within these three areas, the contributions of psychologists, sociologists, economists, marketing researchers, and others were reviewed. Five primary components of the models were identified and compared. The components are: (1) situational characteristics, (2) product characteristics, (3) individual characteristics, (4) social influences, and (5) the interaction or decision rules. The explicit use of behavioral and social science models in energy decision-making and behavior studies has been limited. Examples are given of a small number of energy studies which applied and tested existing models in studying the adoption of energy conservation behaviors and technologies, and solar technology.

  11. Swimming behavior of zebrafish is accurately classified by direct modeling and behavioral space analysis

    Science.gov (United States)

    Feng, Ruopei; Chemla, Yann; Gruebele, Martin

    Larval zebrafish is a popular organism in the search for the correlation between locomotion behavior and neural pathways because of their highly stereotyped and temporally episodic swimming motion. This correlation is usually investigated using electrophysiological recordings of neural activities in partially immobilized fish. Seeking for a way to study animal behavior without constraints or intruding electrodes, which can in turn modify their behavior, our lab has introduced a parameter-free approach which allows automated classification of the locomotion behaviors of freely swimming fish. We looked into several types of swimming bouts including free swimming and two modes of escape responses and established a new classification of these behaviors. Combined with a neurokinematic model, our analysis showed the capability to probe intrinsic properties of the underlying neural pathways of freely swimming larval zebrafish by inspecting swimming movies only.

  12. Slow conduction in the border zones of patchy fibrosis stabilises the drivers for atrial fibrillation: Insights from multi-scale human atrial modelling

    Directory of Open Access Journals (Sweden)

    Ross Morgan

    2016-10-01

    Full Text Available Introduction. The genesis of atrial fibrillation (AF and success of AF ablation therapy have been strongly linked with atrial fibrosis. Increasing evidence suggests that patient-specific distributions of fibrosis may determine the locations of electrical drivers (rotors sustaining AF, but the underlying mechanisms are incompletely understood. This study aims to elucidate a missing mechanistic link between patient-specific fibrosis distributions and AF drivers. Methods. 3D atrial models integrated human atrial geometry, rule-based fibre orientation, region-specific electrophysiology and AF-induced ionic remodelling. A novel detailed model for an atrial fibroblast was developed, and effects of myocyte-fibroblast (M-F coupling were explored at single-cell, 1D tissue and 3D atria levels. Left atrial LGE MRI datasets from 3 chronic AF patients were segmented to provide the patient-specific distributions of fibrosis. The data was non-linearly registered and mapped to the 3D atria model. Six distinctive fibrosis levels (0 – healthy tissue, 5 – dense fibrosis were identified based on LGE MRI intensity and modelled as progressively increasing M-F coupling and decreasing atrial tissue coupling. Uniform 3D atrial model with diffuse (level 2 fibrosis was considered for comparison.Results. In single cells and tissue, the largest effect of atrial M-F coupling was on the myocyte resting membrane potential, leading to partial inactivation of sodium current and reduction of conduction velocity (CV. In the 3D atria, further to the M-F coupling, effects of fibrosis on tissue coupling greatly reduce atrial CV. AF was initiated by fast pacing in each 3D model with either uniform or patient-specific fibrosis. High variation in fibrosis distributions between the models resulted in varying complexity of AF, with several drivers emerging. In the diffuse fibrosis models, waves randomly meandered through the atria, whereas in each the patient-specific models, rotors

  13. Study the epidemiological profile of taxi drivers in the background of occupational environment, stress and personality characteristics

    Science.gov (United States)

    Bawa, Mukesh Suresh; Srivastav, Manissha

    2013-01-01

    Background: Work hazards have been a major cause of concern in driving industry especially in taxi drivers. This study integrates the various factors that influence physical and emotional well-being of taxi drivers into the theoretical model that shows that the work environment, stress and personality characteristics directly influence taxi drivers’ health. Objective: The aim of the following study is to study the relative and combined influence of work environment, personality characteristics and stress on the health of taxi drivers. Meterials and Methods: The present study is cross-sectional (descriptive) study taxi drivers in Mumbai. They are selected using multistage random sampling method. Calculated sample size is 508. Data produced after the survey is analyzed using IBM SPSS 16.0 software. Results: Nearly 65% of taxi drivers belonged to middle-age group of 21-40 years of age. Majority (59%) of taxi drivers belonged to the lower upper socio-economic class. 70% of taxi drivers worked for more than 8 h daily. 63% gave the history of one or more addictions. 52% taxi drivers had type B1 personality, only 6% had stress prone and aggressive type A1 personality. Traffic congestion (67.1%) was reported as the leading stressor followed by narrow bottle neck roads (43%), too many speed breakers (41%), rude gestures and behavior by other drivers (42%) and bad weather (36%). Nearly 86% taxi drivers had one or more symptoms of morbidities. Gastrointestinal symptoms predominated followed by musculoskeletal symptoms and depression. Conclusion: Socio-demographic attributes, work environment, stress and personality significantly influence physical and psychological morbidities in taxi drivers. PMID:24872669

