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Sample records for based adaptive traffic

  1. Adaptive Automation Based on Air Traffic Controller Decision-Making

    NARCIS (Netherlands)

    IJtsma (Student TU Delft), Martijn; Borst, C.; Mercado Velasco, G.A.; Mulder, M.; van Paassen, M.M.; Tsang, P.S.; Vidulich, M.A.

    2017-01-01

    Through smart scheduling and triggering of automation support, adaptive automation has the potential to balance air traffic controller workload. The challenge in the design of adaptive automation systems is to decide how and when the automation should provide support. This paper describes the design

  2. The Use of Adaptive Traffic Signal Systems Based on Floating Car Data

    Directory of Open Access Journals (Sweden)

    Vittorio Astarita

    2017-01-01

    Full Text Available This paper presents a simple concept which has not been, up to now, thoroughly explored in scientific research: the use of information coming from the network of Internet connected mobile devices (on vehicles to regulate traffic light systems. Three large-scale changes are going to shape the future of transportation and could lead to the regulation of traffic signal system based on floating car data (FCD: (i the implementation of Internet connected cars with global navigation satellite (GNSS system receivers and the autonomous car revolution; (ii the spreading of mobile cooperative Web 2.0 and the extension to connected vehicles; (iii an increasing need for sustainability of transportation in terms of energy efficiency, traffic safety, and environmental issues. Up to now, the concept of floating car data (FCD has only been extensively used to obtain traffic information and estimate traffic parameters. Traffic lights regulation based on FCD technology has not been fully researched since the implementation requires new ideas and algorithms. This paper intends to provide a seminal insight into the important issue of adaptive traffic light based on FCD by presenting ideas that can be useful to researchers and engineers in the long-term task of developing new algorithms and systems that may revolutionize the way traffic lights are regulated.

  3. Self-Adapting Routing Overlay Network for Frequently Changing Application Traffic in Content-Based Publish/Subscribe System

    Directory of Open Access Journals (Sweden)

    Meng Chi

    2014-01-01

    Full Text Available In the large-scale distributed simulation area, the topology of the overlay network cannot always rapidly adapt to frequently changing application traffic to reduce the overall traffic cost. In this paper, we propose a self-adapting routing strategy for frequently changing application traffic in content-based publish/subscribe system. The strategy firstly trains the traffic information and then uses this training information to predict the application traffic in the future. Finally, the strategy reconfigures the topology of the overlay network based on this predicting information to reduce the overall traffic cost. A predicting path is also introduced in this paper to reduce the reconfiguration numbers in the process of the reconfigurations. Compared to other strategies, the experimental results show that the strategy proposed in this paper could reduce the overall traffic cost of the publish/subscribe system in less reconfigurations.

  4. Adaptive EWMA Method Based on Abnormal Network Traffic for LDoS Attacks

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    Dan Tang

    2014-01-01

    Full Text Available The low-rate denial of service (LDoS attacks reduce network services capabilities by periodically sending high intensity pulse data flows. For their concealed performance, it is more difficult for traditional DoS detection methods to detect LDoS attacks; at the same time the accuracy of the current detection methods for LDoS attacks is relatively low. As the fact that LDoS attacks led to abnormal distribution of the ACK traffic, LDoS attacks can be detected by analyzing the distribution characteristics of ACK traffic. Then traditional EWMA algorithm which can smooth the accidental error while being the same as the exceptional mutation may cause some misjudgment; therefore a new LDoS detection method based on adaptive EWMA (AEWMA algorithm is proposed. The AEWMA algorithm which uses an adaptive weighting function instead of the constant weighting of EWMA algorithm can smooth the accidental error and retain the exceptional mutation. So AEWMA method is more beneficial than EWMA method for analyzing and measuring the abnormal distribution of ACK traffic. The NS2 simulations show that AEWMA method can detect LDoS attacks effectively and has a low false negative rate and a false positive rate. Based on DARPA99 datasets, experiment results show that AEWMA method is more efficient than EWMA method.

  5. Adaptive Correction Forecasting Approach for Urban Traffic Flow Based on Fuzzy c-Mean Clustering and Advanced Neural Network

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    He Huang

    2013-01-01

    Full Text Available Forecasting of urban traffic flow is important to intelligent transportation system (ITS developments and implementations. The precise forecasting of traffic flow will be pretty helpful to relax road traffic congestion. The accuracy of traditional single model without correction mechanism is poor. Summarizing the existing prediction models and considering the characteristics of the traffic itself, a traffic flow prediction model based on fuzzy c-mean clustering method (FCM and advanced neural network (NN was proposed. FCM can improve the prediction accuracy and robustness of the model, while advanced NN can optimize the generalization ability of the model. Besides these, the output value of the model is calibrated by the correction mechanism. The experimental results show that the proposed method has better prediction accuracy and robustness than the other models.

  6. Adaptive traffic control systems for urban networks

    Directory of Open Access Journals (Sweden)

    Radivojević Danilo

    2017-01-01

    Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

  7. A Traffic Prediction Model for Self-Adapting Routing Overlay Network in Publish/Subscribe System

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    Meng Chi

    2017-01-01

    Full Text Available In large-scale location-based service, an ideal situation is that self-adapting routing strategies use future traffic data as input to generate a topology which could adapt to the changing traffic well. In the paper, we propose a traffic prediction model for the broker in publish/subscribe system, which can predict the traffic of the link in future by neural network. We first introduced our traffic prediction model and then described the model integration. Finally, the experimental results show that our traffic prediction model could predict the traffic of link well.

  8. Cross-layer based adaptive wireless traffic control for per-flow and per-station fairness

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    Siwamogsatham Siwaruk

    2011-01-01

    Full Text Available Abstract In the IEEE 802.11 wireless LANs, the bandwidth is not fairly shared among stations due to the distributed coordination function (DCF mechanism in the IEEE 802.11 MAC protocol. It introduces the per-flow and per-station unfairness problems between uplink and downlink flows, as the uplink flows usually dominate the downlink flows. In addition, some users may use greedy applications such as video streaming, which may prevent other applications from connecting to the Internet. In this article, we propose an adaptive cross-layer bandwidth allocation mechanism to provide per-station and per-flow fairness. To verify the effectiveness and scalability, our scheme is implemented on a wireless access router and numerous experiments in a typical wireless environment with both TCP and UDP traffic are conducted to evaluate performance of the proposed scheme.

  9. Preceding Vehicle Detection and Tracking Adaptive to Illumination Variation in Night Traffic Scenes Based on Relevance Analysis

    Science.gov (United States)

    Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

    2014-01-01

    Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation. PMID:25195855

  10. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

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    Antonio Artuñedo

    2017-04-01

    Full Text Available Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

  11. Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

    Science.gov (United States)

    Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

    2017-04-26

    Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

  12. An Adaptive Fuzzy-Logic Traffic Control System in Conditions of Saturated Transport Stream

    Science.gov (United States)

    Marakhimov, A. R.; Igamberdiev, H. Z.; Umarov, Sh. X.

    2016-01-01

    This paper considers the problem of building adaptive fuzzy-logic traffic control systems (AFLTCS) to deal with information fuzziness and uncertainty in case of heavy traffic streams. Methods of formal description of traffic control on the crossroads based on fuzzy sets and fuzzy logic are proposed. This paper also provides efficient algorithms for implementing AFLTCS and develops the appropriate simulation models to test the efficiency of suggested approach. PMID:27517081

  13. Agent Based Individual Traffic Guidance

    DEFF Research Database (Denmark)

    Wanscher, Jørgen

    This thesis investigates the possibilities in applying Operations Research (OR) to autonomous vehicular traffic. The explicit difference to most other research today is that we presume that an agent is present in every vehicle - hence Agent Based Individual Traffic guidance (ABIT). The next...... evolutionary step for the in-vehicle route planners is the introduction of two-way communication. We presume that the agent is capable of exactly this. Based on this presumption we discuss the possibilities and define a taxonomy and use this to discuss the ABIT system. Based on a set of scenarios we conclude...... that the system can be divided into two separate constituents. The immediate dispersion, which is used for small areas and quick response, and the individual alleviation, which considers the longer distance decision support. Both of these require intrinsicate models and cost functions which at the beginning...

  14. A Novel Method of Adaptive Traffic Image Enhancement for Complex Environments

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    Cao Liu

    2015-01-01

    Full Text Available There exist two main drawbacks for traffic images in classic image enhancement methods. First is the performance degradation that occurs under frontlight, backlight, and extremely dark conditions. The second drawback is complicated manual settings, such as transform functions and multiple parameter selection mechanisms. Thus, this paper proposes an effective and adaptive parameter optimization enhancement algorithm based on adaptive brightness baseline drift (ABBD for color traffic images under different luminance conditions. This method consists of two parts: brightness baseline model acquisition and adaptive color image compensation. The brightness baseline model can be attained by analyzing changes in light along a timeline. The adaptive color image compensation involves color space remapping and adaptive compensation specific color components. Our experiments were tested on various traffic images under frontlight, backlight, and during nighttime. The experimental results show that the proposed method achieved better effects compared with other available methods under different luminance conditions, which also effectively reduced the influence of the weather.

  15. Adaptive traffic signal control with actor-critic methods in a real-world traffic network with different traffic disruption events

    NARCIS (Netherlands)

    Aslani, Mohammad; Mesgari, Mohammad Saadi; Wiering, Marco

    2017-01-01

    The transportation demand is rapidly growing in metropolises, resulting in chronic traffic con-gestions in dense downtown areas. Adaptive traffic signal control as the principle part of in-telligent transportation systems has a primary role to effectively reduce traffic congestion by making a

  16. TOWARDS A CLOUD BASED SMART TRAFFIC MANAGEMENT FRAMEWORK

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    M. M. Rahimi

    2017-09-01

    Full Text Available Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

  17. Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment

    Science.gov (United States)

    Aricò, Pietro; Borghini, Gianluca; Di Flumeri, Gianluca; Colosimo, Alfredo; Bonelli, Stefano; Golfetti, Alessia; Pozzi, Simone; Imbert, Jean-Paul; Granger, Géraud; Benhacene, Raïlane; Babiloni, Fabio

    2016-01-01

    Adaptive Automation (AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both the under- and over-load conditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the AA solutions without affecting the operative task. In this regard, passive Brain-Computer Interface (pBCI) systems are a good candidate to activate automation, since they are able to gather information about the covert behavior (e.g., mental workload) of a subject by analyzing its neurophysiological signals (i.e., brain activity), and without interfering with the ongoing operational activity. We proposed a pBCI system able to trigger AA solutions integrated in a realistic Air Traffic Management (ATM) research simulator developed and hosted at ENAC (École Nationale de l'Aviation Civile of Toulouse, France). Twelve Air Traffic Controller (ATCO) students have been involved in the experiment and they have been asked to perform ATM scenarios with and without the support of the AA solutions. Results demonstrated the effectiveness of the proposed pBCI system, since it enabled the AA mostly during the high-demanding conditions (i.e., overload situations) inducing a reduction of the mental workload under which the ATCOs were operating. On the contrary, as desired, the AA was not activated when workload level was under the threshold, to prevent too low demanding conditions that could bring the operator's workload level toward potentially dangerous conditions of underload. PMID:27833542

  18. The Study of Reinforcement Learning for Traffic Self-Adaptive Control under Multiagent Markov Game Environment

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    Lun-Hui Xu

    2013-01-01

    Full Text Available Urban traffic self-adaptive control problem is dynamic and uncertain, so the states of traffic environment are hard to be observed. Efficient agent which controls a single intersection can be discovered automatically via multiagent reinforcement learning. However, in the majority of the previous works on this approach, each agent needed perfect observed information when interacting with the environment and learned individually with less efficient coordination. This study casts traffic self-adaptive control as a multiagent Markov game problem. The design employs traffic signal control agent (TSCA for each signalized intersection that coordinates with neighboring TSCAs. A mathematical model for TSCAs’ interaction is built based on nonzero-sum markov game which has been applied to let TSCAs learn how to cooperate. A multiagent Markov game reinforcement learning approach is constructed on the basis of single-agent Q-learning. This method lets each TSCA learn to update its Q-values under the joint actions and imperfect information. The convergence of the proposed algorithm is analyzed theoretically. The simulation results show that the proposed method is convergent and effective in realistic traffic self-adaptive control setting.

  19. Agent Based Individual Traffic guidance

    DEFF Research Database (Denmark)

    Wanscher, Jørgen Bundgaard

    2004-01-01

    can be obtained through cellular phone tracking or GPS systems. This information can then be used to provide individual traffic guidance as opposed to the mass information systems of today -- dynamic roadsigns and trafficradio. The goal is to achieve better usage of road and time. The main topic......When working with traffic planning or guidance it is common practice to view the vehicles as a combined mass. >From this models are employed to specify the vehicle supply and demand for each region. As the models are complex and the calculations are equally demanding the regions and the detail...

  20. A Cooperative Human-Adaptive Traffic Simulation (CHATS)

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    Phillips, Charles T.; Ballin, Mark G.

    1999-01-01

    NASA is considering the development of a Cooperative Human-Adaptive Traffic Simulation (CHATS), to examine and evaluate performance of the National Airspace System (NAS) as the aviation community moves toward free flight. CHATS will be specifically oriented toward simulating strategic decision-making by airspace users and by the service provider s traffic management personnel, within the context of different airspace and rules assumptions. It will use human teams to represent these interests and make decisions, and will rely on computer modeling and simulation to calculate the impacts of these decisions. The simulation objectives will be to examine: 1. evolution of airspace users and the service provider s strategies, through adaptation to new operational environments; 2. air carriers competitive and cooperative behavior; 3. expected benefits to airspace users and the service provider as compared to the current NAS; 4. operational limitations of free flight concepts due to congestion and safety concerns. This paper describes an operational concept for CHATS, and presents a high-level functional design which would utilize a combination of existing and new models and simulation capabilities.

  1. Policy based traffic light control – Balancing weights of user groups

    NARCIS (Netherlands)

    Vreeswijk, Jacob Dirk; Wismans, Luc Johannes Josephus; Tutert, Bas

    2013-01-01

    On the basis of policy-based target groups, we developed a prioritization strategy for traffic streams and applied it with the adaptive urban traffic control (UTC) ImFlow. Our main aim was to gain understanding of the possibilities of a policy driven prioritization in an urban context. We conclude

  2. Fuzzy Logic Based Autonomous Traffic Control System

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    Muhammad ABBAS

    2012-01-01

    Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.

  3. Towards reducing traffic congestion using cooperative adaptive cruise control on a freeway with a ramp

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    Georges Arnaout

    2011-12-01

    Full Text Available Purpose: In this paper, the impact of Cooperative Adaptive Cruise Control (CACC systems on traffic performance is examined using microscopic agent-based simulation. Using a developed traffic simulation model of a freeway with an on-ramp - created to induce perturbations and to trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The previously proposed traffic simulation model is extended and validated. By embedding CACC vehicles in different penetration levels, the results show significance and indicate the potential of CACC systems to improve traffic characteristics and therefore can be used to reduce traffic congestion. The study shows that the impact of CACC is positive but is highly dependent on the CACC market penetration. The flow rate of the traffic using CACC is proportional to the market penetration rate of CACC equipped vehicles and the density of the traffic.Design/methodology/approach: This paper uses microscopic simulation experiments followed by a quantitative statistical analysis. Simulation enables researchers manipulating the system variables to straightforwardly predict the outcome on the overall system, giving researchers the unique opportunity to interfere and make improvements to performance. Thus with simulation, changes to variables that might require excessive time, or be unfeasible to carry on real systems, are often completed within seconds.Findings: The findings of this paper are summarized as follow:•\tProvide and validate a platform (agent-based microscopic traffic simulator in which any CACC algorithm (current or future may be evaluated.•\tProvide detailed analysis associated with implementation of CACC vehicles on freeways.•\tInvestigate whether embedding CACC vehicles on freeways has a significant positive impact or not.Research limitations/implications: The main limitation of this research is that it has been conducted solely in a computer laboratory. Laboratory

  4. Multi-Agent Look-Ahead Traffic-Adaptive Control

    NARCIS (Netherlands)

    Van Katwijk, R.T.

    2008-01-01

    The objective of this thesis is to create a distributed, multi-agent, approach to traffic control. This PhD thesis' focus is on the control of a network instrumented by traffic signals.A thorough literature study has been performed, reviewing the current state of the art in traffic signal control.

  5. Traffic

    International Nuclear Information System (INIS)

    Lichtblau, G.

    2001-01-01

    This chapter deals with passenger and freight traffic, public and private transportation, traffic related environmental impacts, future developments, traffic indicators, regional traffic planning, health costs due to road traffic related air pollution, noise pollution, measures and regulations for traffic control and fuels for traffic. In particular energy consumption, energy efficiency, pollutant emissions ( CO 2 , SO 2 , NO x , HC, CO, N 2 O, NH 3 and particulates) and environmental effects of the different types of traffic and different types of fuels are compared and studied. Legal regulations and measures for an effective traffic control are discussed. (a.n.)

  6. Highway traffic noise prediction based on GIS

    Science.gov (United States)

    Zhao, Jianghua; Qin, Qiming

    2014-05-01

    Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.

  7. Relaxing Synchronization in Parallel Agent-Based Road Traffic Simulation

    NARCIS (Netherlands)

    Xu, Y.; Cai, W.; Aydt, H.; Lees, M.; Zehe, D.

    Large-scale agent-based traffic simulation is computationally intensive. Parallel computing can help to speed up agent-based traffic simulation. Parallelization of agent-based traffic simulations is generally achieved by decomposing the road network into subregions. The agents in each subregion are

  8. Simulating and evaluating an adaptive and integrated traffic lights control system for smart city application

    Science.gov (United States)

    Djuana, E.; Rahardjo, K.; Gozali, F.; Tan, S.; Rambung, R.; Adrian, D.

    2018-01-01

    A city could be categorized as a smart city when the information technology has been developed to the point that the administration could sense, understand, and control every resource to serve its people and sustain the development of the city. One of the smart city aspects is transportation and traffic management. This paper presents a research project to design an adaptive traffic lights control system as a part of the smart system for optimizing road utilization and reducing congestion. Research problems presented include: (1) Congestion in one direction toward an intersection due to dynamic traffic condition from time to time during the day, while the timing cycles in traffic lights system are mostly static; (2) No timing synchronization among traffic lights in adjacent intersections that is causing unsteady flows; (3) Difficulties in traffic condition monitoring on the intersection and the lack of facility for remotely controlling traffic lights. In this research, a simulator has been built to model the adaptivity and integration among different traffic lights controllers in adjacent intersections, and a case study consisting of three sets of intersections along Jalan K. H. Hasyim Ashari has been simulated. It can be concluded that timing slots synchronization among traffic lights is crucial for maintaining a steady traffic flow.

  9. Decision-making tool for applying adaptive traffic control systems : final report.

    Science.gov (United States)

    2016-03-01

    Adaptive traffic signal control technologies have been increasingly deployed in real world situations. The objective of this project was to develop a decision-making tool to guide traffic engineers and decision-makers who must decide whether or not a...

  10. The transportation network rough description for an adaptive traffic control algorithms by means of video detection technique

    Directory of Open Access Journals (Sweden)

    Jan PIECHA

    2013-01-01

    Full Text Available The contribution discusses a transportation network rough description that corresponds to satisfactory level of an adaptive traffic control algorithms implementation [4], supported by video-detection system. The decision making algorithms have to provide us with not only vehicles’ approach time prediction, at the intersections but also finding possible solution for avoiding critical queues at the intersections. Majority of traditional traffic control systems are based on number of cars recorded by inductive loops, however they do not define any proper occupation states at any traffic lane. The time window indicated for passing the defined number of cars loses the distance gaps visible between the cars on the traffic lane. That is why remarkable part from the defined number of cars will not cross the intersection in the defined green light time. Procedures used for searching an optimal solution using the inductive measurements can, in the majority cases, be undoubtedly noticed as a theoretical analysis only.

  11. Fixed Point Learning Based Intelligent Traffic Control System

    Science.gov (United States)

    Zongyao, Wang; Cong, Sui; Cheng, Shao

    2017-10-01

    Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

  12. Research on the Method of Traffic Organization and Optimization Based on Dynamic Traffic Flow Model

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    Shu-bin Li

    2017-01-01

    Full Text Available The modern transportation system is becoming sluggish by traffic jams, so much so that it can harm the economic and society in our country. One of the reasons is the surging vehicles day by day. Another reason is the shortage of the traffic supply seriously. But the most important reason is that the traffic organization and optimization hardly met the conditions of modern transport development. In this paper, the practical method of the traffic organization and optimization used in regional area is explored by the dynamic traffic network analysis method. Firstly, the operational states of the regional traffic network are obtained by simulation method based on the self-developed traffic simulation software DynaCHINA, in which the improved traffic flow simulation model was proposed in order to be more suitable for actual domestic urban transport situation. Then the appropriated optimization model and algorithm were proposed according to different optimized content and organization goals, and the traffic simulation processes more suitable to regional optimization were designed exactly. Finally, a regional network in Tai’an city was selected as an example. The simulation results show that the proposed method is effective and feasible. It can provide strong scientific and technological support for the traffic management department.

  13. Intelligent Traffic Light Based on PLC Control

    Science.gov (United States)

    Mei, Lin; Zhang, Lijian; Wang, Lingling

    2017-11-01

    The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

  14. Macroscopic Traffic State Estimation: Understanding Traffic Sensing Data-Based Estimation Errors

    Directory of Open Access Journals (Sweden)

    Paul B. C. van Erp

    2017-01-01

    Full Text Available Traffic state estimation is a crucial element in traffic management systems and in providing traffic information to road users. In this article, we evaluate traffic sensing data-based estimation error characteristics in macroscopic traffic state estimation. We consider two types of sensing data, that is, loop-detector data and probe speed data. These data are used to estimate the mean speed in a discrete space-time mesh. We assume that there are no errors in the sensing data. This allows us to study the errors resulting from the differences in characteristics between the sensing data and desired estimate together with the incomplete description of the relation between the two. The aim of the study is to evaluate the dependency of this estimation error on the traffic conditions and sensing data characteristics. For this purpose, we use microscopic traffic simulation, where we compare the estimates with the ground truth using Edie’s definitions. The study exposes a relation between the error distribution characteristics and traffic conditions. Furthermore, we find that it is important to account for the correlation between individual probe data-based estimation errors. Knowledge related to these estimation errors contributes to making better use of the available sensing data in traffic state estimation.

  15. Traffic data reconstruction based on Markov random field modeling

    International Nuclear Information System (INIS)

    Kataoka, Shun; Tanaka, Kazuyuki; Yasuda, Muneki; Furtlehner, Cyril

    2014-01-01

    We consider the traffic data reconstruction problem. Suppose we have the traffic data of an entire city that are incomplete because some road data are unobserved. The problem is to reconstruct the unobserved parts of the data. In this paper, we propose a new method to reconstruct incomplete traffic data collected from various sensors. Our approach is based on Markov random field modeling of road traffic. The reconstruction is achieved by using a mean-field method and a machine learning method. We numerically verify the performance of our method using realistic simulated traffic data for the real road network of Sendai, Japan. (paper)

  16. Adaptive Traffic Control Systems in a medium-sized Scandinavian city

    DEFF Research Database (Denmark)

    Agerholm, Niels; Olesen, Anne Vingaard

    2018-01-01

    Adaptive Traffic Control Systems (ATCS) are aimed at reducing congestion. ATCS adapt to approaching traffic to continuously optimise the traffic flows in question. ATCS have been implemented in many locations, including the Scandinavian countries, with various effects. Due to congestion problems......, ATCS were installed in the eight signalised intersections of a 1.7 km stretch of the ring road in the medium-sized Danish city of Aalborg. To measure the effect of ATCS a with/without study was carried out. GPS data from a car following the traffic, recorded transportation times for buses in service......, and GPS data from a range of cars driving on the ring road formed the basis for the study. The result of ATCS implementation was a significant 17% reduction in transportation time on the ring road in the most congested period, the afternoon peak. Less significant effects were found regarding the morning...

  17. Temporal-Spatial Analysis of Traffic Congestion Based on Modified CTM

    Directory of Open Access Journals (Sweden)

    Chenglong Chu

    2015-01-01

    Full Text Available A modified cell transmission model (CTM is proposed to depict the temporal-spatial evolution of traffic congestion on urban freeways. Specifically, drivers’ adaptive behaviors and the corresponding influence on traffic flows are emphasized. Two piecewise linear regression models are proposed to describe the relationship of flow and density (occupancy. Several types of cellular connections are designed to depict urban rapid roads with on/off-ramps and junctions. Based on the data collected on freeway of Queen Elizabeth, Ontario, Canada, we show that the new model provides a relatively higher accuracy of temporal-spatial evolution of traffic congestions.

  18. BEAGLEBOARD EMBEDDED SYSTEM FOR ADAPTIVE TRAFFIC LIGHT CONTROL SYSTEM WITH CAMERA SENSOR

    Directory of Open Access Journals (Sweden)

    Muhammad Febrian Rachmadi

    2012-07-01

    Full Text Available Traffic is one of the most important aspects in human daily life because traffic affects smoothness of capital flows, logistics, and other community activities. Without appropriate traffic light control system, possibility of traffic congestion will be very high and hinder people’s life in urban areas. Adaptive traffic light control system can be used to solve traffic congestions in an intersection because it can adaptively change the durations of green light each lane in an intersection depend on traffic density. The proposed adaptive traffic light control system prototype uses Beagleboard-xM, CCTV camera, and AVR microcontrollers. We use computer vision technique to obtain information on traffic density combining Viola-Jones method with Kalman Filter method. To calculate traffic light time of each traffic light in intersection, we use Distributed Constraint Satisfaction Problem (DCSP. From implementations and experiments results, we conclude that BeagleBoard-xM can be used as main engine of adaptive traffic light control system with 91.735% average counting rate. Lalu intas adalah salah satu aspek yang paling penting dalam kehidupan sehari-hari manusia karena lalu lintas memengaruhi kelancaran arus modal, logistik, dan kegiatan masyarakat lainnya. Tanpa sistem kontrol lampu lalu lintas yang memadai, kemungkinan kemacetan lalu lintas akan sangat tinggi dan menghambat kehidupan masyarakat di perkotaan. Sistem kontrol lampu lalu lintas adaptif dapat digunakan untuk memecahkan kemacetan lalu lintas di persimpangan karena dapat mengubah durasi lampu hijau di setiap persimpangan jalan tergantung pada kepadatan lalu lintas. Prototipe sistem kontrol lampu lalu lintas menggunakan BeagleBoard-XM, kamera CCTV, dan mikrokontroler AVR. Peneliti menggunakan teknik computer vision untuk mendapatkan informasi tentang kepadatan lalu lintas dengan menggabungkan metode Viola-Jones dan metode Filter Kalman. Untuk menghitung waktu setiap lampu lalu lintas

  19. Visual traffic jam analysis based on trajectory data.

    Science.gov (United States)

    Wang, Zuchao; Lu, Min; Yuan, Xiaoru; Zhang, Junping; van de Wetering, Huub

    2013-12-01

    In this work, we present an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system.

  20. Traffic and Driving Simulator Based on Architecture of Interactive Motion

    Science.gov (United States)

    Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

    2015-01-01

    This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination. PMID:26491711

  1. A Novel Architecture for Adaptive Traffic Control in Network on Chip using Code Division Multiple Access Technique

    OpenAIRE

    Fatemeh. Dehghani; Shahram. Darooei

    2016-01-01

    Network on chip has emerged as a long-term and effective method in Multiprocessor System-on-Chip communications in order to overcome the bottleneck in bus based communication architectures. Efficiency and performance of network on chip is so dependent on the architecture and structure of the network. In this paper a new structure and architecture for adaptive traffic control in network on chip using Code Division Multiple Access technique is presented. To solve the problem of synchronous acce...

  2. Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers.

    Science.gov (United States)

    Oviedo-Trespalacios, Oscar; Haque, Md Mazharul; King, Mark; Washington, Simon

    2017-04-01

    The use of mobile phones while driving remains a major human factors issue in the transport system. A significant safety concern is that driving while distracted by a mobile phone potentially modifies the driving speed leading to conflicts with other road users and consequently increases crash risk. However, the lack of systematic knowledge of the mechanisms involved in speed adaptation of distracted drivers constrains the explanation and modelling of the extent of this phenomenon. The objective of this study was to investigate speed adaptation of distracted drivers under varying road infrastructure and traffic complexity conditions. The CARRS-Q Advanced Driving Simulator was used to test participants on a simulated road with different traffic conditions, such as free flow traffic along straight roads, driving in urbanized areas, and driving in heavy traffic along suburban roads. Thirty-two licensed young drivers drove the simulator under three phone conditions: baseline (no phone conversation), hands-free and handheld phone conversations. To understand the relationships between distraction, road infrastructure and traffic complexity, speed adaptation calculated as the deviation of driving speed from the posted speed limit was modelled using a decision tree. The identified groups of road infrastructure and traffic characteristics from the decision tree were then modelled with a Generalized Linear Mixed Model (GLMM) with repeated measures to develop inferences about speed adaptation behaviour of distracted drivers. The GLMM also included driver characteristics and secondary task demands as predictors of speed adaptation. Results indicated that complex road environments like urbanization, car-following situations along suburban roads, and curved road alignment significantly influenced speed adaptation behaviour. Distracted drivers selected a lower speed while driving along a curved road or during car-following situations, but speed adaptation was negligible in the

  3. Calculating Traffic based on Road Sensor Data

    NARCIS (Netherlands)

    Bisseling, Rob; Gao, Fengnan; Hafkenscheid, Patrick; Idema, Reijer; Jetka, Tomasz; Guerra Ones, Valia; Rata, Debanshu; Sikora, Monika

    2014-01-01

    Road sensors gather a lot of statistical data about traffic. In this paper, we discuss how a measure for the amount of traffic on the roads can be derived from this data, such that the measure is independent of the number and placement of sensors, and the calculations can be performed quickly for

  4. Evaluating the safety impact of adaptive cruise control in traffic oscillations on freeways.

    Science.gov (United States)

    Li, Ye; Li, Zhibin; Wang, Hao; Wang, Wei; Xing, Lu

    2017-07-01

    Adaptive cruise control (ACC) has been considered one of the critical components of automated driving. ACC adjusts vehicle speeds automatically by measuring the status of the ego-vehicle and leading vehicle. Current commercial ACCs are designed to be comfortable and convenient driving systems. Little attention is paid to the safety impacts of ACC, especially in traffic oscillations when crash risks are the highest. The primary objective of this study was to evaluate the impacts of ACC parameter settings on rear-end collisions on freeways. First, the occurrence of a rear-end collision in a stop-and-go wave was analyzed. A car-following model in an integrated ACC was developed for a simulation analysis. The time-to-collision based factors were calculated as surrogate safety measures of the collision risk. We also evaluated different market penetration rates considering that the application of ACC will be a gradual process. The results showed that the safety impacts of ACC were largely affected by the parameters. Smaller time delays and larger time gaps improved safety performance, but inappropriate parameter settings increased the collision risks and caused traffic disturbances. A higher reduction of the collision risk was achieved as the ACC vehicle penetration rate increased, especially in the initial stage with penetration rates of less than 30%. This study also showed that in the initial stage, the combination of ACC and a variable speed limit achieved better safety improvements on congested freeways than each single technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Simulation and analysis of traffic flow based on cellular automaton

    Science.gov (United States)

    Ren, Xianping; Liu, Xia

    2018-03-01

    In this paper, single-lane and two-lane traffic model are established based on cellular automaton. Different values of vehicle arrival rate at the entrance and vehicle departure rate at the exit are set to analyze their effects on density, average speed and traffic flow. If the road exit is unblocked, vehicles can pass through the road smoothly despite of the arrival rate at the entrance. If vehicles enter into the road continuously, the traffic condition is varied with the departure rate at the exit. To avoid traffic jam, reasonable vehicle departure rate should be adopted.

  6. The development of a method to measure speed adaptation to traffic complexity: Identifying novice, unsafe, and overconfident drivers.

    NARCIS (Netherlands)

    Craen, S. de Twisk, D.A.M. Hagenzieker, M.P. Elffers, H. & Brookhuis, K.A.

    2008-01-01

    To monitor novice driver performance in the first years of solo driving, a test aimed at assessing speed adaptation to the traffic situation was developed and evaluated. The Adaptation Test consisted of 18 traffic scenes presented in two (almost) identical photographs, which differed in one single

  7. The development of a method to measure speed adaptation to traffic complexity : Identifying novice, unsafe, and overconfident drivers

    NARCIS (Netherlands)

    de Craen, Saskia; Twisk, Divera A. M.; Hagenzieker, Marjan P.; Elffers, Henk; Brookhuis, Karel A.

    To monitor novice driver performance in the first years of solo driving, a test aimed at assessing speed adaptation to the traffic situation was developed and evaluated. The Adaptation Test consisted of 18 traffic scenes presented in two (almost) identical photographs, which differed in one single

  8. Adaptation Computing Parameters of Pan-Tilt-Zoom Cameras for Traffic Monitoring

    Directory of Open Access Journals (Sweden)

    Ya Lin WU

    2014-01-01

    Full Text Available The Closed- CIRCUIT television (CCTV cameras have been widely used in recent years for traffic monitoring and surveillance applications. We can use CCTV cameras to extract automatically real-time traffic parameters according to the image processing and tracking technologies. Especially, the pan-tilt-zoom (PTZ cameras can provide flexible view selection as well as a wider observation range, and this makes the traffic parameters can be accurately calculated. Therefore, that the parameters of PTZ cameras are calibrated plays an important role in vision-based traffic applications. However, in the specific traffic environment, which is that the license plate number of the illegal parking is located, the parameters of PTZ cameras have to be updated according to the position and distance of illegal parking. In proposed traffic monitoring systems, we use the ordinary webcam and PTZ camera. We get vanishing-point of traffic lane lines in the pixel-based coordinate system by fixed webcam. The parameters of PTZ camera can be initialized by distance of the traffic monitoring and specific objectives and vanishing-point. And then we can use the coordinate position of the illegally parked car to update the parameters of PTZ camera and then get the real word coordinate position of the illegally parked car and use it to compute the distance. The result shows the error of the tested distance and real distance is only 0.2064 meter.

  9. Particle-based model for skiing traffic.

    Science.gov (United States)

    Holleczek, Thomas; Tröster, Gerhard

    2012-05-01

    We develop and investigate a particle-based model for ski slope traffic. Skiers are modeled as particles with a mass that are exposed to social and physical forces, which define the riding behavior of skiers during their descents on ski slopes. We also report position and speed data of 21 skiers recorded with GPS-equipped cell phones on two ski slopes. A comparison of these data with the trajectories resulting from computer simulations of our model shows a good correspondence. A study of the relationship among the density, speed, and flow of skiers reveals that congestion does not occur even with arrival rates of skiers exceeding the maximum ski lift capacity. In a sensitivity analysis, we identify the kinetic friction coefficient of skis on snow, the skier mass, the range of repelling social forces, and the arrival rate of skiers as the crucial parameters influencing the simulation results. Our model allows for the prediction of speed zones and skier densities on ski slopes, which is important in the prevention of skiing accidents.

  10. Particle-based model for skiing traffic

    Science.gov (United States)

    Holleczek, Thomas; Tröster, Gerhard

    2012-05-01

    We develop and investigate a particle-based model for ski slope traffic. Skiers are modeled as particles with a mass that are exposed to social and physical forces, which define the riding behavior of skiers during their descents on ski slopes. We also report position and speed data of 21 skiers recorded with GPS-equipped cell phones on two ski slopes. A comparison of these data with the trajectories resulting from computer simulations of our model shows a good correspondence. A study of the relationship among the density, speed, and flow of skiers reveals that congestion does not occur even with arrival rates of skiers exceeding the maximum ski lift capacity. In a sensitivity analysis, we identify the kinetic friction coefficient of skis on snow, the skier mass, the range of repelling social forces, and the arrival rate of skiers as the crucial parameters influencing the simulation results. Our model allows for the prediction of speed zones and skier densities on ski slopes, which is important in the prevention of skiing accidents.

  11. A Multi-Agent Traffic Control Model Based on Distributed System

    Directory of Open Access Journals (Sweden)

    Qian WU

    2014-06-01

    Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

  12. Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    M. Udin Harun Al Rasyid

    2014-12-01

    Full Text Available Wireless sensor network (WSN uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as power‐efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with non‐adaptive scheme. From the simulation results, our proposed idea has good‐quality data transmission and more efficient in energy consumption, but it has higher delay than that of non‐adaptive scheme. Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.

  13. Effect of the Primary User Traffic on Cognitive Relaying with Adaptive Transmission

    KAUST Repository

    Rao, Anlei

    2012-09-08

    In a cognitive-relay system, the secondary user is permitted to transmit data via a relay when the spectrum bands are detected to be free. The miss detection of spectrum sensing and the primary user traffic will affect the data transmission performance of the secondary user. In this paper, we investigate the impact of the status change of the primary user on the bit error rate (BER) of the adaptive transmission of the secondary user in a cognitive-relay system. Numerical results show that the primary user traffic can significantly degrade the BER of the secondary user transmission.

  14. Reducing Traffic Congestions by Introducing CACC-Vehicles on a Multi-Lane Highway Using Agent-Based Approach

    Science.gov (United States)

    Arnaout, Georges M.; Bowling, Shannon R.

    2011-01-01

    Traffic congestion is an ongoing problem of great interest to researchers from different areas in academia. With the emerging technology for inter-vehicle communication, vehicles have the ability to exchange information with predecessors by wireless communication. In this paper, we present an agent-based model of traffic congestion and examine the impact of having CACC (Cooperative Adaptive Cruise Control) embedded vehicle(s) on a highway system consisting of 4 traffic lanes without overtaking. In our model, CACC vehicles adapt their acceleration/deceleration according to vehicle-to-vehicle inter-communication. We analyze the average speed of the cars, the shockwaves, and the evolution of traffic congestion throughout the lifecycle of the model. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce the oscillatory behavior (stop and go) resulting from the acceleration/deceleration of the vehicles.

  15. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Mingheng

    2013-01-01

    Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

  16. Use of agent based simulation for traffic safety assessment

    CSIR Research Space (South Africa)

    Conradie, Dirk CU

    2008-07-01

    Full Text Available This paper describes the development of an agent based Computational Building Simulation (CBS) tool, termed KRONOS that is being used to work on advanced research questions such as traffic safety assessment and user behaviour in buildings...

  17. Agent-Based Collaborative Traffic Flow Management, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose agent-based game-theoretic approaches for simulation of strategies involved in multi-objective collaborative traffic flow management (CTFM). Intelligent...

  18. The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios.

    Science.gov (United States)

    Tian, Bin; Hou, Kun Mean; Zhou, Haiying

    2016-06-21

    The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination.

  19. The Traffic Adaptive Data Dissemination (TrAD Protocol for both Urban and Highway Scenarios

    Directory of Open Access Journals (Sweden)

    Bin Tian

    2016-06-01

    Full Text Available The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination.

  20. Smartphone Based Traffic Sign Inventory and Assessment.

    Science.gov (United States)

    2016-01-01

    Road signs are an important part of the infrastructure and are needed to ensure smooth and : safe traffic flow. Faded, occluded, damaged or vandalized signs can confuse or misinform : drivers and lead to unsafe driving behavior. E.g. if a driver is n...

  1. Impact of Different Spacing Policies for Adaptive Cruise Control on Traffic and Energy Consumption of Electric Vehicles

    OpenAIRE

    Bayar, Bilgehan; Sajadi Alamdari, Seyed Amin; Viti, Francesco; Voos, Holger

    2016-01-01

    This paper assesses the impact of different spacing policies for Adaptive Cruise Control (ACC) systems on traffic and environment. The largest deal of existing studies focus on assessing the performance in terms of safety, while only few deal with the effect of ACC on the traffic flow and the environment. In particular, very little is know on traffic stability and energy consumption. In this study, the vehicles equipped with ACC are modelled and controlled by two different spacing policies. B...

  2. Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm

    Directory of Open Access Journals (Sweden)

    Li Wang

    2017-01-01

    Full Text Available Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole.

  3. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    Directory of Open Access Journals (Sweden)

    Su Yang

    Full Text Available Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1 Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2 The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3 The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  4. Intelligent traffic lights based on MATLAB

    Science.gov (United States)

    Nie, Ying

    2018-04-01

    In this paper, I describes the traffic lights system and it has some. Through analysis, I used MATLAB technology, transformed the camera photographs into digital signals. Than divided the road vehicle is into three methods: very congestion, congestion, a little congestion. Through the MCU programming, solved the different roads have different delay time, and Used this method, saving time and resources, so as to reduce road congestion.

  5. Value of Information for Optimal Adaptive Routing in Stochastic Time-Dependent Traffic Networks: Algorithms and Computational Tools

    Science.gov (United States)

    2010-10-25

    Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...

  6. InSync Adaptive Traffic Control System for the Veterans Memorial Hwy Corridor on Long Island, NY

    Science.gov (United States)

    2012-08-01

    This report documents Rhythm Engineerings adaptive traffic control system field installation performed : by New York State Department of Transportation (NYSDOT) along Veterans Memorial Hwy in Long : Island, NY. This report reviews the reason for t...