  14. Modelling hydrological changes in surface in relation with anthropogenic drivers and consequences on human health and local economic

    Science.gov (United States)

    Sandoz, Alain; Leblond, Agnès; Boutron, Olivier

    2016-04-01

    of the watershed. The modeling also performed to simulate a change in rainfall locally to measure hydrological and environmental consequences. According to these scenarios, it was possible to map the potential areas of mosquitoes breeding sites (presence / absence of mosquitoes) and their impact on urban populations in terms of health risks and nuisance. This territory represents many interests for decision-makers interested in issues of governance and renaturation. To improve the inclusion of better water governance and territories, as well as facilitate dynamic annealing, it might be necessary to help decision-makers having a better knowledge of the impact of human drivers on water management on the territory. This increased knowledge would also enable local decision-makers to improve their awareness of the heritage and biodiversity of wetlands. This project was funded by the French Ministry of Ecology, Sustainable Development and Energy as part of the projects Water and Territories.

  15. Determinants and Drivers of Infectious Disease Threat Events in Europe.

    Science.gov (United States)

    Semenza, Jan C; Lindgren, Elisabet; Balkanyi, Laszlo; Espinosa, Laura; Almqvist, My S; Penttinen, Pasi; Rocklöv, Joacim

    2016-04-01

    Infectious disease threat events (IDTEs) are increasing in frequency worldwide. We analyzed underlying drivers of 116 IDTEs detected in Europe during 2008-2013 by epidemic intelligence at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorized into 3 groups: globalization and environment, sociodemographic, and public health systems. A combination of >2 drivers was responsible for most IDTEs. The driver category globalization and environment contributed to 61% of individual IDTEs, and the top 5 individual drivers of all IDTEs were travel and tourism, food and water quality, natural environment, global trade, and climate. Hierarchical cluster analysis of all drivers identified travel and tourism as a distinctly separate driver. Monitoring and modeling such disease drivers can help anticipate future IDTEs and strengthen control measures. More important, intervening directly on these underlying drivers can diminish the likelihood of the occurrence of an IDTE and reduce the associated human and economic costs.

  16. A compositional method to model dependent failure behavior based on PoF models

    Directory of Open Access Journals (Sweden)

    Zhiguo ZENG

    2017-10-01

    Full Text Available In this paper, a new method is developed to model dependent failure behavior among failure mechanisms. Unlike the existing methods, the developed method models the root cause of the dependency explicitly, so that a deterministic model, rather than a probabilistic one, can be established. Three steps comprise the developed method. First, physics-of-failure (PoF models are utilized to model each failure mechanism. Then, interactions among failure mechanisms are modeled as a combination of three basic relations, competition, superposition and coupling. This is the reason why the method is referred to as “compositional method”. Finally, the PoF models and the interaction model are combined to develop a deterministic model of the dependent failure behavior. As a demonstration, the method is applied on an actual spool and the developed failure behavior model is validated by a wear test. The result demonstrates that the compositional method is an effective way to model dependent failure behavior.

  17. Etiological model of disordered eating behaviors in Brazilian adolescent girls.

    Science.gov (United States)

    Fortes, Leonardo de Sousa; Filgueiras, Juliana Fernandes; Oliveira, Fernanda da Costa; Almeida, Sebastião Sousa; Ferreira, Maria Elisa Caputo

    2016-01-01

    The objective was to construct an etiological model of disordered eating behaviors in Brazilian adolescent girls. A total of 1,358 adolescent girls from four cities participated. The study used psychometric scales to assess disordered eating behaviors, body dissatisfaction, media pressure, self-esteem, mood, depressive symptoms, and perfectionism. Weight, height, and skinfolds were measured to calculate body mass index (BMI) and percent body fat (%F). Structural equation modeling explained 76% of variance in disordered eating behaviors (F(9, 1,351) = 74.50; p = 0.001). The findings indicate that body dissatisfaction mediated the relationship between media pressures, self-esteem, mood, BMI, %F, and disordered eating behaviors (F(9, 1,351) = 59.89; p = 0.001). Although depressive symptoms were not related to body dissatisfaction, the model indicated a direct relationship with disordered eating behaviors (F(2, 1,356) = 23.98; p = 0.001). In conclusion, only perfectionism failed to fit the etiological model of disordered eating behaviors in Brazilian adolescent girls.