  7. A safety assessment methodology applied to CNS/ATM-based air traffic control system

    Energy Technology Data Exchange (ETDEWEB)

    Vismari, Lucio Flavio, E-mail: lucio.vismari@usp.b [Safety Analysis Group (GAS), School of Engineering at University of Sao Paulo (Poli-USP), Av. Prof. Luciano Gualberto, Trav.3, n.158, Predio da Engenharia de Eletricidade, Sala C2-32, CEP 05508-900, Sao Paulo (Brazil); Batista Camargo Junior, Joao, E-mail: joaocamargo@usp.b [Safety Analysis Group (GAS), School of Engineering at University of Sao Paulo (Poli-USP), Av. Prof. Luciano Gualberto, Trav.3, n.158, Predio da Engenharia de Eletricidade, Sala C2-32, CEP 05508-900, Sao Paulo (Brazil)

    2011-07-15

    In the last decades, the air traffic system has been changing to adapt itself to new social demands, mainly the safe growth of worldwide traffic capacity. Those changes are ruled by the Communication, Navigation, Surveillance/Air Traffic Management (CNS/ATM) paradigm , based on digital communication technologies (mainly satellites) as a way of improving communication, surveillance, navigation and air traffic management services. However, CNS/ATM poses new challenges and needs, mainly related to the safety assessment process. In face of these new challenges, and considering the main characteristics of the CNS/ATM, a methodology is proposed at this work by combining 'absolute' and 'relative' safety assessment methods adopted by the International Civil Aviation Organization (ICAO) in ICAO Doc.9689 , using Fluid Stochastic Petri Nets (FSPN) as the modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed (in analysis) and the legacy system models. To demonstrate its usefulness, the proposed methodology was applied to the 'Automatic Dependent Surveillance-Broadcasting' (ADS-B) based air traffic control system. As conclusions, the proposed methodology assured to assess CNS/ATM system safety properties, in which FSPN formalism provides important modeling capabilities, and discrete event simulation allowing the estimation of the desired safety metric.

  8. A safety assessment methodology applied to CNS/ATM-based air traffic control system

    International Nuclear Information System (INIS)

    Vismari, Lucio Flavio; Batista Camargo Junior, Joao

    2011-01-01

    In the last decades, the air traffic system has been changing to adapt itself to new social demands, mainly the safe growth of worldwide traffic capacity. Those changes are ruled by the Communication, Navigation, Surveillance/Air Traffic Management (CNS/ATM) paradigm , based on digital communication technologies (mainly satellites) as a way of improving communication, surveillance, navigation and air traffic management services. However, CNS/ATM poses new challenges and needs, mainly related to the safety assessment process. In face of these new challenges, and considering the main characteristics of the CNS/ATM, a methodology is proposed at this work by combining 'absolute' and 'relative' safety assessment methods adopted by the International Civil Aviation Organization (ICAO) in ICAO Doc.9689 , using Fluid Stochastic Petri Nets (FSPN) as the modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed (in analysis) and the legacy system models. To demonstrate its usefulness, the proposed methodology was applied to the 'Automatic Dependent Surveillance-Broadcasting' (ADS-B) based air traffic control system. As conclusions, the proposed methodology assured to assess CNS/ATM system safety properties, in which FSPN formalism provides important modeling capabilities, and discrete event simulation allowing the estimation of the desired safety metric.

  9. Impact of Primary User Traffic on Adaptive Transmission for Cognitive Radio with Partial Relay Selection

    KAUST Repository

    Rao, Anlei

    2012-09-08

    In a cognitive relay system, the secondary user is permitted to transmit data via a relay when licensed frequency bands are detected to be free. Previous studies mainly focus on reducing or limiting the interference of the secondary transmission on the primary users. On the other hand, however, the primary user traffic will also affect the data transmission performance of the secondary users. In this paper, we investigate the impact of the primary user traffic on the bit error rate (BER) of the secondary transmission, when the secondary user adopts adaptive transmission with a relay partially selected. From the numerical results, we can see that the primary user traffic seriously degrades average BER. The worse-link partial selection can perform almost as well as the global selection when the channel conditions of the source-relay links and the relay-destination links differ a lot. In addition, although the relay selection improves the spectral efficiency of the secondary transmission, numerical results show that it only has slight impact on the overall average BER, so that the robustness of the system will not be affected by the relay selection.

  10. Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2012-01-01

    Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.

  11. Model-Based Traffic Control for Sustainable Mobility

    NARCIS (Netherlands)

    Zegeye, S.K.

    2011-01-01

    Computationally efficient dynamic fuel consumption, emissions, and dispersion of emissions models are developed. Fast and practically feasible model-based controller is proposed. Using the developed models, the controller steers the traffic flow in such a way that a balanced trade-off between the

  12. Speed-Density Model of Interrupted Traffic Flow Based on Coil Data

    Directory of Open Access Journals (Sweden)

    Chen Yu

    2016-01-01

    Full Text Available As a fundamental traffic diagram, the speed-density relationship can provide a solid foundation for traffic flow analysis and efficient traffic management. Because of the change in modern travel modes, the dramatic increase in the number of vehicles and traffic density, and the impact of traffic signals and other factors, vehicles change velocity frequently, which means that a speed-density model based on uninterrupted traffic flow is not suitable for interrupted traffic flow. Based on the coil data of urban roads in Wuhan, China, a new method which can accurately describe the speed-density relation of interrupted traffic flow is proposed for speed fluctuation characteristics. The model of upper and lower bounds of critical values obtained by fitting the data of the coils on urban roads can accurately and intuitively describe the state of urban road traffic, and the physical meaning of each parameter plays an important role in the prediction and analysis of such traffic.

  13. Transit Traffic Analysis Zone Delineating Method Based on Thiessen Polygon

    Directory of Open Access Journals (Sweden)

    Shuwei Wang

    2014-04-01

    Full Text Available A green transportation system composed of transit, busses and bicycles could be a significant in alleviating traffic congestion. However, the inaccuracy of current transit ridership forecasting methods is imposing a negative impact on the development of urban transit systems. Traffic Analysis Zone (TAZ delineating is a fundamental and essential step in ridership forecasting, existing delineating method in four-step models have some problems in reflecting the travel characteristics of urban transit. This paper aims to come up with a Transit Traffic Analysis Zone delineation method as supplement of traditional TAZs in transit service analysis. The deficiencies of current TAZ delineating methods were analyzed, and the requirements of Transit Traffic Analysis Zone (TTAZ were summarized. Considering these requirements, Thiessen Polygon was introduced into TTAZ delineating. In order to validate its feasibility, Beijing was then taken as an example to delineate TTAZs, followed by a spatial analysis of office buildings within a TTAZ and transit station departure passengers. Analysis result shows that the TTAZs based on Thiessen polygon could reflect the transit travel characteristic and is of in-depth research value.

  14. Obtaining Application-based and Content-based Internet Traffic Statistics

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Pedersen, Jens Myrup

    2012-01-01

    Understanding Internet traffic is crucial in order to facilitate academic research and practical network engineering, e.g. when doing traffic classification, prioritization of traffic, creating realistic scenarios and models for Internet traffic development etc. In this paper we demonstrate how...... the Volunteer-Based System for Research on the Internet, developed at Aalborg University, is capable of providing detailed statistics of Internet usage. Since an increasing amount of HTTP traffic has been observed during the last few years, the system also supports creating statistics of different kinds of HTTP...... be useful for studying characteristics of computer network traffic in application-oriented or content-type- oriented way, and is now ready for a larger-scale implementation. The paper is concluded with a discussion about various applications of the system and possibilities of further enhancement....

  15. Automated Video-Based Traffic Count Analysis.

    Science.gov (United States)

    2016-01-01

    The goal of this effort has been to develop techniques that could be applied to the : detection and tracking of vehicles in overhead footage of intersections. To that end we : have developed and published techniques for vehicle tracking based on dete...

  16. Automated Generation of Traffic Incident Response Plan Based on Case-Based Reasoning and Bayesian Theory

    Directory of Open Access Journals (Sweden)

    Yongfeng Ma

    2014-01-01

    Full Text Available Traffic incident response plan, specifying response agencies and their responsibilities, can guide responders to take actions effectively and timely after traffic incidents. With a reasonable and feasible traffic incident response plan, related agencies will save many losses, such as humans and wealth. In this paper, how to generate traffic incident response plan automatically and specially was solved. Firstly, a well-known and approved method, Case-Based Reasoning (CBR, was introduced. Based on CBR, a detailed case representation and R5-cycle of CBR were developed. To enhance the efficiency of case retrieval, which was an important procedure, Bayesian Theory was introduced. To measure the performance of the proposed method, 23 traffic incidents caused by traffic crashes were selected and three indicators, Precision P, Recall R, and Indicator F, were used. Results showed that 20 of 23 cases could be retrieved effectively and accurately. The method is practicable and accurate to generate traffic incident response plans. The method will promote the intelligent generation and management of traffic incident response plans and also make Traffic Incident Management more scientific and effective.

  17. Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior

    Science.gov (United States)

    Wedde, Horst F.; Lehnhoff, Sebastian; van Bonn, Bernhard; Bay, Z.; Becker, S.; Böttcher, S.; Brunner, C.; Büscher, A.; Fürst, T.; Lazarescu, A. M.; Rotaru, E.; Senge, S.; Steinbach, B.; Yilmaz, F.; Zimmermann, T.

    Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, to an extent where they make driving and transportation times largely unpredictable. Due to the highly dynamic character of congestion building and dissolving this phenomenon appears even to resist a formal treatment. Static approaches, and even more their global management, have proven counterproductive in practice. Given the latest progress in VANET technology and the remarkable commercially driven efforts like in the European C2C consortium, or the VSC Project in the US, allow meanwhile to tackle various aspects of traffic regulation through VANET communication. In this paper we introduce a novel, completely decentralized multi-agent routing algorithm (termed BeeJamA) which we have derived from the foraging behavior of honey bees. It is highly dynamic, adaptive, robust, and scalable, and it allows for both avoiding congestions, and minimizing traveling times to individual destinations. Vehicle guidance is provided well ahead of every intersection, depending on the individual speeds. Thus strict deadlines are imposed on, and respected by, the BeeJamA algorithm. We report on extensive simulation experiments which show the superior performance of BeeJamA over conventional approaches.

  18. Long-term high air pollution exposure induced metabolic adaptations in traffic policemen.

    Science.gov (United States)

    Tan, Chaochao; Wang, Yupeng; Lin, Mingyue; Wang, Zhu; He, Li; Li, Zhiyi; Li, Yu; Xu, Keqian

    2018-03-01

    To assess the adverse physiological changes induced by long-term exposure to PM2.5. Totally 183 traffic policemen and 88 office policemen as the control group, were enrolled in this study. The concentrations of PM2.5 in both the working places of traffic and office policemen were obtained. Detailed personal questionnaires and conventional laboratory tests including hematology, fasting blood glucose, blood lipids, liver, kidney, immunity and tumor-related markers were conducted on all participants of this study. A dose-response relationship between the FBG, HDL-c and CEA values and the PM2.5 exposure duration was observed. Multivariate analysis confirmed that one hour on duty outdoor per day for one year was associated with an increase in FBG of 0.005% (95% CI: 0.0004% to 0.009%), CEA of 0.012% (95% CI: 0.006% to 0.017%), and a decrease in HDL-C of 0.001% (95% CI: 0.00034% to 0.002%). Long-term high air pollution exposure may lead to metabolism adaptation and it is likely involved in the development of cardiovascular disease and diabetes mellitus. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. MIMO Lyapunov Theory-Based RBF Neural Classifier for Traffic Sign Recognition

    Directory of Open Access Journals (Sweden)

    King Hann Lim

    2012-01-01

    Full Text Available Lyapunov theory-based radial basis function neural network (RBFNN is developed for traffic sign recognition in this paper to perform multiple inputs multiple outputs (MIMO classification. Multidimensional input is inserted into RBF nodes and these nodes are linked with multiple weights. An iterative weight adaptation scheme is hence designed with regards to the Lyapunov stability theory to obtain a set of optimum weights. In the design, the Lyapunov function has to be well selected to construct an energy space with a single global minimum. Weight gain is formed later to obey the Lyapunov stability theory. Detail analysis and discussion on the proposed classifier’s properties are included in the paper. The performance comparisons between the proposed classifier and some existing conventional techniques are evaluated using traffic sign patterns. Simulation results reveal that our proposed system achieved better performance with lower number of training iterations.

  20. Influence of Intra-cell Traffic on the Output Power of Base Station in GSM

    Directory of Open Access Journals (Sweden)

    M. Mileusnic

    2014-06-01

    Full Text Available In this paper we analyze the influence of intracell traffic in a GSM cell on the base station output power. It is proved that intracell traffic increases this power. If offered traffic is small, the increase of output power is equal to the part of intracell traffic. When the offered traffic and, as the result, call loss increase, the increase of output power becomes less. The results of calculation are verified by the computer simulation of traffic process in the GSM cell. The calculation and the simulation consider the uniform distribution of mobile users in the cell, but the conclusions are of a general nature.

  1. Improved GIS-based Methods for Traffic Noise Impact Assessment

    DEFF Research Database (Denmark)

    Nielsen, Otto Anker; Bloch, Karsten Sand

    1996-01-01

    When vector-based GIS-packages are used for traffic noise impact assessments, the buffer-technique is usually employed for the study: 1. For each road segment buffer-zones representing different noise-intervals are generated, 2. The buffers from all road segments are smoothed together, and 3....... The number of buildings within the buffers are enumerated. This technique provides an inaccurate assessment of the noise diffusion since it does not correct for buildings barrier and reflection to noise. The paper presents the results from a research project where the traditional noise buffer technique...... was compared with a new method which includes these corrections. Both methods follow the Common Nordic Noise Calculation Model, although the traditional buffer technique ignores parts of the model. The basis for the work was a digital map of roads and building polygons, combined with a traffic- and road...

  2. Android-based E-Traffic law enforcement system in Surakarta City

    Science.gov (United States)

    Yulianto, Budi; Setiono

    2018-03-01

    The urban advancement is always overpowered by the increasing number of vehicles as the need for movement of people and goods. This can lead to traffic problems if there is no effort on the implementation of traffic management and engineering, and traffic law enforcement. In this case, the Government of Surakarta City has implemented various policies and regulations related to traffic management and engineering in order to run traffic in an orderly, safe and comfortable manner according to the applicable law. However, conditions in the field shows that traffic violations still occurred frequently due to the weakness of traffic law enforcement in terms of human resources and the system. In this connection, a tool is needed to support traffic law enforcement, especially in relation to the reporting system of traffic violations. This study aims to develop an Android-based traffic violations reporting application (E-Traffic Law Enforcement) as part of the traffic law enforcement system in Surakarta City. The Android-apps records the location and time of the traffic violations incident along with the visual evidence of the infringement. This information will be connected to the database system to detect offenders and to do the traffic law enforcement process.

  3. Trafficability Analysis at Traffic Crossing and Parameters Optimization Based on Particle Swarm Optimization Method

    Directory of Open Access Journals (Sweden)

    Bin He

    2014-01-01

    Full Text Available In city traffic, it is important to improve transportation efficiency and the spacing of platoon should be shortened when crossing the street. The best method to deal with this problem is automatic control of vehicles. In this paper, a mathematical model is established for the platoon’s longitudinal movement. A systematic analysis of longitudinal control law is presented for the platoon of vehicles. However, the parameter calibration for the platoon model is relatively difficult because the platoon model is complex and the parameters are coupled with each other. In this paper, the particle swarm optimization method is introduced to effectively optimize the parameters of platoon. The proposed method effectively finds the optimal parameters based on simulations and makes the spacing of platoon shorter.

  4. Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

    Science.gov (United States)

    Chen, Caixia; Shi, Chun

    2018-03-01

    Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

  5. TRAFFIC SIGN DETECTION BASED ON BIOLOGICALLY VISUAL MECHANISM

    Directory of Open Access Journals (Sweden)

    X. Hu

    2012-07-01

    Full Text Available TSR (Traffic sign recognition is an important problem in ITS (intelligent traffic system, which is being paid more and more attention for realizing drivers assisting system and unmanned vehicle etc. TSR consists of two steps: detection and recognition, and this paper describe a new traffic sign detection method. The design principle of the traffic sign is comply with the visual attention mechanism of human, so we propose a method using visual attention mechanism to detect traffic sign ,which is reasonable. In our method, the whole scene will firstly be analyzed by visual attention model to acquire the area where traffic signs might be placed. And then, these candidate areas will be analyzed according to the shape characteristics of the traffic sign to detect traffic signs. In traffic sign detection experiments, the result shows the proposed method is effectively and robust than other existing saliency detection method.

  6. Adaptive Load Balancing Strategy Based on LVS

    OpenAIRE

    Fu Chen; Zhang Li-Jun

    2017-01-01

    Linux Virtual Server (LVS) is a load balancing server that deployed on a cluster of real servers and the load balancer running on the Linux operating system. In the scheduling module, we designed an adaptive load balancing strategy. Firstly, we introduce the traffic state prediction. The algorithm we choose is Radial Basis Function (RBF) neural network. Secondly, we update weights according to the real-time usage of CPU, memory and hard disk. Then we conduct a series of experiments and the ad...

  7. Dynamic traffic assignment based trailblazing guide signing for major traffic generator.

    Science.gov (United States)

    2009-11-01

    The placement of guide signs and the display of dynamic massage signs greatly affect drivers : understanding of the network and therefore their route choices. Most existing dynamic traffic assignment : models assume that drivers heading to a Major...

  8. Adaptive Load Balancing Strategy Based on LVS

    Directory of Open Access Journals (Sweden)

    Fu Chen

    2017-01-01

    Full Text Available Linux Virtual Server (LVS is a load balancing server that deployed on a cluster of real servers and the load balancer running on the Linux operating system. In the scheduling module, we designed an adaptive load balancing strategy. Firstly, we introduce the traffic state prediction. The algorithm we choose is Radial Basis Function (RBF neural network. Secondly, we update weights according to the real-time usage of CPU, memory and hard disk. Then we conduct a series of experiments and the adaptive strategies have a better performance on load balancing.

  9. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

    Directory of Open Access Journals (Sweden)

    Shouyi Yin

    2015-01-01

    Full Text Available Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

  10. Fast traffic sign recognition with a rotation invariant binary pattern based feature.

    Science.gov (United States)

    Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

    2015-01-19

    Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

  11. An efficient statistical-based approach for road traffic congestion monitoring

    KAUST Repository

    Abdelhafid, Zeroual

    2017-12-14

    In this paper, we propose an effective approach which has to detect traffic congestion. The detection strategy is based on the combinational use of piecewise switched linear traffic (PWSL) model with exponentially-weighted moving average (EWMA) chart. PWSL model describes traffic flow dynamics. Then, PWSL residuals are used as the input of EWMA chart to detect traffic congestions. The evaluation results of the developed approach using data from a portion of the I210-W highway in Califorina showed the efficiency of the PWSL-EWMA approach in in detecting traffic congestions.

  12. Effect of adaptive cruise control systems on mixed traffic flow near an on-ramp

    Science.gov (United States)

    Davis, L. C.

    2007-06-01

    Mixed traffic flow consisting of vehicles equipped with adaptive cruise control (ACC) and manually driven vehicles is analyzed using car-following simulations. Simulations of merging from an on-ramp onto a freeway reported in the literature have not thus far demonstrated a substantial positive impact of ACC. In this paper cooperative merging for ACC vehicles is proposed to improve throughput and increase distance traveled in a fixed time. In such a system an ACC vehicle senses not only the preceding vehicle in the same lane but also the vehicle immediately in front in the other lane. Prior to reaching the merge region, the ACC vehicle adjusts its velocity to ensure that a safe gap for merging is obtained. If on-ramp demand is moderate, cooperative merging produces significant improvement in throughput (20%) and increases up to 3.6 km in distance traveled in 600 s for 50% ACC mixed flow relative to the flow of all-manual vehicles. For large demand, it is shown that autonomous merging with cooperation in the flow of all ACC vehicles leads to throughput limited only by the downstream capacity, which is determined by speed limit and headway time.

  13. A knowledge-based system for controlling automobile traffic

    Science.gov (United States)

    Maravas, Alexander; Stengel, Robert F.

    1994-01-01

    Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

  14. Grazing Soybean to Increase Voluntary Cow Traffic in a Pasture-based Automatic Milking System

    Directory of Open Access Journals (Sweden)

    C. E. F. Clark

    2014-03-01

    Full Text Available Pasture-based automatic milking systems (AMS require cow traffic to enable cows to be milked. The interval between milkings can be manipulated by strategically allocating pasture. The current experiment investigated the effect of replacing an allocation of grazed pasture with grazed soybean (Glycine max with the hypothesis that incorporating soybean would increase voluntary cow traffic and milk production. One hundred and eighty mixed age, primiparous and multiparous Holstein-Friesian/Illawarra cows were randomly assigned to two treatment groups (n = 90/group with a 2×2 Latin square design. Each group was either offered treatments of kikuyu grass (Pennisetum clandestinum Hoach ex Chiov. pasture (pasture or soybean from 0900 h to 1500 h during the experimental period which consisted of 2 periods of 3 days following 5 days of training and adaptation in each period with groups crossing over treatments after the first period. The number of cows trafficking to each treatment was similar together with milk yield (mean ≈18 L/cow/d in this experiment. For the cows that arrived at soybean or pasture there were significant differences in their behaviour and consequently the number of cows exiting each treatment paddock. There was greater cow traffic (more cows and sooner exiting pasture allocations. Cows that arrived at soybean stayed on the allocation for 25% more time and ate more forage (8.5 kg/cow/d/allocation relative to pasture (4.7 kg/cow/d/allocation. Pasture cows predominantly replaced eating time with rumination. These findings suggest that replacing pasture with alternative grazeable forages provides no additional incentive to increase voluntary cow traffic to an allocation of feed in AMS. This work highlights the opportunity to increase forage intakes in AMS through the incorporation of alternative forages.