  18. Risk factors affecting fatal bus accident severity: Their impact on different types of bus drivers.

    Science.gov (United States)

    Feng, Shumin; Li, Zhenning; Ci, Yusheng; Zhang, Guohui

    2016-01-01

    While the bus is generally considered to be a relatively safe means of transportation, the property losses and casualties caused by bus accidents, especially fatal ones, are far from negligible. The reasons for a driver to incur fatalities are different in each case, and it is essential to discover the underlying risk factors of bus fatality severity for different types of drivers in order to improve bus safety. The current study investigates the underlying risk factors of fatal bus accident severity to different types of drivers in the U.S. by estimating an ordered logistic model. Data for the analysis are retrieved from the Buses Involved in Fatal Accidents (BIFA) database from the USA for the years 2006-2010. Accidents are divided into three levels by counting their equivalent fatalities, and the drivers are classified into three clusters by the K-means cluster analysis. The analysis shows that some risk factors have the same impact on different types of drivers, they are: (a) season; (b) day of week; (c) time period; (d) number of vehicles involved; (e) land use; (f) manner of collision; (g) speed limit; (h) snow or ice surface condition; (i) school bus; (j) bus type and seating capacity; (k) driver's age; (l) driver's gender; (m) risky behaviors; and (n) restraint system. Results also show that some risk factors only have impact on the "young and elder drivers with history of traffic violations", they are: (a) section type; (b) number of lanes per direction; (c) roadway profile; (d) wet road surface; and (e) cyclist-bus accident. Notably, history of traffic violations has different impact on different types of bus drivers. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Impact Of ATIS On Drivers' Decisions And Route Choice: A Literature Review

    OpenAIRE

    Abedel-aty, Mohamed A.; Vaughn, Kenneth M.; Kitamura, Ryuichi; Jovanis, Paul P.

    1993-01-01

    This report reviews the recent studies adopted in order to understand drivers' behavior, and in particular, behavior when influenced by an Advanced Traveler Information System (ATIS). Different approaches were used in these studies: field experiments, route choice surveys, interactive computer simulation games, route choice simulation and/or modeling, and stated preference. These studies are classified according to the main approach used, and the main objective, method, and findings are prese...

  20. Key drivers of airline loyalty

    Science.gov (United States)

    Dolnicar, Sara; Grabler, Klaus; Grün, Bettina; Kulnig, Anna

    2011-01-01

    This study investigates drivers of airline loyalty. It contributes to the body of knowledge in the area by investigating loyalty for a number of a priori market segments identified by airline management and by using a method which accounts for the multi-step nature of the airline choice process. The study is based on responses from 687 passengers. Results indicate that, at aggregate level, frequent flyer membership, price, the status of being a national carrier and the reputation of the airline as perceived by friends are the variables which best discriminate between travellers loyal to the airline and those who are not. Differences in drivers of airline loyalty for a number of segments were identified. For example, loyalty programs play a key role for business travellers whereas airline loyalty of leisure travellers is difficult to trace back to single factors. For none of the calculated models satisfaction emerged as a key driver of airline loyalty. PMID:27064618

  1. Complex Behavior in Simple Models of Biological Coevolution

    Science.gov (United States)

    Rikvold, Per Arne

    We explore the complex dynamical behavior of simple predator-prey models of biological coevolution that account for interspecific and intraspecific competition for resources, as well as adaptive foraging behavior. In long kinetic Monte Carlo simulations of these models we find quite robust 1/f-like noise in species diversity and population sizes, as well as power-law distributions for the lifetimes of individual species and the durations of quiet periods of relative evolutionary stasis. In one model, based on the Holling Type II functional response, adaptive foraging produces a metastable low-diversity phase and a stable high-diversity phase.

  2. Longitudinal models in the behavioral and related sciences

    NARCIS (Netherlands)

    Montfort, van K.; Satorra, A.; Oud, H.

    2007-01-01

    Longitudinal Models in the Behavioral and Related Sciences opens with the latest theoretical developments. In particular, the book addresses situations that arise due to the categorical nature of the data, issues related to state space modeling, and potential problems that may arise from network

  3. The Ram as a Model for Behavioral Neuroendocrinology

    Science.gov (United States)

    Perkins, Anne; Roselli, Charles E.

    2007-01-01

    The sheep offers a unique model to study male sexual behavior and sexual partner preference. Rams are seasonal breeders and show the greatest libido during short days coincident with the resumption of ovarian cyclicity in the ewe. Threshold concentrations of testosterone are required for the acquisition and display of adult sexual behavior. In addition, estrogens produced from circulating testosterone by cytochrome P450 aromatase in the preoptic area are critical for the maintenance of sexual behaviors in rams. Sex differences in adult reproductive behaviors and hormone responsiveness are the result of permanent organizational effects exerted by testosterone and its metabolites on brain development. Early exposure to ewes enhances ram sexual performance, but cannot prevent some rams from exhibiting male-oriented sexual partner preferences. Neurochemical and neuroanatomical studies suggest that male-oriented ram behavior may be a consequence of individual variations in brain sexual differentiation. PMID:17482616

  4. Gambling and the Reasoned Action Model: Predicting Past Behavior, Intentions, and Future Behavior.

    Science.gov (United States)

    Dahl, Ethan; Tagler, Michael J; Hohman, Zachary P

    2018-03-01

    Gambling is a serious concern for society because it is highly addictive and is associated with a myriad of negative outcomes. The current study applied the Reasoned Action Model (RAM) to understand and predict gambling intentions and behavior. Although prior studies have taken a reasoned action approach to understand gambling, no prior study has fully applied the RAM or used the RAM to predict future gambling. Across two studies the RAM was used to predict intentions to gamble, past gambling behavior, and future gambling behavior. In study 1 the model significantly predicted intentions and past behavior in both a college student and Amazon Mechanical Turk sample. In study 2 the model predicted future gambling behavior, measured 2 weeks after initial measurement of the RAM constructs. This study stands as the first to show the utility of the RAM in predicting future gambling behavior. Across both studies, attitudes and perceived normative pressure were the strongest predictors of intentions to gamble. These findings provide increased understanding of gambling and inform the development of gambling interventions based on the RAM.

  5. Technology and teen drivers.

    Science.gov (United States)

    Lee, John D

    2007-01-01

    The rapid evolution of computing, communication, and sensor technology is likely to affect young drivers more than others. The distraction potential of infotainment technology stresses the same vulnerabilities that already lead young drivers to crash more frequently than other drivers. Cell phones, text messaging, MP3 players, and other nomadic devices all present a threat because young drivers may lack the spare attentional capacity for vehicle control and the ability to anticipate and manage hazards. Moreover, young drivers are likely to be the first and most aggressive users of new technology. Fortunately, emerging technology can also support safe driving. Electronic stability control, collision avoidance systems, intelligent speed adaptation, and vehicle tracking systems can all help mitigate the threats to young drivers. However, technology alone is unlikely to make young drivers safer. One promising approach to tailoring technology to teen drivers is to extend proven methods for enhancing young driver safety. The success of graduated drivers license programs (GDL) and the impressive safety benefit of supervised driving suggest ways of tailoring technology to the needs of young drivers. To anticipate the effects of technology on teen driving it may be useful to draw an analogy between the effects of passengers and the effects of technology. Technology can act as a teen passenger and undermine safety or it can act as an adult passenger and enhance safety. Rapidly developing technology may have particularly large effects on teen drivers. To maximize the positive effects and minimize the negative effects will require a broad range of industries to work together. Ideally, vehicle manufacturers would work with infotainment providers, insurance companies, and policy makers to craft new technologies so that they accommodate the needs of young drivers. Without such collaboration young drivers will face even greater challenges to their safety as new technologies emerge.

  6. Modelling the behavior of an oil saturated sand

    International Nuclear Information System (INIS)

    Evgin, E.; Altaee, A.; Lord, S.; Konuk, I.

    1990-01-01

    The experiments carried out in an earlier study show the oil contamination affects the strength and deformation characteristics of a crushed quartz sand. In the present study, a mathematical soil model is used to simulate the mechanical behavior of the same sand. The model parameters are determined for both clean and oil contaminated soil. Simulations are made for the stress-strain behavior of the soil in drained and undrained conventional traixial compression tests. In order to illustrate the effect of changes in the soil properties on the behavior of an engineering structure, a finite element analysis is carried out. In this paper comparative results are presented to show the differences in the behavior of a foundation resting on a clean sand, on an oil contaminated sand, and on a sand contaminated locally

  7. Incorporation of the Driver’s Personality Profile in an Agent Model

    Directory of Open Access Journals (Sweden)

    Mian Muhammad Mubasher

    2015-12-01

    Full Text Available Urban traffic flow is a complex system. Behavior of an individual driver can have butterfly effect which can become root cause of an emergent phenomenon such as congestion or accident. Interaction of drivers with each other and the surrounding environment forms the dynamics of traffic flow. Hence global effects of traffic flow depend upon the behavior of each individual driver. Due to several applications of driver models in serious games, urban traffic planning and simulations, study of a realistic driver model is important. Hhence cognitive models of a driver agent are required. In order to address this challenge concepts from cognitive science and psychology are employed to design a computational model of driver cognition which is capable of incorporating law abidance and social norms using big five personality profile.