  15. FPGA Based Real-time Network Traffic Analysis using Traffic Dispersion Patterns

    Energy Technology Data Exchange (ETDEWEB)

    Khan, F; Gokhale, M; Chuah, C N

    2010-03-26

    The problem of Network Traffic Classification (NTC) has attracted significant amount of interest in the research community, offering a wide range of solutions at various levels. The core challenge is in addressing high amounts of traffic diversity found in today's networks. The problem becomes more challenging if a quick detection is required as in the case of identifying malicious network behavior or new applications like peer-to-peer traffic that have potential to quickly throttle the network bandwidth or cause significant damage. Recently, Traffic Dispersion Graphs (TDGs) have been introduced as a viable candidate for NTC. The TDGs work by forming a network wide communication graphs that embed characteristic patterns of underlying network applications. However, these patterns need to be quickly evaluated for mounting real-time response against them. This paper addresses these concerns and presents a novel solution for real-time analysis of Traffic Dispersion Metrics (TDMs) in the TDGs. We evaluate the dispersion metrics of interest and present a dedicated solution on an FPGA for their analysis. We also present analytical measures and empirically evaluate operating effectiveness of our design. The mapped design on Virtex-5 device can process 7.4 million packets/second for a TDG comprising of 10k flows at very high accuracies of over 96%.

  16. Traffic sign recognition based on deep convolutional neural network

    Science.gov (United States)

    Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan

    2017-11-01

    Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.

  17. TRAFFIC SIMULATION FOR MIXED TRAFFIC SYSTEMS

    African Journals Online (AJOL)

    EGETE

    2012-05-04

    2002). Description of a microscopic traffic model of an urban district and the analysis and problem solving traffic congestion based on actual data is its objective. There suggested models for a vehicular traffic flow based on partial ...

  18. Multiscale based adaptive contrast enhancement

    Science.gov (United States)

    Abir, Muhammad; Islam, Fahima; Wachs, Daniel; Lee, Hyoung

    2013-02-01

    A contrast enhancement algorithm is developed for enhancing the contrast of x-ray images. The algorithm is based on Laplacian pyramid image processing technique. The image is decomposed into three frequency sub-bands- low, medium, and high. Each sub-band contains different frequency information of the image. The detail structure of the image lies on the high frequency sub-band and the overall structure lies on the low frequency sub-band. Apparently it is difficult to extract detail structure from the high frequency sub-bands. Enhancement of the detail structures is necessary in order to find out the calcifications on the mammograms, cracks on any object such as fuel plate, etc. In our proposed method contrast enhancement is achieved from high and medium frequency sub-band images by decomposing the image based on multi-scale Laplacian pyramid and enhancing contrast by suitable image processing. Standard Deviation-based Modified Adaptive contrast enhancement (SDMACE) technique is applied to enhance the low-contrast information on the sub-bands without overshooting noise. An alpha-trimmed mean filter is used in SDMACE for sharpness enhancement. After modifying all sub-band images, the final image is derived from reconstruction of the sub-band images from lower resolution level to upper resolution level including the residual image. To demonstrate the effectiveness of the algorithm an x-ray of a fuel plate and two mammograms are analyzed. Subjective evaluation is performed to evaluate the effectiveness of the algorithm. The proposed algorithm is compared with the well-known contrast limited adaptive histogram equalization (CLAHE) algorithm. Experimental results prove that the proposed algorithm offers improved contrast of the x-ray images.

  19. Road traffic management based on self-load-balancing approach

    Directory of Open Access Journals (Sweden)

    Adnane Ahmed

    2016-01-01

    Full Text Available Traffic congestion is one of the most challenging problems for nowadays cities. Several contributions mainly based on V2V (Vehicle-to-Vehicle communication have been published, but most of them have never been applied due to their communication related problems and costs. In this article, a novel cost-effective approach is introduced inspired by social life of insects where direct (V2V communication does not exist anymore. Vehicles are equipped with devices that perform simple tasks, but their interactions with the environment through RSUs (Road Side Units allow the creation of an intelligence which notifies drivers about congested road segments to avoid them. We call this emerging behavior self-load balancing. Description of the fundamentals of this approach and its performance are detailed in this work.

  20. An approach of traffic signal control based on NLRSQP algorithm

    Science.gov (United States)

    Zou, Yuan-Yang; Hu, Yu

    2017-11-01

    This paper presents a linear program model with linear complementarity constraints (LPLCC) to solve traffic signal optimization problem. The objective function of the model is to obtain the minimization of total queue length with weight factors at the end of each cycle. Then, a combination algorithm based on the nonlinear least regression and sequence quadratic program (NLRSQP) is proposed, by which the local optimal solution can be obtained. Furthermore, four numerical experiments are proposed to study how to set the initial solution of the algorithm that can get a better local optimal solution more quickly. In particular, the results of numerical experiments show that: The model is effective for different arrival rates and weight factors; and the lower bound of the initial solution is, the better optimal solution can be obtained.

  1. An RFID-based intelligent vehicle speed controller using active traffic signals.

    Science.gov (United States)

    Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C; de Pedro, Teresa

    2010-01-01

    These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver's attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results.

  2. An RFID-Based Intelligent Vehicle Speed Controller Using Active Traffic Signals

    Science.gov (United States)

    Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C.; de Pedro, Teresa

    2010-01-01

    These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver’s attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results. PMID:22219692

  3. An RFID-Based Intelligent Vehicle Speed Controller Using Active Traffic Signals

    Directory of Open Access Journals (Sweden)

    Joshué Pérez

    2010-06-01

    Full Text Available These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS. One prime example of ITS is vehicle Cruise Control (CC, which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver’s attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results.

  4. Feedback in Videogame-Based Adaptive Training

    Science.gov (United States)

    Rivera, Iris Daliz

    2010-01-01

    The field of training has been changing rapidly due to advances in technology such as videogame-based adaptive training. Videogame-based adaptive training has provided flexibility and adaptability for training in cost-effective ways. Although this method of training may have many benefits for the trainee, current research has not kept up to pace…

  5. A Method Based on Dial's Algorithm for Multi-time Dynamic Traffic Assignment

    Directory of Open Access Journals (Sweden)

    Rongjie Kuang

    2014-03-01

    Full Text Available Due to static traffic assignment has poor performance in reflecting actual case and dynamic traffic assignment may incurs excessive compute cost, method of multi-time dynamic traffic assignment combining static and dynamic traffic assignment balances factors of precision and cost effectively. A method based on Dial's logit algorithm is proposed in the article to solve the dynamic stochastic user equilibrium problem in dynamic traffic assignment. Before that, a fitting function that can proximately reflect overloaded traffic condition of link is proposed and used to give corresponding model. Numerical example is given to illustrate heuristic procedure of method and to compare results with one of same example solved by other literature's algorithm. Results show that method based on Dial's algorithm is preferable to algorithm from others.

  6. Roads and traffic: Effects on ecology and wildlife habitat use; applications for cooperative adaptive management

    Science.gov (United States)

    Ouren, Douglas S.; Watts, Raymond D.

    2005-01-01

    The land of the United States in dissected by more than 4 million miles of roads that fragment wildlife habitat on both public and private lands. Traffic on these roads causes additional effects. On secondary roads, which provide access to the most natural habitat, the levels, timing, and types of traffic are seldom known. In order to understand the effects of traffic on wildlife, USGS is conducting research cooperatively with the Bureau of Land Management, the U.S. Forest Service, the National Park Service, and the Colorado Division of Wildlife.

  7. Traffic Sign Recognition System based on Cambridge Correlator Image Comparator

    Directory of Open Access Journals (Sweden)

    J. Turan

    2012-06-01

    Full Text Available Paper presents basic information about application of Optical Correlator (OC, specifically Cambridge Correlator, in system to recognize of traffic sign. Traffic Sign Recognition System consists of three main blocks, Preprocessing, Optical Correlator and Traffic Sign Identification. The Region of Interest (ROI is defined and chosen in preprocessing block and then goes to Optical Correlator, where is compared with database of Traffic Sign. Output of Optical Correlation is correlation plane, which consist of highly localized intensities, know as correlation peaks. The intensity of spots provides a measure of similarity and position of spots, how images (traffic signs are relatively aligned in the input scene. Several experiments have been done with proposed system and results and conclusion are discussed.

  8. TrAD: Traffic Adaptive Data Dissemination Protocol for Both Urban and Highway VANETs

    OpenAIRE

    Tian, Bin; Hou, K.M.; LI, Jianjin

    2016-01-01

    Accepted by the 30-th IEEE International Conference on Advanced Information Networking and Applications (AINA-2016); Vehicular Ad hoc Networks (VANETs) aim to improve transportation activities that include traffic safety, transport efficiency and even infotainment on the wheels, in which a great number of traffic event-driven messages are needed to disseminate in a region of interest timely. However, due to the nature of VANETs, highly dynamic mobility and frequent disconnection, data dissemi...

  9. Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

    Science.gov (United States)

    Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin

    As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.

  10. Adaptation-Based Programming in Haskell

    Directory of Open Access Journals (Sweden)

    Tim Bauer

    2011-09-01

    Full Text Available We present an embedded DSL to support adaptation-based programming (ABP in Haskell. ABP is an abstract model for defining adaptive values, called adaptives, which adapt in response to some associated feedback. We show how our design choices in Haskell motivate higher-level combinators and constructs and help us derive more complicated compositional adaptives. We also show an important specialization of ABP is in support of reinforcement learning constructs, which optimize adaptive values based on a programmer-specified objective function. This permits ABP users to easily define adaptive values that express uncertainty anywhere in their programs. Over repeated executions, these adaptive values adjust to more efficient ones and enable the user's programs to self optimize. The design of our DSL depends significantly on the use of type classes. We will illustrate, along with presenting our DSL, how the use of type classes can support the gradual evolution of DSLs.

  11. Traffic conflict assessment for non-lane-based movements of motorcycles under congested conditions

    Directory of Open Access Journals (Sweden)

    Long Xuan Nguyen

    2014-03-01

    Full Text Available Traffic conflict under congested conditions is one of the main safety issues of motorcycle traffic in developing countries. Unlike cars, motorcycles often display non-lane-based movements such as swerving or oblique following of a lead vehicle when traffic becomes congested. Very few studies have quantitatively evaluated the effects of such non-lane-based movements on traffic conflict. Therefore, in this study we aim to develop an integrated model to assess the traffic conflict of motorcycles under congested conditions. The proposed model includes a concept of safety space to describe the non-lane-based movements unique to motorcycles, new features developed for traffic conflict assessment such as parameters of acceleration and deceleration, and the conditions for choosing a lead vehicle. Calibration data were extracted from video clips taken at two road segments in Ho Chi Minh City. A simulation based on the model was developed to verify the dynamic non-lane-based movements of motorcycles. Subsequently, the assessment of traffic conflict was validated by calculating the probability of sudden braking at each time interval according to the change in the density of motorcycle flow. Our findings underscore the fact that higher flow density may lead to conflicts associated with a greater probability of sudden breaking. Three types of motorcycle traffic conflicts were confirmed, and the proportions of each type were calculated and discussed.

  12. Shadow-Based Vehicle Detection in Urban Traffic

    Directory of Open Access Journals (Sweden)

    Manuel Ibarra-Arenado

    2017-04-01

    Full Text Available Vehicle detection is a fundamental task in Forward Collision Avoiding Systems (FACS. Generally, vision-based vehicle detection methods consist of two stages: hypotheses generation and hypotheses verification. In this paper, we focus on the former, presenting a feature-based method for on-road vehicle detection in urban traffic. Hypotheses for vehicle candidates are generated according to the shadow under the vehicles by comparing pixel properties across the vertical intensity gradients caused by shadows on the road, and followed by intensity thresholding and morphological discrimination. Unlike methods that identify the shadow under a vehicle as a road region with intensity smaller than a coarse lower bound of the intensity for road, the thresholding strategy we propose determines a coarse upper bound of the intensity for shadow which reduces false positives rates. The experimental results are promising in terms of detection performance and robustness in day time under different weather conditions and cluttered scenarios to enable validation for the first stage of a complete FACS.

  13. Traffic Command Gesture Recognition for Virtual Urban Scenes Based on a Spatiotemporal Convolution Neural Network

    Directory of Open Access Journals (Sweden)

    Chunyong Ma

    2018-01-01

    Full Text Available Intelligent recognition of traffic police command gestures increases authenticity and interactivity in virtual urban scenes. To actualize real-time traffic gesture recognition, a novel spatiotemporal convolution neural network (ST-CNN model is presented. We utilized Kinect 2.0 to construct a traffic police command gesture skeleton (TPCGS dataset collected from 10 volunteers. Subsequently, convolution operations on the locational change of each skeletal point were performed to extract temporal features, analyze the relative positions of skeletal points, and extract spatial features. After temporal and spatial features based on the three-dimensional positional information of traffic police skeleton points were extracted, the ST-CNN model classified positional information into eight types of Chinese traffic police gestures. The test accuracy of the ST-CNN model was 96.67%. In addition, a virtual urban traffic scene in which real-time command tests were carried out was set up, and a real-time test accuracy rate of 93.0% was achieved. The proposed ST-CNN model ensured a high level of accuracy and robustness. The ST-CNN model recognized traffic command gestures, and such recognition was found to control vehicles in virtual traffic environments, which enriches the interactive mode of the virtual city scene. Traffic command gesture recognition contributes to smart city construction.

  14. An Imputation Method for Missing Traffic Data Based on FCM Optimized by PSO-SVR

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    2018-01-01

    Full Text Available Missing traffic data are inevitable due to detector failure or communication failure. Currently, most of imputation methods estimated the missing traffic values by using spatial-temporal information as much as possible. However, it ignores an important fact that spatial-temporal information of the traffic missing data is often incomplete and unavailable. Moreover, most of the existing methods are verified by traffic data from freeway, and their applicability to urban road data needs to be further verified. In this paper, a hybrid method for missing traffic data imputation is proposed using FCM optimized by a combination of PSO algorithm and SVR. In this method, FCM is the basic algorithm and the parameters of FCM are optimized. Firstly, the patterns of missing traffic data are analyzed and the representation of missing traffic data is given using matrix-based data structure. Then, traffic data from urban expressway and urban arterial road are used to analyze spatial-temporal correlation of the traffic data for the determination of the proposed method input. Finally, numerical experiment is designed from three perspectives to test the performance of the proposed method. The experimental results demonstrate that the novel method not only has high imputation precision, but also exhibits good robustness.

  15. Smart Traffic Management Protocol Based on VANET architecture

    Directory of Open Access Journals (Sweden)

    Amilcare Francesco Santamaria

    2014-01-01

    Full Text Available Nowadays one of the hottest theme in wireless environments research is the application of the newest technologies to road safety problems and traffic management exploiting the (VANET architecture. In this work, a novel protocol that aims to achieve a better traffic management is proposed. The overal system is able to reduce traffic level inside the city exploiting inter-communication among vehicles and support infrastructures also known as (V2V and (V2I communications. We design a network protocol called (STMP that takes advantages of IEEE 802.11p standard. On each road several sensors system are placed and they are responsible of monitoring. Gathered data are spread in the network exploiting ad-hoc protocol messages. The increasing knowledge about environment conditions make possible to take preventive actions. Moreover, having a realtime monitoring of the lanes it is possible to reveal roads and city blocks congestions in a shorter time. An external entity to the (VANET is responsible to manage traffic and rearrange traffic along the lanes of the city avoiding huge traffic levels.

  16. A video-based real-time adaptive vehicle-counting system for urban roads.

    Directory of Open Access Journals (Sweden)

    Fei Liu

    Full Text Available In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.

  17. Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads

    Directory of Open Access Journals (Sweden)

    Goran Petrovic

    2012-03-01

    Full Text Available Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications and UMTS (Universal Mobile Telecommunications System base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

  18. mBm-Based Scalings of Traffic Propagated in Internet

    Directory of Open Access Journals (Sweden)

    Ming Li

    2011-01-01

    Full Text Available Scaling phenomena of the Internet traffic gain people's interests, ranging from computer scientists to statisticians. There are two types of scales. One is small-time scaling and the other large-time one. Tools to separately describe them are desired in computer communications, such as performance analysis of network systems. Conventional tools, such as the standard fractional Brownian motion (fBm, or its increment process, or the standard multifractional fBm (mBm indexed by the local Hölder function H(t may not be enough for this purpose. In this paper, we propose to describe the local scaling of traffic by using D(t on a point-by-point basis and to measure the large-time scaling of traffic by using E[H(t] on an interval-by-interval basis, where E implies the expectation operator. Since E[H(t] is a constant within an observation interval while D(t is random in general, they are uncorrelated with each other. Thus, our proposed method can be used to separately characterize the small-time scaling phenomenon and the large one of traffic, providing a new tool to investigate the scaling phenomena of traffic.

  19. Adaptation and beyond: Lessons from community based adaptation ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    25 avr. 2016 ... Community based adaptation puts people at the centre of their own development. It is not just about responding to climate shocks, but is a learning process that empowers communities to solve problems and plan for climate events. Without underestimating the severity of climate change, this approach ...

  20. Discovering urban mobility patterns with PageRank based traffic modeling and prediction

    Science.gov (United States)

    Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

    2017-11-01

    Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.

  1. Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

    KAUST Repository

    Canepa, Edward S.

    2013-09-01

    Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill- Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offliine. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © American Institute of Mathematical Sciences.

  2. Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

    KAUST Repository

    Canepa, Edward S.

    2013-01-01

    Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. We use this fact to pose the problem of detecting spoofing cyber-attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber-attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © 2013 IEEE.

  3. RAIL TRAFFIC VOLUME ESTIMATION BASED ON WORLD DEVELOPMENT INDICATORS

    Directory of Open Access Journals (Sweden)

    Luka Lazarević

    2015-08-01

    Full Text Available European transport policy, defined in the White Paper, supports shift from road to rail and waterborne transport. The hypothesis of the paper is that changes in the economic environment influence rail traffic volume. Therefore, a model for prediction of rail traffic volume applied in different economic contexts could be a valuable tool for the transport planners. The model was built using common Machine Learning techniques that learn from the past experience. In the model preparation, world development indicators defined by the World Bank were used as input parameters.

  4. Intelligent vehicle based traffic monitoring – exploring application in South Africa

    CSIR Research Space (South Africa)

    Labuschagne, FJJ

    2010-08-01

    Full Text Available The paper details the anticipated benefits of an intelligent vehicle based traffic monitoring approach holds. The approach utilises advanced technology with the potential to reduce crashes and includes the monitor of vehicle speeds and flows...

  5. Agent-based traffic management and reinforcement learning in congested intersection network.

    Science.gov (United States)

    2012-08-01

    This study evaluates the performance of traffic control systems based on reinforcement learning (RL), also called approximate dynamic programming (ADP). Two algorithms have been selected for testing: 1) Q-learning and 2) approximate dynamic programmi...

  6. Intelligent Control in Automation Based on Wireless Traffic Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kurt Derr; Milos Manic

    2007-08-01

    Wireless technology is a central component of many factory automation infrastructures in both the commercial and government sectors, providing connectivity among various components in industrial realms (distributed sensors, machines, mobile process controllers). However wireless technologies provide more threats to computer security than wired environments. The advantageous features of Bluetooth technology resulted in Bluetooth units shipments climbing to five million per week at the end of 2005 [1, 2]. This is why the real-time interpretation and understanding of Bluetooth traffic behavior is critical in both maintaining the integrity of computer systems and increasing the efficient use of this technology in control type applications. Although neuro-fuzzy approaches have been applied to wireless 802.11 behavior analysis in the past, a significantly different Bluetooth protocol framework has not been extensively explored using this technology. This paper presents a new neurofuzzy traffic analysis algorithm of this still new territory of Bluetooth traffic. Further enhancements of this algorithm are presented along with the comparison against the traditional, numerical approach. Through test examples, interesting Bluetooth traffic behavior characteristics were captured, and the comparative elegance of this computationally inexpensive approach was demonstrated. This analysis can be used to provide directions for future development and use of this prevailing technology in various control type applications, as well as making the use of it more secure.