  8. What drives technology-based distractions? A structural equation model on social-psychological factors of technology-based driver distraction engagement.

    Science.gov (United States)

    Chen, Huei-Yen Winnie; Donmez, Birsen

    2016-06-01

    With the proliferation of new mobile and in-vehicle technologies, understanding the motivations behind a driver's voluntary engagement with such technologies is crucial from a safety perspective, yet is complex. Previous literature either surveyed a large number of distractions that may be diverse, or too focuses on one particular activity, such as cell phone use. Further, earlier studies about social-psychological factors underlying driver distraction tend to focus on one or two factors in-depth, and those that examine a more comprehensive set of factors are often limited in their analyses methods. The present work considers a wide array of social-psychological factors within a structural equation model to predict their influence on a focused set of technology-based distractions. A better understanding of these facilitators can enhance the design of distraction mitigation strategies. We analysed survey responses about three technology-based driver distractions: holding phone conversations, manually interacting with cell phones, and adjusting the settings of in-vehicle technology, as well as responses on five social-psychological factors: attitude, descriptive norm, injunctive norm, technology inclination, and a risk/sensation seeking personality. Using data collected from 525 drivers (ages: 18-80), a structural equation model was built to analyse these social-psychological factors as latent variables influencing self-reported engagement in these three technology-based distractions. Self-reported engagement in technology-based distractions was found to be largely influenced by attitudes about the distractions. Personality and social norms also played a significant role, but technology inclination did not. A closer look at two age groups (18-30 and 30+) showed that the effect of social norms, especially of injunctive norm (i.e., perceived approvals), was less prominent in the 30+ age group, while personality remained a significant predictor for the 30+ age group but

  9. Head Motion Modeling for Human Behavior Analysis in Dyadic Interaction.

    Science.gov (United States)

    Xiao, Bo; Georgiou, Panayiotis; Baucom, Brian; Narayanan, Shrikanth S

    2015-07-13

    This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors' behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however, are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics, we propose a data driven approach to identify typical head motion patterns. The approach follows the steps of first segmenting motion events, then parametrically representing the motion by linear predictive features, and finally generalizing the motion types using Gaussian mixture models. The proposed approach is experimentally validated using video recordings of communication sessions from real couples involved in a couples therapy study. In particular we use the head motion model to classify binarized expert judgments of the interactants' specific behavioral characteristics where entrainment in head motion is hypothesized to play a role: Acceptance, Blame, Positive , and Negative behavior. We achieve accuracies in the range of 60% to 70% for the various experimental settings and conditions. In addition, we describe a measure of motion similarity between the interaction partners based on the proposed model. We show that the relative change of head motion similarity during the interaction significantly correlates with the expert judgments of the interactants' behavioral characteristics. These findings demonstrate the effectiveness of the proposed head motion model, and underscore the promise of analyzing human behavioral characteristics through signal processing methods.

  10. Safety evaluation of driver cognitive failures and driving errors on right-turn filtering movement at signalized road intersections based on Fuzzy Cellular Automata (FCA) model.

    Science.gov (United States)

    Chai, Chen; Wong, Yiik Diew; Wang, Xuesong

    2017-07-01

    This paper proposes a simulation-based approach to estimate safety impact of driver cognitive failures and driving errors. Fuzzy Logic, which involves linguistic terms and uncertainty, is incorporated with Cellular Automata model to simulate decision-making process of right-turn filtering movement at signalized intersections. Simulation experiments are conducted to estimate the relationships between cognitive failures and driving errors with safety performance. Simulation results show Different types of cognitive failures are found to have varied relationship with driving errors and safety performance. For right-turn filtering movement, cognitive failures are more likely to result in driving errors with denser conflicting traffic stream. Moreover, different driving errors are found to have different safety impacts. The study serves to provide a novel approach to linguistically assess cognitions and replicate decision-making procedures of the individual driver. Compare to crash analysis, the proposed FCA model allows quantitative estimation of particular cognitive failures, and the impact of cognitions on driving errors and safety performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Quantitative understanding of Forbush decrease drivers based on shock-only and CME-only models using global signature of February 14, 1978 event

    International Nuclear Information System (INIS)

    Raghav, Anil; Lotekar, Ajay; Bhaskar, Ankush; Vichare, Geeta; Yadav, Virendra

    2014-01-01

    We have studied the Forbush decrease (FD) event that occurred on February 14, 1978 using 43 neutron monitor observatories to understand the global signature of FD. We have studied rigidity dependence of shock amplitude and total FD amplitude. We have found almost the same power law index for both shock phase amplitude and total FD amplitude. Local time variation of shock phase amplitude and maximum depression time of FD have been investigated which indicate possible effect of shock/CME orientation. We have analyzed rigidity dependence of time constants of two phase recovery. Time constants of slow component of recovery phase show rigidity dependence and imply possible effect of diffusion. Solar wind speed was observed to be well correlated with slow component of FD recovery phase. This indicates solar wind speed as possible driver of recovery phase. To investigate the contribution of interplanetary drivers, shock and CME in FD, we have used shock-only and CME-only models. We have applied these models separately to shock phase and main phase amplitudes respectively. This confirms presently accepted physical scenario that the first step of FD is due to propagating shock barrier and second step is due to flux rope of CME/magnetic cloud

  12. Applying the Health Belief Model to college students' health behavior

    Science.gov (United States)

    Kim, Hak-Seon; Ahn, Joo

    2012-01-01

    The purpose of this research was to investigate how university students' nutrition beliefs influence their health behavioral intention. This study used an online survey engine (Qulatrics.com) to collect data from college students. Out of 253 questionnaires collected, 251 questionnaires (99.2%) were used for the statistical analysis. Confirmatory Factor Analysis (CFA) revealed that six dimensions, "Nutrition Confidence," "Susceptibility," "Severity," "Barrier," "Benefit," "Behavioral Intention to Eat Healthy Food," and "Behavioral Intention to do Physical Activity," had construct validity; Cronbach's alpha coefficient and composite reliabilities were tested for item reliability. The results validate that objective nutrition knowledge was a good predictor of college students' nutrition confidence. The results also clearly showed that two direct measures were significant predictors of behavioral intentions as hypothesized. Perceived benefit of eating healthy food and perceived barrier for eat healthy food to had significant effects on Behavioral Intentions and was a valid measurement to use to determine Behavioral Intentions. These findings can enhance the extant literature on the universal applicability of the model and serve as useful references for further investigations of the validity of the model within other health care or foodservice settings and for other health behavioral categories. PMID:23346306

  13. How to model normative behavior in Petri nets

    OpenAIRE

    Raskin, J.-F.; Tan, Yao-Hua; Torre, L.W.N.

    1996-01-01

    textabstractIn this paper, we show how to extend the Petri net formalism to represent different types of behavior, in particular normative behavior. This extension is motivated by the use of Petri nets to model bureaucratic procedures, which contain normative aspects like obligations and permissions. We propose to extend Petri nets with a preference relation, a well-known mechanism from deontic logic to discriminate between ideal and varying sub-ideal states.

  14. Hysteretic Behavior of Prestressed Concrete Bridge Pier with Fiber Model

    OpenAIRE

    Hui-li, Wang; Guang-qi, Feng; Si-feng, Qin

    2014-01-01

    The hysteretic behavior and seismic characteristics of the prestressed concrete bridge pier were researched. The effects of the prestressed tendon ratio, the longitudinal reinforcement ratio, and the stirrup reinforcement ratio on the hysteretic behavior and seismic characteristics of the prestressed concrete bridge pier have been obtained with the fiber model analysis method. The analysis show some results about the prestressed concrete bridge pier. Firstly, greater prestressed tendon ratio ...

  15. Analysis of the ecological conservation behavior of farmers in payment for ecosystem service programs in eco-environmentally fragile areas using social psychology models.