  7. Intelligent Control in Automation Based on Wireless Traffic Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kurt Derr; Milos Manic

    2007-09-01

    Wireless technology is a central component of many factory automation infrastructures in both the commercial and government sectors, providing connectivity among various components in industrial realms (distributed sensors, machines, mobile process controllers). However wireless technologies provide more threats to computer security than wired environments. The advantageous features of Bluetooth technology resulted in Bluetooth units shipments climbing to five million per week at the end of 2005 [1, 2]. This is why the real-time interpretation and understanding of Bluetooth traffic behavior is critical in both maintaining the integrity of computer systems and increasing the efficient use of this technology in control type applications. Although neuro-fuzzy approaches have been applied to wireless 802.11 behavior analysis in the past, a significantly different Bluetooth protocol framework has not been extensively explored using this technology. This paper presents a new neurofuzzy traffic analysis algorithm of this still new territory of Bluetooth traffic. Further enhancements of this algorithm are presented along with the comparison against the traditional, numerical approach. Through test examples, interesting Bluetooth traffic behavior characteristics were captured, and the comparative elegance of this computationally inexpensive approach was demonstrated. This analysis can be used to provide directions for future development and use of this prevailing technology in various control type applications, as well as making the use of it more secure.

  8. Pattern-based approach for logical traffic isolation forensic modelling

    CSIR Research Space (South Africa)

    Dlamini, I

    2009-08-01

    Full Text Available reusability and flexibility of the LTI model. This model is viewed as a three-tier architecture, which for experimental purposes is composed of the following components: traffic generator, DiffServ network and the sink server. The Mediator pattern is used...

  9. IPTV traffic management using topology-based hierarchical scheduling in Carrier Ethernet transport networks

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    of Service (QoS) provisioning abilities, which guarantee end-to-end performances of voice, video and data traffic delivered over networks. This paper introduces a topology-based hierarchical scheduler scheme, which controls the incoming traffic at the edge of the network based on the network topology....... This work has been carried out as a part of the research project HIPT (High quality IP network for IPTV and VoIP) founded by Danish Advanced Technology Foundation....

  10. Efficient graph-based dynamic load-balancing for parallel large-scale agent-based traffic simulation

    NARCIS (Netherlands)

    Xu, Y.; Cai, W.; Aydt, H.; Lees, M.; Tolk, A.; Diallo, S.Y.; Ryzhov, I.O.; Yilmaz, L.; Buckley, S.; Miller, J.A.

    2014-01-01

    One of the issues of parallelizing large-scale agent-based traffic simulations is partitioning and load-balancing. Traffic simulations are dynamic applications where the distribution of workload in the spatial domain constantly changes. Dynamic load-balancing at run-time has shown better efficiency

  11. A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

    Directory of Open Access Journals (Sweden)

    Yiliang Zeng

    2014-01-01

    Full Text Available A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

  12. An Efficient MapReduce-Based Parallel Clustering Algorithm for Distributed Traffic Subarea Division

    Directory of Open Access Journals (Sweden)

    Dawen Xia

    2015-01-01

    Full Text Available Traffic subarea division is vital for traffic system management and traffic network analysis in intelligent transportation systems (ITSs. Since existing methods may not be suitable for big traffic data processing, this paper presents a MapReduce-based Parallel Three-Phase K-Means (Par3PKM algorithm for solving traffic subarea division problem on a widely adopted Hadoop distributed computing platform. Specifically, we first modify the distance metric and initialization strategy of K-Means and then employ a MapReduce paradigm to redesign the optimized K-Means algorithm for parallel clustering of large-scale taxi trajectories. Moreover, we propose a boundary identifying method to connect the borders of clustering results for each cluster. Finally, we divide traffic subarea of Beijing based on real-world trajectory data sets generated by 12,000 taxis in a period of one month using the proposed approach. Experimental evaluation results indicate that when compared with K-Means, Par2PK-Means, and ParCLARA, Par3PKM achieves higher efficiency, more accuracy, and better scalability and can effectively divide traffic subarea with big taxi trajectory data.

  13. A novel multisensor traffic state assessment system based on incomplete data.

    Science.gov (United States)

    Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

    2014-01-01

    A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

  14. Density-Based Statistical Clustering: Enabling Sidefire Ultrasonic Traffic Sensing in Smart Cities

    Directory of Open Access Journals (Sweden)

    Volker Lücken

    2018-01-01

    Full Text Available Traffic routing is a central challenge in the context of urban areas, with a direct impact on personal mobility, traffic congestion, and air pollution. In the last decade, the possibilities for traffic flow control have improved together with the corresponding management systems. However, the lack of real-time traffic flow information with a city-wide coverage is a major limiting factor for an optimum operation. Smart City concepts seek to tackle these challenges in the future by combining sensing, communications, distributed information, and actuation. This paper presents an integrated approach that combines smart street lamps with traffic sensing technology. More specifically, infrastructure-based ultrasonic sensors, which are deployed together with a street light system, are used for multilane traffic participant detection and classification. Application of these sensors in time-varying reflective environments posed an unresolved problem for many ultrasonic sensing solutions in the past and therefore widely limited the dissemination of this technology. We present a solution using an algorithmic approach that combines statistical standardization with clustering techniques from the field of unsupervised learning. By using a multilevel communication concept, centralized and decentralized traffic information fusion is possible. The evaluation is based on results from automotive test track measurements and several European real-world installations.

  15. Understanding structure of urban traffic network based on spatial-temporal correlation analysis

    Science.gov (United States)

    Yang, Yanfang; Jia, Limin; Qin, Yong; Han, Shixiu; Dong, Honghui

    2017-08-01

    Understanding the structural characteristics of urban traffic network comprehensively can provide references for improving road utilization rate and alleviating traffic congestion. This paper focuses on the spatial-temporal correlations between different pairs of traffic series and proposes a complex network-based method of constructing the urban traffic network. In the network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding spatial-temporal correlation. Further, a modified PageRank algorithm, named the geographical weight-based PageRank algorithm (GWPA), is proposed to analyze the spatial distribution of important segments in the road network. Finally, experiments are conducted by using three kinds of traffic series collected from the urban road network in Beijing. Experimental results show that the urban traffic networks constructed by three traffic variables all indicate both small-world and scale-free characteristics. Compared with the results of PageRank algorithm, GWPA is proved to be valid in evaluating the importance of segments and identifying the important segments with small degree.

  16. A new smart traffic monitoring method using embedded cement-based piezoelectric sensors

    International Nuclear Information System (INIS)

    Zhang, Jinrui; Lu, Youyuan; Lu, Zeyu; Liu, Chao; Sun, Guoxing; Li, Zongjin

    2015-01-01

    Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel’s integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h −1 to 70 km h −1 , the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement. (paper)

  17. Knowledge-based driver assistance systems traffic situation description and situation feature relevance

    CERN Document Server

    Huelsen, Michael

    2014-01-01

    The comprehension of a traffic situation plays a major role in driving a vehicle. Interpretable information forms a basis for future projection, decision making and action performing, such as navigating, maneuvering and driving control. Michael Huelsen provides an ontology-based generic traffic situation description capable of supplying various advanced driver assistance systems with relevant information about the current traffic situation of a vehicle and its environment. These systems are enabled to perform reasonable actions and approach visionary goals such as injury and accident free driv

  18. Actual situation analyses of rat-run traffic on community streets based on car probe data

    Science.gov (United States)

    Sakuragi, Yuki; Matsuo, Kojiro; Sugiki, Nao

    2017-10-01

    Lowering of so-called "rat-run" traffic on community streets has been one of significant challenges for improving the living environment of neighborhood. However, it has been difficult to quantitatively grasp the actual situation of rat-run traffic by the traditional surveys such as point observations. This study aims to develop a method for extracting rat-run traffic based on car probe data. In addition, based on the extracted rat-run traffic in Toyohashi city, Japan, we try to analyze the actual situation such as time and location distribution of the rat-run traffic. As a result, in Toyohashi city, the rate of using rat-run route increases in peak time period. Focusing on the location distribution of rat-run traffic, in addition, they pass through a variety of community streets. There is no great inter-district bias of the route frequently used as rat-run traffic. Next, we focused on some trips passing through a heavily used route as rat-run traffic. As a result, we found the possibility that they habitually use the route as rat-run because their trips had some commonalities. We also found that they tend to use the rat-run route due to shorter distance than using the alternative highway route, and that the travel speeds were faster than using the alternative highway route. In conclusions, we confirmed that the proposed method can quantitatively grasp the actual situation and the phenomenal tendencies of the rat-run traffic.

  19. Drawing for Traffic Marking Using Bidirectional Gradient-Based Detection with MMS LIDAR Intensity

    Science.gov (United States)

    Takahashi, G.; Takeda, H.; Nakamura, K.

    2016-06-01

    Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS) equipped with high-density Laser imaging Detection and Ranging (LiDAR) scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014). The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

  20. DRAWING FOR TRAFFIC MARKING USING BIDIRECTIONAL GRADIENT-BASED DETECTION WITH MMS LIDAR INTENSITY

    Directory of Open Access Journals (Sweden)

    G. Takahashi

    2016-06-01

    Full Text Available Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS equipped with high-density Laser imaging Detection and Ranging (LiDAR scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014. The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

  1. Traffic Multiresolution Modeling and Consistency Analysis of Urban Expressway Based on Asynchronous Integration Strategy

    Directory of Open Access Journals (Sweden)

    Liyan Zhang

    2017-01-01

    Full Text Available The paper studies multiresolution traffic flow simulation model of urban expressway. Firstly, compared with two-level hybrid model, three-level multiresolution hybrid model has been chosen. Then, multiresolution simulation framework and integration strategies are introduced. Thirdly, the paper proposes an urban expressway multiresolution traffic simulation model by asynchronous integration strategy based on Set Theory, which includes three submodels: macromodel, mesomodel, and micromodel. After that, the applicable conditions and derivation process of the three submodels are discussed in detail. In addition, in order to simulate and evaluate the multiresolution model, “simple simulation scenario” of North-South Elevated Expressway in Shanghai has been established. The simulation results showed the following. (1 Volume-density relationships of three submodels are unanimous with detector data. (2 When traffic density is high, macromodel has a high precision and smaller error and the dispersion of results is smaller. Compared with macromodel, simulation accuracies of micromodel and mesomodel are lower but errors are bigger. (3 Multiresolution model can simulate characteristics of traffic flow, capture traffic wave, and keep the consistency of traffic state transition. Finally, the results showed that the novel multiresolution model can have higher simulation accuracy and it is feasible and effective in the real traffic simulation scenario.

  2. Real-time traffic sign recognition based on a general purpose GPU and deep-learning.

    Science.gov (United States)

    Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

    2017-01-01

    We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

  3. Entropy Based Analysis of DNS Query Traffic in the Campus Network

    Directory of Open Access Journals (Sweden)

    Dennis Arturo Ludeña Romaña

    2008-10-01

    Full Text Available We carried out the entropy based study on the DNS query traffic from the campus network in a university through January 1st, 2006 to March 31st, 2007. The results are summarized, as follows: (1 The source IP addresses- and query keyword-based entropies change symmetrically in the DNS query traffic from the outside of the campus network when detecting the spam bot activity on the campus network. On the other hand (2, the source IP addresses- and query keywordbased entropies change similarly each other when detecting big DNS query traffic caused by prescanning or distributed denial of service (DDoS attack from the campus network. Therefore, we can detect the spam bot and/or DDoS attack bot by only watching DNS query access traffic.

  4. Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

    Science.gov (United States)

    Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

    2016-01-01

    This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

  5. Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones

    Directory of Open Access Journals (Sweden)

    Cuiping Zhang

    2014-01-01

    Full Text Available Traffic safety evaluation for traffic analysis zones (TAZs plays an important role in transportation safety planning and long-range transportation plan development. This paper aims to present a comprehensive analysis of zonal safety evaluation. First, several criteria are proposed to measure the crash risk at zonal level. Then these criteria are integrated into one measure-average hazard index (AHI, which is used to identify unsafe zones. In addition, the study develops a negative binomial regression model to statistically estimate significant factors for the unsafe zones. The model results indicate that the zonal crash frequency can be associated with several social-economic, demographic, and transportation system factors. The impact of these significant factors on zonal crash is also discussed. The finding of this study suggests that safety evaluation and estimation might benefit engineers and decision makers in identifying high crash locations for potential safety improvements.

  6. Weighted Networks Model Based on Traffic Dynamics with Local Perturbation

    International Nuclear Information System (INIS)

    Zhao Hui; Gao Ziyou

    2007-01-01

    In the study of weighted complex networks, the interplay between traffic and topology have been paid much attention. However, the variation of topology and weight brought by new added vertices or edges should also be considered. In this paper, an evolution model of weighted networks driven by traffic dynamics with local perturbation is proposed. The model gives power-law distribution of degree, weight and strength, as confirmed by empirical measurements. By choosing appropriate parameters W and δ, the exponents of various power law distributions can be adjusted to meet real world networks. Nontrivial clustering coefficient C, degree assortativity coefficient r, and strength-degree correlation are also considered. What should be emphasized is that, with the consideration of local perturbation, one can adjust the exponent of strength-degree correlation more effectively. It makes our model more general than previous ones and may help reproducing real world networks more appropriately.

  7. A Knowledge- Based Decision Support Architecture for Advanced Traffic Management

    OpenAIRE

    Ritchie, Stephen G.

    1990-01-01

    Fundamental to the operation of most currently envisioned Intelligent Vehicle-Roadway System (IVRS) projects are advanced systems for surveillance, control and management of integrated freeway and arterial networks. A major concern in the development of such Smart Roads, and the focus of this paper, is the provision of decision support for traffic management center personnel, particularly for addressing nonrecurring congestion in large or complex networks. Decision support for control room st...

  8. Opposition-Based Adaptive Fireworks Algorithm

    OpenAIRE

    Chibing Gong

    2016-01-01

    A fireworks algorithm (FWA) is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA) proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA). The purpose of this paper is to add opposition-based learning (OBL) to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based a...

  9. Next generation network based carrier ethernet test bed for IPTV traffic

    DEFF Research Database (Denmark)

    Fu, Rong; Berger, Michael Stübert; Zheng, Yu

    2009-01-01

    This paper presents a Carrier Ethernet (CE) test bed based on the Next Generation Network (NGN) framework. After the concept of CE carried out by Metro Ethernet Forum (MEF), the carrier-grade Ethernet are obtaining more and more interests and being investigated as the low cost and high performanc...... services of transport network to carry the IPTV traffic. This test bed is approaching to support the research on providing a high performance carrier-grade Ethernet transport network for IPTV traffic....

  10. A novel downlink scheduling strategy for traffic communication system based on TD-LTE technology.

    Science.gov (United States)

    Chen, Ting; Zhao, Xiangmo; Gao, Tao; Zhang, Licheng

    2016-01-01

    There are many existing classical scheduling algorithms which can obtain better system throughput and user equality, however, they are not designed for traffic transportation environment, which cannot consider whether the transmission performance of various information flows could meet comprehensive requirements of traffic safety and delay tolerance. This paper proposes a novel downlink scheduling strategy for traffic communication system based on TD-LTE technology, which can perform two classification mappings for various information flows in the eNodeB: firstly, associate every information flow packet with traffic safety importance weight according to its relevance to the traffic safety; secondly, associate every traffic information flow with service type importance weight according to its quality of service (QoS) requirements. Once the connection is established, at every scheduling moment, scheduler would decide the scheduling order of all buffers' head of line packets periodically according to the instant value of scheduling importance weight function, which calculated by the proposed algorithm. From different scenario simulations, it can be verified that the proposed algorithm can provide superior differentiated transmission service and reliable QoS guarantee to information flows with different traffic safety levels and service types, which is more suitable for traffic transportation environment compared with the existing popularity PF algorithm. With the limited wireless resource, information flow closed related to traffic safety will always obtain priority scheduling right timely, which can help the passengers' journey more safe. Moreover, the proposed algorithm cannot only obtain good flow throughput and user fairness which are almost equal to those of the PF algorithm without significant differences, but also provide better realtime transmission guarantee to realtime information flow.

  11. Sliding Window Based Feature Extraction and Traffic Clustering for Green Mobile Cyberphysical Systems

    Directory of Open Access Journals (Sweden)

    Jiao Zhang

    2017-01-01

    Full Text Available Both the densification of small base stations and the diversity of user activities bring huge challenges for today’s heterogeneous networks, either heavy burdens on base stations or serious energy waste. In order to ensure coverage of the network while reducing the total energy consumption, we adopt a green mobile cyberphysical system (MCPS to handle this problem. In this paper, we propose a feature extraction method using sliding window to extract the distribution feature of mobile user equipment (UE, and a case study is presented to demonstrate that the method is efficacious in reserving the clustering distribution feature. Furthermore, we present traffic clustering analysis to categorize collected traffic distribution samples into a limited set of traffic patterns, where the patterns and corresponding optimized control strategies are used to similar traffic distributions for the rapid control of base station state. Experimental results show that the sliding window is more superior in enabling higher UE coverage over the grid method. Besides, the optimized control strategy obtained from the traffic pattern is capable of achieving a high coverage that can well serve over 98% of all mobile UE for similar traffic distributions.

  12. Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

    Directory of Open Access Journals (Sweden)

    Yiliang Zeng

    Full Text Available Due to the rapid development of motor vehicle Driver Assistance Systems (DAS, the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

  13. Traffic Management for Emergency Vehicle Priority Based on Visual Sensing

    Directory of Open Access Journals (Sweden)

    Kapileswar Nellore

    2016-11-01

    Full Text Available Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible traffic congestion at intersections. Most of the traffic lights today feature a fixed green light sequence, therefore the green light sequence is determined without taking the presence of the emergency vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines, etc. stuck in a traffic jam and delayed in reaching their destination can lead to loss of property and valuable lives. This paper presents an approach to schedule emergency vehicles in traffic. The approach combines the measurement of the distance between the emergency vehicle and an intersection using visual sensing methods, vehicle counting and time sensitive alert transmission within the sensor network. The distance between the emergency vehicle and the intersection is calculated for comparison using Euclidean distance, Manhattan distance and Canberra distance techniques. The experimental results have shown that the Euclidean distance outperforms other distance measurement techniques. Along with visual sensing techniques to collect emergency vehicle information, it is very important to have a Medium Access Control (MAC protocol to deliver the emergency vehicle information to the Traffic Management Center (TMC with less delay. Then only the emergency vehicle is quickly served and can reach the destination in time. In this paper, we have also investigated the MAC layer in WSNs to prioritize the emergency vehicle data and to reduce the transmission delay for emergency messages. We have modified the medium access procedure used in standard IEEE 802.11p with PE-MAC protocol, which is a new back off selection and contention window adjustment scheme to achieve low broadcast delay for emergency messages. A VANET model for the UTMS is developed and simulated in NS-2. The performance of the standard IEEE 802.11p and the proposed PE-MAC is analysed in detail. The NS-2

  14. Traffic Management for Emergency Vehicle Priority Based on Visual Sensing.

    Science.gov (United States)

    Nellore, Kapileswar; Hancke, Gerhard P

    2016-11-10

    Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible traffic congestion at intersections. Most of the traffic lights today feature a fixed green light sequence, therefore the green light sequence is determined without taking the presence of the emergency vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines, etc. stuck in a traffic jam and delayed in reaching their destination can lead to loss of property and valuable lives. This paper presents an approach to schedule emergency vehicles in traffic. The approach combines the measurement of the distance between the emergency vehicle and an intersection using visual sensing methods, vehicle counting and time sensitive alert transmission within the sensor network. The distance between the emergency vehicle and the intersection is calculated for comparison using Euclidean distance, Manhattan distance and Canberra distance techniques. The experimental results have shown that the Euclidean distance outperforms other distance measurement techniques. Along with visual sensing techniques to collect emergency vehicle information, it is very important to have a Medium Access Control (MAC) protocol to deliver the emergency vehicle information to the Traffic Management Center (TMC) with less delay. Then only the emergency vehicle is quickly served and can reach the destination in time. In this paper, we have also investigated the MAC layer in WSNs to prioritize the emergency vehicle data and to reduce the transmission delay for emergency messages. We have modified the medium access procedure used in standard IEEE 802.11p with PE-MAC protocol, which is a new back off selection and contention window adjustment scheme to achieve low broadcast delay for emergency messages. A VANET model for the UTMS is developed and simulated in NS-2. The performance of the standard IEEE 802.11p and the proposed PE-MAC is analysed in detail. The NS-2 simulation results

  15. Improving information for community-based adaptation

    Energy Technology Data Exchange (ETDEWEB)

    Huq, Saleemul

    2011-10-15

    Community-based adaptation aims to empower local people to cope with and plan for the impacts of climate change. In a world where knowledge equals power, you could be forgiven for thinking that enabling this type of adaptation boils down to providing local people with information. Conventional approaches to planning adaptation rely on 'expert' advice and credible 'science' from authoritative information providers such as the Intergovernmental Panel on Climate Change. But to truly support the needs of local communities, this information needs to be more site-specific, more user-friendly and more inclusive of traditional knowledge and existing coping practices.

  16. Opposition-Based Adaptive Fireworks Algorithm

    Directory of Open Access Journals (Sweden)

    Chibing Gong

    2016-07-01

    Full Text Available A fireworks algorithm (FWA is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA. The purpose of this paper is to add opposition-based learning (OBL to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based adaptive fireworks algorithm (OAFWA. The final results conclude that OAFWA significantly outperformed EFWA and AFWA in terms of solution accuracy. Additionally, OAFWA was compared with a bat algorithm (BA, differential evolution (DE, self-adapting control parameters in differential evolution (jDE, a firefly algorithm (FA, and a standard particle swarm optimization 2011 (SPSO2011 algorithm. The research results indicate that OAFWA ranks the highest of the six algorithms for both solution accuracy and runtime cost.

  17. Adaptive Beamforming Based on Complex Quaternion Processes

    Directory of Open Access Journals (Sweden)

    Jian-wu Tao

    2014-01-01

    Full Text Available Motivated by the benefits of array signal processing in quaternion domain, we investigate the problem of adaptive beamforming based on complex quaternion processes in this paper. First, a complex quaternion least-mean squares (CQLMS algorithm is proposed and its performance is analyzed. The CQLMS algorithm is suitable for adaptive beamforming of vector-sensor array. The weight vector update of CQLMS algorithm is derived based on the complex gradient, leading to lower computational complexity. Because the complex quaternion can exhibit the orthogonal structure of an electromagnetic vector-sensor in a natural way, a complex quaternion model in time domain is provided for a 3-component vector-sensor array. And the normalized adaptive beamformer using CQLMS is presented. Finally, simulation results are given to validate the performance of the proposed adaptive beamformer.

  18. Swarm-Based Smart City Platform: A Traffic Application

    Directory of Open Access Journals (Sweden)

    Pablo CHAMOSO

    2016-05-01

    Full Text Available Smart cities are proposed as a medium-term option for all cities. This article aims to propose an architecture that allows cities to provide solutions to interconnect all their elements. The study case focuses in locating and optimized regulation of traffic in cities. However, thanks to the proposed structure and the applied algorithms, the architecture is scalable in size of the sensor network, in functionality or even in the use of resources. A simulation environment that is able to show the operation of the architecture in the same way that a real city would, is presented.

  19. Volunteer-Based System for Research on the Internet Traffic

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Balachandran, Kartheepan; Hald, Sara Ligaard

    2012-01-01

    To overcome the drawbacks of existing methods for traffic classification (by ports, Deep Packet Inspection, statistical classification) a new system was developed, in which the data are collected and classified directly by clients installed on machines belonging to volunteers. Our approach combines...... the information obtained from the system sockets, the HTTP content types, and the data transmitted through network interfaces. It allows to group packets into flows and associate them with particular applications or types of service. This paper presents the design of our system, the implementation, the testing...

  20. Rotating-Disk-Based Hybridized Electromagnetic-Triboelectric Nanogenerator for Sustainably Powering Wireless Traffic Volume Sensors.

    Science.gov (United States)

    Zhang, Binbin; Chen, Jun; Jin, Long; Deng, Weili; Zhang, Lei; Zhang, Haitao; Zhu, Minhao; Yang, Weiqing; Wang, Zhong Lin

    2016-06-28

    Wireless traffic volume detectors play a critical role for measuring the traffic-flow in a real-time for current Intelligent Traffic System. However, as a battery-operated electronic device, regularly replacing battery remains a great challenge, especially in the remote area and wide distribution. Here, we report a self-powered active wireless traffic volume sensor by using a rotating-disk-based hybridized nanogenerator of triboelectric nanogenerator and electromagnetic generator as the sustainable power source. Operated at a rotating rate of 1000 rpm, the device delivered an output power of 17.5 mW, corresponding to a volume power density of 55.7 W/m(3) (Pd = P/V, see Supporting Information for detailed calculation) at a loading resistance of 700 Ω. The hybridized nanogenerator was demonstrated to effectively harvest energy from wind generated by a moving vehicle through the tunnel. And the delivered power is capable of triggering a counter via a wireless transmitter for real-time monitoring the traffic volume in the tunnel. This study further expands the applications of triboelectric nanogenerators for high-performance ambient mechanical energy harvesting and as sustainable power sources for driving wireless traffic volume sensors.

  1. Quality based approach for adaptive face recognition

    Science.gov (United States)

    Abboud, Ali J.; Sellahewa, Harin; Jassim, Sabah A.

    2009-05-01

    Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary restore image quality according to the need of the intended application. In this paper, we present no-reference image quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance of adaptive face recognition system over the corresponding non-adaptive scheme.

  2. Burden of road traffic injuries in Nepal: results of a countrywide population-based survey.

    Science.gov (United States)

    Nepal, Sarthak; Gupta, Shailvi; Wong, Evan G; Gurung, Susant; Swaroop, Mamta; Kushner, Adam L; Nwomeh, Benedict C

    2015-04-27

    Road traffic injury has emerged as a leading cause of mortality, contributing to 2·1% of deaths globally and is predicted to be the third highest contributor to the global burden of mortality by 2020. This major public health problem disproportionately affects low-income and middle-income countries, where such incidents are too often underreported. Our study aims to explore the epidemiology of road traffic injurys in Nepal at a population level via a countrywide study. The Surgeons OverSeas Assessment of Surgical Need (SOSAS) tool, a cluster randomised, cross-sectional nationwide survey, was conducted in Nepal between May 25, and June 12, 2014. Two-stage cluster sampling was performed: 15 of 75 districts were chosen randomly proportional to population; within each district, after stratification for urban and rural, and three clusters were randomly chosen. Questions were structured anatomically and designed around a representative spectrum of surgical conditions. Road traffic injury-related results were reported. 1350 households and 2695 individuals were surveyed with a response rate of 97%. 75 road traffic injuries were reported in 72 individuals (2·67% [95% CI 2·10-3·35] of the study population), with a mean age of 33·2 years (SD 1·85). The most commonly affected age group was 30-44 years, with females showing significantly lower odds of sustaining a road traffic injury than men (crude odds ratio 0·29 [95% CI 0·16-0·52]). Road traffic injuries composed 19·8% of the injuries reported. Motorcycle crashes were the most common road traffic injuries (48·0%), followed by car, truck, or bus crashes (26·7%), and pedestrian or bicycle crashes (25·3%). The extremity was the most common anatomic site injured (74·7%). Of the 80 deaths reported in the previous year, 7·5% (n=6) were due to road traffic injuries. This study provides the epidemiology of road traffic injuries at a population-based level in the first countrywide surgical needs assessment in Nepal

  3. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Zhaosheng Yang

    2014-01-01

    Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

  4. Domain Adaption Based on ELM Autoencoder

    Directory of Open Access Journals (Sweden)

    Wan-Yu Deng

    2017-01-01

    Full Text Available We propose a new ELM Autoencoder (ELM-AE based domain adaption algorithm which describes the subspaces of source and target domain by ELM-AE and then carries out subspace alignment to project different domains into a common new space. By leveraging nonlinear approximation ability and efficient one-pass learning ability of ELM-AE, the proposed domain adaption algorithm can efficiently seek a better cross-domain feature representation than linear feature representation approaches such as PCA to improve domain adaption performance. The widely experimental results on Office/Caltech-256 datasets show that the proposed algorithm can achieve better classification accuracy than PCA subspace alignment algorithm and other state-of-the-art domain adaption algorithms in most cases.

  5. Adaptive designs for learning based on MOOCs

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2016-01-01

    Informed by research in MOOCs and adaptive learning systems the project has developed a design framework which can guide the development of SPOCs (Small Private Online Courses), adapted to experienced school teachers' different learning needs. In 2020 it will be a requirement that, Danish school...... teachers have a bachelor degree in the subjects they teach. More than 10,000 teachers need professional development and municipalities ask for an adaptive teacher development program with personalized learning. The project's research question is the study and development of design principles that can guide...... the development of adaptive designs for learning on the basis of MOOCs as an overall design framework. The project is methodologically inspired by Design Based Research....

  6. A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

    Directory of Open Access Journals (Sweden)

    Jianqiang Wang

    2013-12-01

    Full Text Available The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS. This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

  7. Road Traffic Congestion Management Based on a Search-Allocation Approach

    Directory of Open Access Journals (Sweden)

    Raiyn Jamal

    2017-03-01

    Full Text Available This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA. An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT technologies.

  8. An Embedded Fuzzy Logic Based Application for Density Traffic Control System

    Directory of Open Access Journals (Sweden)

    Ajao Lukman Adewale

    2018-02-01

    Full Text Available The control of density traffic at cross junction road usually manned by human efforts or implementation of automatic traffic light system. This system seem and proves to be inefficient with some challenges. The major constraints of this traffic control are as a result of the inability of most traffic control systems to assign appropriate waiting time for vehicles based on the lane density. Also with little or no consideration for pedestrians, emergency and security agents priorities. In view of this, an intelligent density traffic control system using  (fuzzy logic which is capable of providing priority to the road users based on the density and emergency situations was developed and presented in this paper. This system will obtain the approximate amount of vehicle and presence of pedestrians respectfully on each lane with help of Infrared Sensors (IR and siren detection system for emergency and security road users. The working principle of this system depending on the logic inputs rules given into the processing unit by the (sensors, S1 and S2 which helps the system to generates a timing sequence that best suit the number of vehicles and pedestrians available on the lane at point in time.

  9. A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2016-02-01

    Full Text Available Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this issue, an efficient feature selection method for network traffic based on a new parallel computing framework called Spark is proposed in this paper. In our approach, the complete feature set is firstly preprocessed based on Fisher score, and a sequential forward search strategy is employed for subsets. The optimal feature subset is then selected using the continuous iterations of the Spark computing framework. The implementation demonstrates that, on the precondition of keeping the classification accuracy, our method reduces the time cost of modeling and classification, and improves the execution efficiency of feature selection significantly.

  10. Local-Area Based Traffic Splitter for Improving Performance Using Subnetting

    Science.gov (United States)

    Yadav, Meenakshi; Mittal, Mohit Kumar

    2010-11-01

    This document provides an overview of LAN traffic splitter. The tool "Local-Area based Traffic splitter" is based on subnetting techniques. It is basically used for calculating subnets for sub-dividing the LAN. Subnetting an IP Network can be done for a variety of reasons, including organization, use of different physical media (such as Ethernet, FDDI, WAN, etc.), preservation of address space, and security. The most common reason is to control network traffic. There are various techniques for calculating subnets that are considered by this tool. This paper will explore the various features of this tool and will also check the effect of subnetting after implementing it on the LAN. These instructions give you basic guidelines for preparing camera-ready papers for conference proceedings.

  11. QPSO-Based Adaptive DNA Computing Algorithm

    Directory of Open Access Journals (Sweden)

    Mehmet Karakose

    2013-01-01

    Full Text Available DNA (deoxyribonucleic acid computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO. Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1 parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2 adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3 numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm.

  12. Ecosystem based approaches to climate adaptation

    DEFF Research Database (Denmark)

    Zandersen, Marianne; Jensen, Anne; Termansen, Mette

    This report analyses the prospects and barriers of applying ecosystem based approaches systematically to climate adaptation in urban areas, taking the case of green roofs in Copenhagen Municipality. It looks at planning aspects of green roofs in Copenhagen as well as citizen views and preferences...... regarding green roofs using policy document analysis, interviews with city planners and deliberative valuation methods....

  13. Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network

    Science.gov (United States)

    Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang

    2015-12-01

    Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.

  14. GIS-BASED ROUTE FINDING USING ANT COLONY OPTIMIZATION AND URBAN TRAFFIC DATA FROM DIFFERENT SOURCES

    Directory of Open Access Journals (Sweden)

    M. Davoodi

    2015-12-01

    Full Text Available Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD, Automatic Number Plate Recognition (ANPR, Floating Car Data (FCD, VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

  15. Gis-Based Route Finding Using ANT Colony Optimization and Urban Traffic Data from Different Sources

    Science.gov (United States)

    Davoodi, M.; Mesgari, M. S.

    2015-12-01

    Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

  16. Comprehensive Parameter Sweep for Learning-based Detector on Traffic Lights

    DEFF Research Database (Denmark)

    Jensen, Morten Bornø; Philipsen, Mark Philip; Trivedi, Mohan M.

    2016-01-01

    Determining the optimal parameters for a given detection algorithm is not straightforward and what ends up as the final values is mostly based on experience and heuristics. In this paper we investigate the influence of three basic parameters in the widely used Aggregate Channel Features (ACF......) object detector applied for traffic light detec- tion. Additionally, we perform an exhaustive search for the optimal pa- rameters for the night time data from the LISA Traffic Light Dataset. The optimized detector reaches an Area-Under-Curve of 66.63 % on cal- culated precision-recall curve....

  17. Throughput-Based Traffic Steering in LTE-Advanced HetNet Deployments

    DEFF Research Database (Denmark)

    Gimenez, Lucas Chavarria; Kovacs, Istvan Z.; Wigard, Jeroen

    2015-01-01

    The objective of this paper is to propose traffic steering solutions that aim at optimizing the end-user throughput. Two different implementations of an active mode throughput-based traffic steering algorithm for Heterogeneous Networks (HetNet) are introduced. One that always forces handover...... of the active users towards the cell offering the highest throughput, and a second scheme that aims at maximizing the systems sum throughput. Results show that the first option brings the best performance at the cost of more than three handovers per user per second for high-load cases. The second option offers...... slightly lower traffic steering gains at a considerably lower cost in terms of number of handovers. The gain in terms of increased average session throughput for the second option equals 32% at low-load, 18% at medium-load, and 7% at high-load conditions. The gain in the fifth percentile user session...

  18. A Big Network Traffic Data Fusion Approach Based on Fisher and Deep Auto-Encoder

    Directory of Open Access Journals (Sweden)

    Xiaoling Tao

    2016-03-01

    Full Text Available Data fusion is usually performed prior to classification in order to reduce the input space. These dimensionality reduction techniques help to decline the complexity of the classification model and thus improve the classification performance. The traditional supervised methods demand labeled samples, and the current network traffic data mostly is not labeled. Thereby, better learners will be built by using both labeled and unlabeled data, than using each one alone. In this paper, a novel network traffic data fusion approach based on Fisher and deep auto-encoder (DFA-F-DAE is proposed to reduce the data dimensions and the complexity of computation. The experimental results show that the DFA-F-DAE improves the generalization ability of the three classification algorithms (J48, back propagation neural network (BPNN, and support vector machine (SVM by data dimensionality reduction. We found that the DFA-F-DAE remarkably improves the efficiency of big network traffic classification.

  19. Predictive control strategies for energy saving of hybrid electric vehicles based on traffic light information

    Directory of Open Access Journals (Sweden)

    Kaijiang YU

    2015-10-01

    Full Text Available As the conventional control method for hybrid electric vehicle doesn’t consider the effect of known traffic light information on the vehicle energy management, this paper proposes a model predictive control intelligent optimization strategies based on traffic light information for hybrid electric vehicles. By building the simplified model of the hybrid electric vehicle and adopting the continuation/generalized minimum residual method, the model prediction problem is solved. The simulation is conducted by using MATLAB/Simulink platform. The simulation results show the effectiveness of the proposed model of the traffic light information, and that the proposed model predictive control method can improve fuel economy and the real-time control performance significantly. The research conclusions show that the proposed control strategy can achieve optimal control of the vehicle trajectory, significantly improving fuel economy of the vehicle, and meet the system requirements for the real-time optimal control.

  20. Efficient IP Traffic over Optical Network Based on Wavelength Translation Switching

    DEFF Research Database (Denmark)

    Jha, Vikas; Kalia, Kartik; Chowdhary, Bhawani Shankar

    2016-01-01

    With the advent of TCP/IP protocol suite the overall era of communication technologies had been redefined. Now, we can’t ignore the presence of huge amount of IP traffic; data, voice or video increasing day by day creating more pressure on existing communicating media and supporting back bone....... With the humongous popularity of Internet the overall traffic on Internet has the same story. Focusing on transmission of IP traffic in an optical network with signals remaining in their optical nature generated at particular wavelength, proposed is the switching of optically generated IP packets through optical...... cross connects based on translation of wavelength when an IP packet is crossing the optical cross connect. Adding the concepts of layer 3 routing protocols along with the wavelength translation scheme, will help in spanning the overall optical network for a larger area....

  1. Environmental impact of electric motorcycles: Evidence from traffic noise assessment by a building-based data mining technique.

    Science.gov (United States)

    Sheng, N; Zhou, X; Zhou, Y

    2016-06-01

    This study provided new evidence on the potential adoption of electric motorcycle (EM) as a cleaner alternative to gasoline-powered motorcycle. The effects of EM on human exposure to traffic noise were assessed in different urban areas with different traffic scenarios. The assessment was carried out by a developed building-based model system that took into account the contribution of motorcycle traffic. The results indicated that the EM could be an appealing solution to reduce the risk of human exposure to excessive high traffic noise in a motorcycle city. Particularly, in a historical urban area in which the total traffic volume was lower and motorcycle traffic was dominant, the proportion of noise levels meeting the standard of 70 dB(A) increased significantly from 12.2% to 41.9% when 100% of gasoline motorcycles in the real traffic scenario were replaced by EMs. On the other hand, in a modern urban area in which the total traffic volume was higher and traffic noise levels at majority of sites were higher than 75 dB(A), the proportion of noise levels above 75 dB(A) decreased significantly from 82.6% to 59.9%. Nevertheless, the effect of EM on improving the traffic noise compliance rate in the modern urban area was not significant and other policies or measures need to be sought. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Grid Mapping for Spatial Pattern Analyses of Recurrent Urban Traffic Congestion Based on Taxi GPS Sensing Data

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-03-01

    Full Text Available Traffic congestion is one of the most serious problems that impact urban transportation efficiency, especially in big cities. Identifying traffic congestion locations and occurring patterns is a prerequisite for urban transportation managers in order to take proper countermeasures for mitigating traffic congestion. In this study, the historical GPS sensing data of about 12,000 taxi floating cars in Beijing were used for pattern analyses of recurrent traffic congestion based on the grid mapping method. Through the use of ArcGIS software, 2D and 3D maps of the road network congestion were generated for traffic congestion pattern visualization. The study results showed that three types of traffic congestion patterns were identified, namely: point type, stemming from insufficient capacities at the nodes of the road network; line type, caused by high traffic demand or bottleneck issues in the road segments; and region type, resulting from multiple high-demand expressways merging and connecting to each other. The study illustrated that the proposed method would be effective for discovering traffic congestion locations and patterns and helpful for decision makers to take corresponding traffic engineering countermeasures in order to relieve the urban traffic congestion issues.

  3. A Task-Based Language Teaching Approach to the Police Traffic Stop

    Science.gov (United States)

    O'Connell, Stephen P.

    2014-01-01

    One possible hurdle to implementing the Task-Based Language Teaching (TBLT) approach is uncertainty about how to turn target tasks into materials that can be used in the classroom. This article discusses the steps taken to create materials for one target task (communicating with a police officer during a traffic stop) in a manner that provides a…

  4. Classification of HTTP traffic based on C5.0 Machine Learning Algorithm

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Riaz, Tahir; Pedersen, Jens Myrup

    2012-01-01

    streaming through third-party plugins, etc. This paper suggests and evaluates two approaches to distinguish various types of HTTP traffic based on the content: distributed among volunteers' machines and centralized running in the core of the network. We also assess the accuracy of the centralized classifier...

  5. Data-driven Travel Demand Modelling and Agent-based Traffic Simulation in Amsterdam Urban Area

    NARCIS (Netherlands)

    Melnikov, V.R.; Krzhizhanovskaya, V.V.; Lees, M.H.; Boukhanovsky, A.V.

    2016-01-01

    The goal of this project is the development of a large-scale agent-based traffic simulation system for Amsterdam urban area, validated on sensor data and adjusted for decision support in critical situations and for policy making in sustainable city development, emission control and electric car

  6. 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.

  7. Background Traffic-Based Retransmission Algorithm for Multimedia Streaming Transfer over Concurrent Multipaths

    Directory of Open Access Journals (Sweden)

    Yuanlong Cao

    2012-01-01

    Full Text Available The content-rich multimedia streaming will be the most attractive services in the next-generation networks. With function of distribute data across multipath end-to-end paths based on SCTP's multihoming feature, concurrent multipath transfer SCTP (CMT-SCTP has been regarded as the most promising technology for the efficient multimedia streaming transmission. However, the current researches on CMT-SCTP mainly focus on the algorithms related to the data delivery performance while they seldom consider the background traffic factors. Actually, background traffic of realistic network environments has an important impact on the performance of CMT-SCTP. In this paper, we firstly investigate the effect of background traffic on the performance of CMT-SCTP based on a close realistic simulation topology with reasonable background traffic in NS2, and then based on the localness nature of background flow, a further improved retransmission algorithm, named RTX_CSI, is proposed to reach more benefits in terms of average throughput and achieve high users' experience of quality for multimedia streaming services.