    Science.gov (United States)

    Deng, Jian; Sun, Pingsheng; Zhao, Fazhu; Han, Xinhui; Yang, Gaihe; Feng, Yongzhong

    2016-04-15

    Studies on the ecological conservation behavior of farmers usually focus on individual and socio-economic characteristics without consideration of the underlying psychological constructs, such as farmers' intention and perceptions. This study uses the theory of planned behavior (TPB), a typical social psychology construct, to analyze the factors affecting the intention and behavior of farmers for conserving the ecological achievements from payment for ecosystem service (PES) programs in eco-environmentally fragile areas. Questionnaires based on TPB were administered to 1004 farmers from the Grain to Green Program area in the Loess Plateau, China, with the resulting dataset used to identify the underlying factors determining farmers' intention and behavior based on the structural equation model. The results show that the farmers' intention and behavior toward conserving ecological achievements were explained well by TPB. The farmers'behavior was significantly positively affected by their intention toward conserving ecological achievements, and their intention was significantly influenced by their attitude (positive or negative value of performance), the subjective norm (social pressure in engaging behavior), and perceived behavioral control (perceptions of their ability). The farmers' degree of support for PES programs and their recognition of environmental effects were the factors that most influenced the farmers' attitude. Pressure from neighbors was the most potent driver of the subjective norm. Meanwhile, perceptions of their ability to perform the behavior were the most potent factors affecting intention and it was mostly driven by the farmers' feelings toward environmental improvement and perceived ability (time and labor) to participate in ecological conservation. The drivers of attitude, subjective norm, and perceived behavioral control can be used by policy makers to direct farmers' intention and behavior toward conserving ecological achievements in fragile

  16. Modeling emergent border-crossing behaviors during pandemics

    Science.gov (United States)

    Santos, Eunice E.; Santos, Eugene; Korah, John; Thompson, Jeremy E.; Gu, Qi; Kim, Keum Joo; Li, Deqing; Russell, Jacob; Subramanian, Suresh; Zhang, Yuxi; Zhao, Yan

    2013-06-01

    Modeling real-world scenarios is a challenge for traditional social science researchers, as it is often hard to capture the intricacies and dynamisms of real-world situations without making simplistic assumptions. This imposes severe limitations on the capabilities of such models and frameworks. Complex population dynamics during natural disasters such as pandemics is an area where computational social science can provide useful insights and explanations. In this paper, we employ a novel intent-driven modeling paradigm for such real-world scenarios by causally mapping beliefs, goals, and actions of individuals and groups to overall behavior using a probabilistic representation called Bayesian Knowledge Bases (BKBs). To validate our framework we examine emergent behavior occurring near a national border during pandemics, specifically the 2009 H1N1 pandemic in Mexico. The novelty of the work in this paper lies in representing the dynamism at multiple scales by including both coarse-grained (events at the national level) and finegrained (events at two separate border locations) information. This is especially useful for analysts in disaster management and first responder organizations who need to be able to understand both macro-level behavior and changes in the immediate vicinity, to help with planning, prevention, and mitigation. We demonstrate the capabilities of our framework in uncovering previously hidden connections and explanations by comparing independent models of the border locations with their fused model to identify emergent behaviors not found in either independent location models nor in a simple linear combination of those models.

  17. Bayesian network model of crowd emotion and negative behavior

    Science.gov (United States)

    Ramli, Nurulhuda; Ghani, Noraida Abdul; Hatta, Zulkarnain Ahmad; Hashim, Intan Hashimah Mohd; Sulong, Jasni; Mahudin, Nor Diana Mohd; Rahman, Shukran Abd; Saad, Zarina Mat

    2014-12-01

    The effects of overcrowding have become a major concern for event organizers. One aspect of this concern has been the idea that overcrowding can enhance the occurrence of serious incidents during events. As one of the largest Muslim religious gathering attended by pilgrims from all over the world, Hajj has become extremely overcrowded with many incidents being reported. The purpose of this study is to analyze the nature of human emotion and negative behavior resulting from overcrowding during Hajj events from data gathered in Malaysian Hajj Experience Survey in 2013. The sample comprised of 147 Malaysian pilgrims (70 males and 77 females). Utilizing a probabilistic model called Bayesian network, this paper models the dependence structure between different emotions and negative behaviors of pilgrims in the crowd. The model included the following variables of emotion: negative, negative comfortable, positive, positive comfortable and positive spiritual and variables of negative behaviors; aggressive and hazardous acts. The study demonstrated that emotions of negative, negative comfortable, positive spiritual and positive emotion have a direct influence on aggressive behavior whereas emotion of negative comfortable, positive spiritual and positive have a direct influence on hazardous acts behavior. The sensitivity analysis showed that a low level of negative and negative comfortable emotions leads to a lower level of aggressive and hazardous behavior. Findings of the study can be further improved to identify the exact cause and risk factors of crowd-related incidents in preventing crowd disasters during the mass gathering events.

  18. Characterization of Models for Time-Dependent Behavior of Soils

    DEFF Research Database (Denmark)

    Liingaard, Morten; Augustesen, Anders; Lade, Poul V.