  8. Traffic characterization and modeling of wavelet-based VBR encoded video

    Energy Technology Data Exchange (ETDEWEB)

    Yu Kuo; Jabbari, B. [George Mason Univ., Fairfax, VA (United States); Zafar, S. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1997-07-01

    Wavelet-based video codecs provide a hierarchical structure for the encoded data, which can cater to a wide variety of applications such as multimedia systems. The characteristics of such an encoder and its output, however, have not been well examined. In this paper, the authors investigate the output characteristics of a wavelet-based video codec and develop a composite model to capture the traffic behavior of its output video data. Wavelet decomposition transforms the input video in a hierarchical structure with a number of subimages at different resolutions and scales. the top-level wavelet in this structure contains most of the signal energy. They first describe the characteristics of traffic generated by each subimage and the effect of dropping various subimages at the encoder on the signal-to-noise ratio at the receiver. They then develop an N-state Markov model to describe the traffic behavior of the top wavelet. The behavior of the remaining wavelets are then obtained through estimation, based on the correlations between these subimages at the same level of resolution and those wavelets located at an immediate higher level. In this paper, a three-state Markov model is developed. The resulting traffic behavior described by various statistical properties, such as moments and correlations, etc., is then utilized to validate their model.

  9. An empirical model to predict road dust emissions based on pavement and traffic characteristics.

    Science.gov (United States)

    Padoan, Elio; Ajmone-Marsan, Franco; Querol, Xavier; Amato, Fulvio

    2017-11-08

    The relative impact of non-exhaust sources (i.e. road dust, tire wear, road wear and brake wear particles) on urban air quality is increasing. Among them, road dust resuspension has generally the highest impact on PM concentrations but its spatio-temporal variability has been rarely studied and modeled. Some recent studies attempted to observe and describe the time-variability but, as it is driven by traffic and meteorology, uncertainty remains on the seasonality of emissions. The knowledge gap on spatial variability is much wider, as several factors have been pointed out as responsible for road dust build-up: pavement characteristics, traffic intensity and speed, fleet composition, proximity to traffic lights, but also the presence of external sources. However, no parameterization is available as a function of these variables. We investigated mobile road dust smaller than 10 μm (MF10) in two cities with different climatic and traffic conditions (Barcelona and Turin), to explore MF10 seasonal variability and the relationship between MF10 and site characteristics (pavement macrotexture, traffic intensity and proximity to braking zone). Moreover, we provide the first estimates of emission factors in the Po Valley both in summer and winter conditions. Our results showed a good inverse relationship between MF10 and macro-texture, traffic intensity and distance from the nearest braking zone. We also found a clear seasonal effect of road dust emissions, with higher emission in summer, likely due to the lower pavement moisture. These results allowed building a simple empirical mode, predicting maximal dust loadings and, consequently, emission potential, based on the aforementioned data. This model will need to be scaled for meteorological effect, using methods accounting for weather and pavement moisture. This can significantly improve bottom-up emission inventory for spatial allocation of emissions and air quality management, to select those roads with higher emissions

  10. Traffic planning for non-homogeneous traffic

    Indian Academy of Sciences (India)

    2.3c Data summary The summarization of the density data based on videotape obser- vations is in table 1 which shows average, 30-second, sampled densities. Using the non- homogeneous traffic continuity equation of (2), the resultant traffic concentrations appear in table 2. Comparing the traffic concentrations in table 1 to ...

  11. Enhancing TSM&O strategies through life cycle benefit/cost analysis : life cycle benefit/cost analysis & life cycle assessment of adaptive traffic control systems and ramp metering systems.

    Science.gov (United States)

    2015-05-01

    The research team developed a comprehensive Benefit/Cost (B/C) analysis framework to evaluate existing and anticipated : intelligent transportation system (ITS) strategies, particularly, adaptive traffic control systems and ramp metering systems, : i...

  12. Testlet-based Multidimensional Adaptive Testing

    Directory of Open Access Journals (Sweden)

    Andreas Frey

    2016-11-01

    Full Text Available Multidimensional adaptive testing (MAT is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT. MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, 1.5 and testlet sizes (3 items, 6 items, 9 items with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

  13. Testlet-Based Multidimensional Adaptive Testing.

    Science.gov (United States)

    Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

    2016-01-01

    Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

  14. Entropy-based adaptive attitude estimation

    Science.gov (United States)

    Kiani, Maryam; Barzegar, Aylin; Pourtakdoust, Seid H.

    2018-03-01

    Gaussian approximation filters have increasingly been developed to enhance the accuracy of attitude estimation in space missions. The effective employment of these algorithms demands accurate knowledge of system dynamics and measurement models, as well as their noise characteristics, which are usually unavailable or unreliable. An innovation-based adaptive filtering approach has been adopted as a solution to this problem; however, it exhibits two major challenges, namely appropriate window size selection and guaranteed assurance of positive definiteness for the estimated noise covariance matrices. The current work presents two novel techniques based on relative entropy and confidence level concepts in order to address the abovementioned drawbacks. The proposed adaptation techniques are applied to two nonlinear state estimation algorithms of the extended Kalman filter and cubature Kalman filter for attitude estimation of a low earth orbit satellite equipped with three-axis magnetometers and Sun sensors. The effectiveness of the proposed adaptation scheme is demonstrated by means of comprehensive sensitivity analysis on the system and environmental parameters by using extensive independent Monte Carlo simulations.

  15. Analytical evaluation of adaptive-modulation-based opportunistic cognitive radio in nakagami-m fading channels

    KAUST Repository

    Chen, Yunfei

    2012-09-01

    The performance of adaptive modulation for cognitive radio with opportunistic access is analyzed by considering the effects of spectrum sensing, primary user (PU) traffic, and time delay for Nakagami- m fading channels. Both the adaptive continuous rate scheme and the adaptive discrete rate scheme are considered. Numerical examples are presented to quantify the effects of spectrum sensing, PU traffic, and time delay for different system parameters. © 1967-2012 IEEE.

  16. Adaptive CGFs Based on Grammatical Evolution

    Directory of Open Access Journals (Sweden)

    Jian Yao

    2015-01-01

    Full Text Available Computer generated forces (CGFs play blue or red units in military simulations for personnel training and weapon systems evaluation. Traditionally, CGFs are controlled through rule-based scripts, despite the doctrine-driven behavior of CGFs being rigid and predictable. Furthermore, CGFs are often tricked by trainees or fail to adapt to new situations (e.g., changes in battle field or update in weapon systems, and, in most cases, the subject matter experts (SMEs review and redesign a large amount of CGF scripts for new scenarios or training tasks, which is both challenging and time-consuming. In an effort to overcome these limitations and move toward more true-to-life scenarios, a study using grammatical evolution (GE to generate adaptive CGFs for air combat simulations has been conducted. Expert knowledge is encoded with modular behavior trees (BTs for compatibility with the operators in genetic algorithm (GA. GE maps CGFs, represented with BTs to binary strings, and uses GA to evolve CGFs with performance feedback from the simulation. Beyond-visual-range air combat experiments between adaptive CGFs and nonadaptive baseline CGFs have been conducted to observe and study this evolutionary process. The experimental results show that the GE is an efficient framework to generate CGFs in BTs formalism and evolve CGFs via GA.

  17. 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.

  18. Two-vehicle injury severity models based on integration of pavement management and traffic engineering factors.

    Science.gov (United States)

    Jiang, Ximiao; Huang, Baoshan; Yan, Xuedong; Zaretzki, Russell L; Richards, Stephen

    2013-01-01

    The severity of traffic-related injuries has been studied by many researchers in recent decades. However, the evaluation of many factors is still in dispute and, until this point, few studies have taken into account pavement management factors as points of interest. The objective of this article is to evaluate the combined influences of pavement management factors and traditional traffic engineering factors on the injury severity of 2-vehicle crashes. This study examines 2-vehicle rear-end, sideswipe, and angle collisions that occurred on Tennessee state routes from 2004 to 2008. Both the traditional ordered probit (OP) model and Bayesian ordered probit (BOP) model with weak informative prior were fitted for each collision type. The performances of these models were evaluated based on the parameter estimates and deviances. The results indicated that pavement management factors played identical roles in all 3 collision types. Pavement serviceability produces significant positive effects on the severity of injuries. The pavement distress index (PDI), rutting depth (RD), and rutting depth difference between right and left wheels (RD_df) were not significant in any of these 3 collision types. The effects of traffic engineering factors varied across collision types, except that a few were consistently significant in all 3 collision types, such as annual average daily traffic (AADT), rural-urban location, speed limit, peaking hour, and light condition. The findings of this study indicated that improved pavement quality does not necessarily lessen the severity of injuries when a 2-vehicle crash occurs. The effects of traffic engineering factors are not universal but vary by the type of crash. The study also found that the BOP model with a weak informative prior can be used as an alternative but was not superior to the traditional OP model in terms of overall performance.

  19. Section based traffic detection on motorways for incident management

    NARCIS (Netherlands)

    Noort, M. van; Klunder, G.

    2007-01-01

    Current vehicle detection on motorways is based generally on either inductive loop systems or various alternatives such as video cameras. Recently, we encountered two new developments that take a different approach: one from The Netherlands using microwave sensors, and the other from Sweden using

  20. Traffic allocation strategies in WSS-based dynamic optical networks

    OpenAIRE

    Shakeri, Ali; Garrich, Miquel; Bravalheri, Anderson; Careglio, Davide; Solé Pareta, Josep; Fumagalli, Andrea

    2017-01-01

    Elastic optical networking (EON) is a viable solution to meet future dynamic capacity requirements of Internet service provider and inter-datacenter networks. At the core of EON, wavelength selective switches (WSSs) are applied to individually route optical circuits, while assigning an arbitrary bandwidth to each circuit. Critically, the WSS control scheme and configuration time may delay the creation time of each circuit in the network. In this paper, we first detail the WSS-based optical da...

  1. Traffic theory

    National Research Council Canada - National Science Library

    Gazis, Denos C

    2002-01-01

    ... of traffic signal settings The vehicle-actuated traffic signal 87 89 77 CHAPTER 3. TRAFFIC CONTROL 101 Objectives of Traffic Control 103 Single, Isolated Intersection 105 Synchronization Scheme...

  2. Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model Generation for ns-3

    Science.gov (United States)

    2015-12-01

    more protocols (especially at different layers of the OSI model ), implementing an inference engine to extract inter- and intrapacket dependencies, and...ARL-TR-7543 ● DEC 2015 US Army Research Laboratory Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model ...ICMP) Model Generation for ns-3 by Jaime C Acosta and Felipe Jovel Survivability/Lethality Analysis Directorate, ARL Felipe Sotelo and Caesar

  3. A simulation-based dynamic traffic assignment model with combined modes

    Directory of Open Access Journals (Sweden)

    Meng Meng

    2014-02-01

    Full Text Available This paper presents a dynamic traffic assignment (DTA model for urban multi-modal transportation network by con­structing a mesoscopic simulation model. Several traffic means such as private car, subway, bus and bicycle are con­sidered in the network. The mesoscopic simulator consists of a mesoscopic supply simulator based on MesoTS model and a time-dependent demand simulator. The mode choice is si­multaneously considered with the route choice based on the improved C-Logit model. The traffic assignment procedure is implemented by a time-dependent shortest path (TDSP al­gorithm in which travellers choose their modes and routes based on a range of choice criteria. The model is particularly suited for appraising a variety of transportation management measures, especially for the application of Intelligent Trans­port Systems (ITS. Five example cases including OD demand level, bus frequency, parking fee, information supply and car ownership rate are designed to test the proposed simulation model through a medium-scale case study in Beijing Chaoy­ang District in China. Computational results illustrate excel­lent performance and the application of the model to analy­sis of urban multi-modal transportation networks.

  4. Intelligent Adaptation Process for Case Based Systems

    International Nuclear Information System (INIS)

    Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

    2014-01-01

    Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

  5. GIS based analysis of Intercity Fatal Road Traffic Accidents in Iran

    Science.gov (United States)

    Alizadeh, A; Zare, M; Darparesh, M; Mohseni, S; Soleimani-Ahmadi, M

    2015-01-01

    Road traffic accidents including intercity car traffic accidents (ICTAs) are among the most important causes of morbidity and mortality due to the growing number of vehicles, risky behaviors, and changes in lifestyle of the general population. A sound knowledge of the geographical distribution of car traffic accidents can be considered as an approach towards the accident causation and it can be used as an administrative tool in allocating the sources for traffic accidents prevention. This study was conducted to investigate the geographical distribution and the time trend of fatal intercity car traffic accidents in Iran. To conduct this descriptive study, all Iranian intercity road traffic mortality data were obtained from the Police reports in the Statistical Yearbook of the Governor’s Budget and Planning. The obtained data were for 17 complete Iranian calendar years from March 1997 to March 2012. The incidence rate (IR) of fatal ICTAs for each year was calculated as the total number of fatal ICTAs in every 100000 population in specified time intervals. Figures and maps indicating the trends and geographical distribution of fatal ICTAs were prepared while using Microsoft Excel and ArcGis9.2 software. The number of fatal car accidents showed a general increasing trend from 3000 in 1996 to 13500 in 2012. The incidence of fatal intercity car accidents has changed from six in 100000 population in 1996 to 18 in 100000 population in 2012. GIS based data showed that the incidence rate of ICTAs in different provinces of Iran was very divergent. The highest incidence of fatal ICTAs was in Semnan province (IR= 35.2), followed by North Khorasan (IR=22.7), and South Khorasan (IR=22). The least incidence of fatal ICTAs was in Tehran province (IR=2.4) followed by Khozestan (IR=6.5), and Eastern Azarbayejan (IR=6.6). The compensation cost of fatal ICTAs also showed an increasing trend during the studied period. Since an increasing amount of money was being paid yearly for the

  6. GIS based analysis of Intercity Fatal Road Traffic Accidents in Iran.

    Science.gov (United States)

    Alizadeh, A; Zare, M; Darparesh, M; Mohseni, S; Soleimani-Ahmadi, M

    2015-01-01

    Road traffic accidents including intercity car traffic accidents (ICTAs) are among the most important causes of morbidity and mortality due to the growing number of vehicles, risky behaviors, and changes in lifestyle of the general population. A sound knowledge of the geographical distribution of car traffic accidents can be considered as an approach towards the accident causation and it can be used as an administrative tool in allocating the sources for traffic accidents prevention. This study was conducted to investigate the geographical distribution and the time trend of fatal intercity car traffic accidents in Iran. To conduct this descriptive study, all Iranian intercity road traffic mortality data were obtained from the Police reports in the Statistical Yearbook of the Governor's Budget and Planning. The obtained data were for 17 complete Iranian calendar years from March 1997 to March 2012. The incidence rate (IR) of fatal ICTAs for each year was calculated as the total number of fatal ICTAs in every 100000 population in specified time intervals. Figures and maps indicating the trends and geographical distribution of fatal ICTAs were prepared while using Microsoft Excel and ArcGis9.2 software. The number of fatal car accidents showed a general increasing trend from 3000 in 1996 to 13500 in 2012. The incidence of fatal intercity car accidents has changed from six in 100000 population in 1996 to 18 in 100000 population in 2012. GIS based data showed that the incidence rate of ICTAs in different provinces of Iran was very divergent. The highest incidence of fatal ICTAs was in Semnan province (IR= 35.2), followed by North Khorasan (IR=22.7), and South Khorasan (IR=22). The least incidence of fatal ICTAs was in Tehran province (IR=2.4) followed by Khozestan (IR=6.5), and Eastern Azarbayejan (IR=6.6). The compensation cost of fatal ICTAs also showed an increasing trend during the studied period. Since an increasing amount of money was being paid yearly for the car

  7. Adaptive DFT-based Interferometer Fringe Tracking

    Science.gov (United States)

    Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.

    2004-01-01

    An automatic interferometer fringe tracking system has been developed, implemented, and tested at the Infrared Optical Telescope Array (IOTA) observatory at Mt. Hopkins, Arizona. The system can minimize the optical path differences (OPDs) for all three baselines of the Michelson stellar interferometer at IOTA. Based on sliding window discrete Fourier transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on off-line data. Implemented in ANSI C on the 266 MHz PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. The adaptive DFT-based tracking algorithm should be applicable to other systems where there is a need to detect or track a signal with an approximately constant-frequency carrier pulse.

  8. Vision based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems

    DEFF Research Database (Denmark)

    Møgelmose, Andreas; Trivedi, Mohan M.; Moeslund, Thomas B.

    2012-01-01

    In this paper, we provide a survey of the traffic sign detection literature, detailing detection systems for Traffic Sign Recognition (TSR) for driver assistance. We separately describe the contributions of recent works to the various stages inherent in traffic sign detection: segmentation, featu...... research, including integration of context and localization. We also introduce a new public database containing US traffic signs...

  9. A method for identifying compromised clients based on DNS traffic analysis

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup; D’Alconzo, Alessandro

    2017-01-01

    based on DNS traffic analysis. The proposed method identifies suspicious agile DNS mappings, i.e., mappings characterized by fast changing domain names or/and IP addresses, often used by malicious services. The approach discovers clients that have queried domains contained within identified suspicious...... domain-to-IP mappings, thus assisting in pinpointing potentially compromised clients within the network. The proposed approach targets compromised clients in large-scale operational networks. We have evaluated the proposed approach using an extensive set of DNS traffic traces from different operational...... ISP networks. The evaluation illustrates a great potential of accurately identifying suspicious domain-to-IP mappings and potentially compromised clients. Furthermore, the achieved performance indicate that the novel detection approach is promising in view of the adoption in operational ISP networks...

  10. Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

    Science.gov (United States)

    Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

    2017-01-01

    Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

  11. Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

    Directory of Open Access Journals (Sweden)

    Shameng Wen

    Full Text Available Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

  12. Dementia and traffic accidents: a Danish register-based cohort study

    DEFF Research Database (Denmark)

    Petersen, Jindong Ding; Siersma, Volkert Dirk; Nielsen, CT

    2016-01-01

    BACKGROUND: As a consequence of a rapid growth of an ageing population, more people with dementia are expected on the roads. Little is known about whether these people are at increased risk of road traffic-related accidents. OBJECTIVE: Our study aims to investigate the risk of road traffic......-related accidents for people aged 65 years or older with a diagnosis of dementia in Denmark. METHODS: We will conduct a nationwide population-based cohort study consisting of Danish people aged 65 or older living in Denmark as of January 1, 2008. The cohort is followed for 7 years (2008-2014). Individual's personal...... data are available in Danish registers and can be linked using a unique personal identification number. A person is identified with dementia if the person meets at least one of the following criteria: (1) a diagnosis of the disease in the Danish National Patient Register or in the Danish Psychiatric...

  13. SDP Policy Iteration-Based Energy Management Strategy Using Traffic Information for Commuter Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Xiaohong Jiao

    2014-07-01

    Full Text Available This paper demonstrates an energy management method using traffic information for commuter hybrid electric vehicles. A control strategy based on stochastic dynamic programming (SDP is developed, which minimizes on average the equivalent fuel consumption, while satisfying the battery charge-sustaining constraints and the overall vehicle power demand for drivability. First, according to the sample information of the traffic speed profiles, the regular route is divided into several segments and the statistic characteristics in the different segments are constructed from gathered data on the averaged vehicle speeds. And then, the energy management problem is formulated as a stochastic nonlinear and constrained optimal control problem and a modified policy iteration algorithm is utilized to generate a time-invariant state-dependent power split strategy. Finally, simulation results over some driving cycles are presented to demonstrate the effectiveness of the proposed energy management strategy.

  14. Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System

    Directory of Open Access Journals (Sweden)

    Miguel Gavilán

    2012-01-01

    Full Text Available This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM. A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  15. Complete vision-based traffic sign recognition supported by an I2V communication system.

    Science.gov (United States)

    García-Garrido, Miguel A; Ocaña, Manuel; Llorca, David F; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel

    2012-01-01

    This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  16. Implementation of a FPGA-Based Feature Detection and Networking System for Real-time Traffic Monitoring

    OpenAIRE

    Chen, Jieshi; Schafer, Benjamin Carrion; Ho, Ivan Wang-Hei

    2016-01-01

    With the growing demand of real-time traffic monitoring nowadays, software-based image processing can hardly meet the real-time data processing requirement due to the serial data processing nature. In this paper, the implementation of a hardware-based feature detection and networking system prototype for real-time traffic monitoring as well as data transmission is presented. The hardware architecture of the proposed system is mainly composed of three parts: data collection, feature detection,...