    2004-01-01

    developed for metals and steel but are, to some extent, used to characterize time effects in geomaterials. The third part is a review of constitutive laws that describe not only viscous effects but also the inviscid ( rate-independent) behavior of soils, in principle, under any possible loading condition......  Different classes of constitutive models have been developed to capture the time-dependent viscous phenomena ~ creep, stress relaxation, and rate effects ! observed in soils. Models based on empirical, rheological, and general stress-strain-time concepts have been studied. The first part....... Special attention is paid to elastoviscoplastic models that combine inviscid elastic and time-dependent plastic behavior. Various general elastoviscoplastic models can roughly be divided into two categories: Models based on the concept of overstress and models based on nonstationary flow surface theory...

  19. Motorcycle safety among motorcycle taxi drivers and nonoccupational motorcyclists in developing countries: A case study of Maoming, South China.

    Science.gov (United States)

    Wu, Connor Y H; Loo, Becky P Y

    2016-01-01

    An increasing number of motorcycle taxis have been involved in traffic crashes in many developing countries. This study examines the characteristics of both motorcycle taxi drivers and nonoccupational motorcyclists, investigates the risks they pose to road safety, and provides recommendations to minimize their risks. Based on the data collected from a questionnaire survey of 867 motorcycle taxi drivers and 2,029 nonoccupational motorcyclists in Maoming, South China, comparisons were made to analyze differences of personal attributes, attitudes toward road safety, and self-reported behavior of the 2 groups. Results of the chi-square tests show that not only motorcycle taxi drivers but also nonoccupational motorcyclists in Maoming held poor attitudes toward road safety and both groups reported unsafe driving behavior. There is much room for improving local road safety education among all motorcyclists in Maoming. Yet, motorcycle taxi drivers were more likely to pose road safety risks than nonoccupational motorcyclists under some circumstances, such as speeding late at night or early in the morning, not requiring passengers to wear helmets, and running a red light. The results of the binary logistic regression model show that possessing a vehicle license for a motorcycle or not was the common significant predictor for unsafe driving behavior of motorcycle taxi drivers and nonoccupational motorcyclists. Therefore, enforcement against all motorcyclists not showing vehicle licenses for their motorcycles should be stepped up. Motorcycle safety is largely poor in Maoming. Therefore, efforts to improve motorcycle safety should be strengthened by targeting not only motorcycle taxi drivers but also nonoccupational motorcyclists.

  20. [Occupational stress situation analysis of different types of train drivers].

    Science.gov (United States)

    Zhou, Wenhui; Gu, Guizhen; Wu, Hui; Yu, Shanfa

    2014-11-01

    To analyze the status of occupational stress in different types of train drivers. By using cluster sampling method, a cross-sectional study was conducted in 1 339 train drivers (including 289 passenger train drivers, 637 freight trains drivers, 339 passenger shunting train drivers, and 74 high speed rail drivers) from a Railway Bureau depot. The survey included individual factors, occupational stress factors, stress response factors and stress mitigating factors. The occupational stress factors, stress response factors and mitigating factors were measured by the revised effort-reward imbalance (ERI) model questionnaires and occupational stress measurement scale. By using the method of covariance analysized the difference of occupational stress factors of all types train drivers, the method of Stepwise regression was used to analyze the effection (R(2)) of occupational stress factors and stress mitigating factors on stress response factors. Covariance analysis as covariates in age, education level, length of service and marital status showed that the scores of ERI (1.58 ± 0.05), extrinsic effort (19.88 ± 0.44), rewards (23.43 ± 0.43), intrinsic effort (17.86 ± 0.36), physical environment (5.70 ± 0.22), social support (30.51 ± 0.88) and daily tension (10.27 ± 0.38 ) of high speed rail drivers were higher than other drivers (F values were 6.06, 11.32, 7.05, 13.25, 5.20, 9.48 and 6.14 respectively, P train drivers were higher than other drivers (F values were 4.33 and 5.50 respectively, P train drivers was high speed rail drivers (R(2) = 0.64), passenger train drivers (R(2) = 0.44), passenger shunting train drivers (R(2) = 0.39), freight trains drivers (R(2) = 0.38); job satisfaction of train drivers was high speed rail drivers (R(2) = 0.68), passenger train drivers (R(2) = 0.62), freight trains drivers (R(2) = 0.43), passenger shunting train drivers(R(2) = 0.38); to daily tension of train drivers was high speed rail drivers (R(2) = 0.54), passenger train