  17. Towards Computerized Adaptive Assessment Based on Structured Tasks

    NARCIS (Netherlands)

    Tvarožek, Jozef; Kravcik, Milos; Bieliková, Mária

    2008-01-01

    Tvarožek, J., Kravčík, M., & Bieliková, M. (2008). Towards Computerized Adaptive Assessment Based on Structured Tasks. In W. Nejdl et al. (Eds.), Adaptive Hypermedia and Adaptive Web-Based Systems (pp. 224-234). Springer Berlin / Heidelberg.

  18. A wireless computational platform for distributed computing based traffic monitoring involving mixed Eulerian-Lagrangian sensing

    KAUST Repository

    Jiang, Jiming

    2013-06-01

    This paper presents a new wireless platform designed for an integrated traffic monitoring system based on combined Lagrangian (mobile) and Eulerian (fixed) sensing. The sensor platform is built around a 32-bit ARM Cortex M4 micro-controller and a 2.4GHz 802.15.4 ISM compliant radio module, and can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. The platform is specially designed and optimized to be integrated in a solar-powered wireless sensor network in which traffic flow maps are computed by the nodes directly using distributed computing. A MPPT circuitry is proposed to increase the power output of the attached solar panel. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debug. An ongoing implementation is briefly discussed, and compared with existing platforms used in wireless sensor networks. © 2013 IEEE.

  19. Threshold based AntNet algorithm for dynamic traffic routing of road networks

    Directory of Open Access Journals (Sweden)

    Ayman M. Ghazy

    2012-07-01

    Full Text Available Dynamic routing algorithms play an important role in road traffic routing to avoid congestion and to direct vehicles to better routes. AntNet routing algorithms have been applied, extensively and successfully, in data communication network. However, its application for dynamic routing on road networks is still considerably limited. This paper presents a modified version of the AntNet routing algorithm, called “Threshold based AntNet”, that has the ability to efficiently utilize a priori information of dynamic traffic routing, especially, for road networks. The modification exploits the practical and pre-known information for most road traffic networks, namely, the good travel times between sources and destinations. The values of those good travel times are manipulated as threshold values. This approach has proven to conserve tracking of good routes. According to the dynamic nature of the problem, the presented approach guards the agility of rediscovering a good route. Attaining the thresholds (good reported travel times, of a given source to destination route, permits for a better utilization of the computational resources, that, leads to better accommodation for the network changes. The presented algorithm introduces a new type of ants called “check ants”. It assists in preserving good routes and, better yet, exposes and discards the degraded ones. The threshold AntNet algorithm presents a new strategy for updating the routing information, supported by the backward ants.

  20. Conception of the system for traffic measurements based on piezoelectric foils

    Science.gov (United States)

    Płaczek, M.

    2016-08-01

    A concept of mechatronic system for traffic measurements based on the piezoelectric transducers used as sensors is presented. The aim of the work project is to theoretically and experimentally analyse the dynamic response of road infrastructure forced by vehicles motion. The subject of the project is therefore on the borderline of civil engineering and mechanical and covers a wide range of issues in both these areas. To measure the dynamic response of the tested pieces of road infrastructure application of piezoelectric, in particular piezoelectric transducers in the form of piezoelectric films (MFC - Macro Fiber Composite) is proposed. The purpose is to verify the possibility to use composite piezoelectric transducers as sensors used in traffic surveillance systems - innovative methods of controlling the road infrastructure and traffic. Presented paper reports works that were done in order to receive the basic information about analysed systems and their behaviour under excitation by passing vehicles. It is very important to verify if such kind of systems can be controlled by the analysis of the dynamic response of road infrastructure measured using piezoelectric transducers. Obtained results show that it could be possible.

  1. Combined Prediction Model of Death Toll for Road Traffic Accidents Based on Independent and Dependent Variables

    Directory of Open Access Journals (Sweden)

    Feng Zhong-xiang

    2014-01-01

    Full Text Available In order to build a combined model which can meet the variation rule of death toll data for road traffic accidents and can reflect the influence of multiple factors on traffic accidents and improve prediction accuracy for accidents, the Verhulst model was built based on the number of death tolls for road traffic accidents in China from 2002 to 2011; and car ownership, population, GDP, highway freight volume, highway passenger transportation volume, and highway mileage were chosen as the factors to build the death toll multivariate linear regression model. Then the two models were combined to be a combined prediction model which has weight coefficient. Shapley value method was applied to calculate the weight coefficient by assessing contributions. Finally, the combined model was used to recalculate the number of death tolls from 2002 to 2011, and the combined model was compared with the Verhulst and multivariate linear regression models. The results showed that the new model could not only characterize the death toll data characteristics but also quantify the degree of influence to the death toll by each influencing factor and had high accuracy as well as strong practicability.

  2. Online traffic flow model applying dynamic flow-density relation

    International Nuclear Information System (INIS)

    Kim, Y.

    2002-01-01

    This dissertation describes a new approach of the online traffic flow modelling based on the hydrodynamic traffic flow model and an online process to adapt the flow-density relation dynamically. The new modelling approach was tested based on the real traffic situations in various homogeneous motorway sections and a motorway section with ramps and gave encouraging simulation results. This work is composed of two parts: first the analysis of traffic flow characteristics and second the development of a new online traffic flow model applying these characteristics. For homogeneous motorway sections traffic flow is classified into six different traffic states with different characteristics. Delimitation criteria were developed to separate these states. The hysteresis phenomena were analysed during the transitions between these traffic states. The traffic states and the transitions are represented on a states diagram with the flow axis and the density axis. For motorway sections with ramps the complicated traffic flow is simplified and classified into three traffic states depending on the propagation of congestion. The traffic states are represented on a phase diagram with the upstream demand axis and the interaction strength axis which was defined in this research. The states diagram and the phase diagram provide a basis for the development of the dynamic flow-density relation. The first-order hydrodynamic traffic flow model was programmed according to the cell-transmission scheme extended by the modification of flow dependent sending/receiving functions, the classification of cells and the determination strategy for the flow-density relation in the cells. The unreasonable results of macroscopic traffic flow models, which may occur in the first and last cells in certain conditions are alleviated by applying buffer cells between the traffic data and the model. The sending/receiving functions of the cells are determined dynamically based on the classification of the

  3. A Belief-Based Model of Air Traffic Controllers Performing Separation Assurance

    Science.gov (United States)

    Landry, S.J.

    2009-01-01

    A model of an air traffic controller performing a separation assurance task was produced. The model was designed to be simple to use and deploy in a simulator, but still provide realistic behavior. The model is based upon an evaluation of the safety function of the controller for separation assurance, and utilizes fast and frugal heuristics and belief networks to establish a knowledge set for the controller model. Based on this knowledge set, the controller acts to keep aircraft separated. Validation results are provided to demonstrate the model s performance.

  4. A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

    Directory of Open Access Journals (Sweden)

    Meng Fan-Bo

    2016-01-01

    Full Text Available Network traffic is a significantly important parameter for network traffic engineering, while it holds highly dynamic nature in the network. Accordingly, it is difficult and impossible to directly predict traffic amount of end-to-end flows. This paper proposes a new prediction algorithm to network traffic using the wavelet analysis. Firstly, network traffic is converted into the time-frequency domain to capture time-frequency feature of network traffic. Secondly, in different frequency components, we model network traffic in the time-frequency domain. Finally, we build the prediction model about network traffic. At the same time, the corresponding prediction algorithm is presented to attain network traffic prediction. Simulation results indicates that our approach is promising.

  5. Solutions to Improve Road Circulation in the Pitesti City Based on Analysis-Diagnostics of Road Traffic

    Science.gov (United States)

    Vîlcan, A.; Neagu, E.; Badarau Suster, H.; Boroiu, A. A.

    2017-10-01

    Road traffic congestion has become a daily phenomenon in the central area of Pitesti in the peak traffic periods. In order to achieve the mobility plan of Pitesti, an important stage is the diagnostic analysis of the road traffic. For this purpose, the urban road network was formalized through a graph containing the most important 40 intersections and traffic measurements were made at all these intersections and on the main roads connecting the peri-urban area. The data obtained by traffic macrosimulation confirmed the overloading of the street network during peak traffic hours and the analyzes made for various road traffic organization scenarios have shown that there are sustainable solutions for urban mobility only if the road network is fundamentally reconfigured (a belt outside the city and a median ring). Thus, the necessity of realizing the road passage in the Prundu neighbourhood and the finishing of the city belt by realizing the “detour West” of the city is argued. The importance of the work is that it brings scientific arguments for the realization of these road infrastructure projects, integrated in the urban mobility plan, which will base the development strategy of the Pitesti municipality.

  6. Prevalence and regional correlates of road traffic injury among Chinese urban residents: A 21-city population-based study.

    Science.gov (United States)

    Rockett, Ian R H; Jiang, Shuhan; Yang, Qian; Yang, Tingzhong; Yang, Xiaozhao Y; Peng, Sihui; Yu, Lingwei

    2017-08-18

    This study estimated the prevalence of road traffic injury among Chinese urban residents and examined individual and regional-level correlates. A cross-sectional multistage process was used to sample residents from 21 selected cities in China. Survey respondents reported their history of road traffic injury in the past 12 months through a community survey. Multilevel, multivariable logistic regression analysis was used to identify injury correlates. Based on a retrospective 12-month reporting window, road traffic injury prevalence among urban residents was 13.2%. Prevalence of road traffic injury, by type, was 8.7, 8.7, 8.5, and 7.7% in the automobile, bicycle, motorcycle, and pedestrian categories, respectively. Multilevel analysis showed that prevalence of road traffic injury was positively associated with minority status, income, and mental health disorder score at the individual level. Regionally, road traffic injury was associated with geographic location of residence and prevalence of mental health disorders. Both individual and regional-level variables were associated with road traffic injury among Chinese urban residents, a finding whose implications transcend wholesale imported generic solutions. This descriptive research demonstrates an urgent need for longitudinal studies across China on risk and protective factors, in order to inform injury etiology, surveillance, prevention, treatment, and evaluation.

  7. A sensor network architecture for urban traffic state estimation with mixed eulerian/lagrangian sensing based on distributed computing

    KAUST Repository

    Canepa, Edward S.

    2014-01-01

    This article describes a new approach to urban traffic flow sensing using decentralized traffic state estimation. Traffic sensor data is generated both by fixed traffic flow sensor nodes and by probe vehicles equipped with a short range transceiver. The data generated by these sensors is sent to a local coordinator node, that poses the problem of estimating the local state of traffic as a mixed integer linear program (MILP). The resulting optimization program is then solved by the nodes in a distributed manner, using branch-and-bound methods. An optimal amount of noise is then added to the maps before dissemination to a central database. Unlike existing probe-based traffic monitoring systems, this system does not transmit user generated location tracks nor any user presence information to a centralized server, effectively preventing privacy attacks. A simulation of the system performance on computer-generated traffic data shows that the system can be implemented with currently available technology. © 2014 Springer International Publishing Switzerland.

  8. An Algorithm of Traffic Perception of DDoS Attacks against SOA Based on Time United Conditional Entropy

    Directory of Open Access Journals (Sweden)

    Yuntao Zhao

    2016-01-01

    Full Text Available DDoS attacks can prevent legitimate users from accessing the service by consuming resource of the target nodes, whose availability of network and service is exposed to a significant threat. Therefore, DDoS traffic perception is the premise and foundation of the whole system security. In this paper the method of DDoS traffic perception for SOA network based on time united conditional entropy was proposed. According to many-to-one relationship mapping between the source IP address and destination IP addresses of DDoS attacks, traffic characteristics of services are analyzed based on conditional entropy. The algorithm is provided with perception ability of DDoS attacks on SOA services by introducing time dimension. Simulation results show that the novel method can realize DDoS traffic perception with analyzing abrupt variation of conditional entropy in time dimension.

  9. Adaptive control of a Stewart platform-based manipulator

    Science.gov (United States)

    Nguyen, Charles C.; Antrazi, Sami S.; Zhou, Zhen-Lei; Campbell, Charles E., Jr.

    1993-01-01

    A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

  10. Analysis of Roadway Traffic Accidents Based on Rough Sets and Bayesian Networks

    Directory of Open Access Journals (Sweden)

    Xiaoxia Xiong

    2018-02-01

    Full Text Available The paper integrates Rough Sets (RS and Bayesian Networks (BN for roadway traffic accident analysis. RS reduction of attributes is first employed to generate the key set of attributes affecting accident outcomes, which are then fed into a BN structure as nodes for BN construction and accident outcome classification. Such RS-based BN framework combines the advantages of RS in knowledge reduction capability and BN in describing interrelationships among different attributes. The framework is demonstrated using the 100-car naturalistic driving data from Virginia Tech Transportation Institute to predict accident type. Comparative evaluation with the baseline BNs shows the RS-based BNs generally have a higher prediction accuracy and lower network complexity while with comparable prediction coverage and receiver operating characteristic curve area, proving that the proposed RS-based BN overall outperforms the BNs with/without traditional feature selection approaches. The proposed RS-based BN indicates the most significant attributes that affect accident types include pre-crash manoeuvre, driver’s attention from forward roadway to centre mirror, number of secondary tasks undertaken, traffic density, and relation to junction, most of which feature pre-crash driver states and driver behaviours that have not been extensively researched in literature, and could give further insight into the nature of traffic accidents.

  11. Adaptive DFT-Based Interferometer Fringe Tracking

    Directory of Open Access Journals (Sweden)

    Pedretti Ettore

    2005-01-01

    Full Text Available An automatic interferometer fringe tracking system has been developed, implemented, and tested at the Infrared Optical Telescope Array (IOTA Observatory at Mount Hopkins, Arizona. The system can minimize the optical path differences (OPDs for all three baselines of the Michelson stellar interferometer at IOTA. Based on sliding window discrete Fourier-transform (DFT calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on offline data. Implemented in ANSI C on the 266 MHz PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately milliseconds per scan (including all three interferograms, using the science camera and piezo scanners to measure and correct the OPDs. The adaptive DFT-based tracking algorithm should be applicable to other systems where there is a need to detect or track a signal with an approximately constant-frequency carrier pulse. One example of such an application might be to the field of thin-film measurement by ellipsometry, using a broadband light source and a Fourier-transform spectrometer to detect the resulting fringe patterns.

  12. A novel grooming algorithm with the adaptive weight and load balancing for dynamic holding-time-aware traffic in optical networks

    Science.gov (United States)

    Xu, Zhanqi; Huang, Jiangjiang; Zhou, Zhiqiang; Ding, Zhe; Ma, Tao; Wang, Junping

    2013-10-01

    To maximize the resource utilization of optical networks, the dynamic traffic grooming, which could efficiently multiplex many low-speed services arriving dynamically onto high-capacity optical channels, has been studied extensively and used widely. However, the link weights in the existing research works can be improved since they do not adapt to the network status and load well. By exploiting the information on the holding times of the preexisting and new lightpaths, and the requested bandwidth of a user service, this paper proposes a grooming algorithm using Adaptively Weighted Links for Holding-Time-Aware (HTA) (abbreviated as AWL-HTA) traffic, especially in the setup process of new lightpath(s). Therefore, the proposed algorithm can not only establish a lightpath that uses network resource efficiently, but also achieve load balancing. In this paper, the key issues on the link weight assignment and procedure within the AWL-HTA are addressed in detail. Comprehensive simulation and experimental results show that the proposed algorithm has a much lower blocking ratio and latency than other existing algorithms.

  13. Switch Based Opportunistic Spectrum Access for General Primary User Traffic Model

    KAUST Repository

    Gaaloul, Fakhreddine

    2012-06-18

    This letter studies cognitive radio transceiver that can opportunistically use the available channels of primary user (PU). Specifically, we investigate and compare two different opportunistic channel access schemes. The first scheme applies when the secondary user (SU) has access to only one channel. The second scheme, based on channel switching mechanism, applies when the SU has access to multiple channels but can at a given time monitor and access only one channel. For these access schemes, we derive the exact analytical results for the novel performance metrics of average access time and average waiting time under general PU traffic models.

  14. Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study.

    Science.gov (United States)

    Smith, Rachel B; Fecht, Daniela; Gulliver, John; Beevers, Sean D; Dajnak, David; Blangiardo, Marta; Ghosh, Rebecca E; Hansell, Anna L; Kelly, Frank J; Anderson, H Ross; Toledano, Mireille B

    2017-12-05

    Objective  To investigate the relation between exposure to both air and noise pollution from road traffic and birth weight outcomes. Design  Retrospective population based cohort study. Setting  Greater London and surrounding counties up to the M25 motorway (2317 km 2 ), UK, from 2006 to 2010. Participants  540 365 singleton term live births. Main outcome measures  Term low birth weight (LBW), small for gestational age (SGA) at term, and term birth weight. Results  Average air pollutant exposures across pregnancy were 41 μg/m 3 nitrogen dioxide (NO 2 ), 73 μg/m 3 nitrogen oxides (NO x ), 14 μg/m 3 particulate matter with aerodynamic diameter road traffic A-weighted noise levels were 58 dB and 53 dB respectively. Interquartile range increases in NO 2 , NO x , PM 2.5 , PM 10 , and source specific PM 2.5 from traffic exhaust (PM 2.5 traffic exhaust ) and traffic non-exhaust (brake or tyre wear and resuspension) (PM 2.5 traffic non-exhaust ) were associated with 2% to 6% increased odds of term LBW, and 1% to 3% increased odds of term SGA. Air pollutant associations were robust to adjustment for road traffic noise. Trends of decreasing birth weight across increasing road traffic noise categories were observed, but were strongly attenuated when adjusted for primary traffic related air pollutants. Only PM 2.5 traffic exhaust and PM 2.5 were consistently associated with increased risk of term LBW after adjustment for each of the other air pollutants. It was estimated that 3% of term LBW cases in London are directly attributable to residential exposure to PM 2.5 >13.8 μg/m 3 during pregnancy. Conclusions  The findings suggest that air pollution from road traffic in London is adversely affecting fetal growth. The results suggest little evidence for an independent exposure-response effect of traffic related noise on birth weight outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to

  15. Probabilistic Predictions of Traffic Demand for En Route Sectors Based on Individual Flight Data

    Science.gov (United States)

    2010-01-01

    The Traffic Flow Management System (TFMS) predicts the demand for each sector, and traffic managers use these predictions to spot possible congestion and to take measures to prevent it. These predictions of sector demand, however, are currently made ...

  16. A Queuing Model-Based System for Triggering Traffic Flow Management Algorithms, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Next generation air traffic management systems are expected use multiple software tools and quantitative methods for managing traffic flow in the National Airspace....

  17. Possibilistic Clustering Technique-Based Traffic Light Control for Handling Emergency Vehicle

    OpenAIRE

    F. Titouna; S. Benferhat; K. Aksa; C. Titouna

    2012-01-01

    A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good...

  18. Adaptability of the Logistics System in National Economic Mobilization Based on Blocking Flow Theory

    Directory of Open Access Journals (Sweden)

    Xiangyuan Jing

    2014-01-01

    Full Text Available In the process of national economic mobilization, the logistics system usually suffers from negative impact and/or threats of such emergency events as wars and accidents, which implies that adaptability of the logistics system directly determines realization of economic mobilization. And where the real-time rescue operation is concerned, heavy traffic congestion is likely to cause a great loss of or damage to human beings and their properties. To deal with this situation, this article constructs a blocking-resistance optimum model and an optimum restructuring model based on blocking flow theories, of which both are illustrated by numerical cases and compared in characteristics and application. The design of these two models is expected to eliminate or alleviate the congestion situation occurring in the logistics system, thus effectively enhancing its adaptability in the national economic mobilization process.

  19. A method for classification of network traffic based on C5.0 Machine Learning Algorithm

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Riaz, M. Tahir; Pedersen, Jens Myrup

    2012-01-01

    current network traffic. To overcome the drawbacks of existing methods for traffic classification, usage of C5.0 Machine Learning Algorithm (MLA) was proposed. On the basis of statistical traffic information received from volunteers and C5.0 algorithm we constructed a boosted classifier, which was shown...

  20. Research in Neural Network Based Adaptive Control

    National Research Council Canada - National Science Library

    Calise, Anthony

    2000-01-01

    .... We regard this as a major step towards flight certification of adaptive controllers. The approach is more general in that it permits a broad class of input nonlinearities, including such effects as discrete and bang/bang control...

  1. Traffic signals - alternative method for emissions reduction; Liikennevaloillako paeaestoet alas

    Energy Technology Data Exchange (ETDEWEB)

    Niittymaeki, J. [Helsinki Univ. of Technology, Espoo (Finland)

    2001-07-01

    powered vehicles are lower than those of gasoline fueled vehicles. The minimum of fuel consumption in traffic is obtained in all the traffic volumes when the periods are longer than the minimum of the delays is. Traffic adaptive control means the control of transport so that the operation of the traffic signals is based on the data collected from traffic magnitude sensors and push buttons for pedestrians. Phase sequence, in which the phase for those going strait forward is immediately after those turning in the junction appeared to be, on the basis of the delays in the junction, stopping likelihood, fuel consumption and emissions, the best solution when the rate between the traffic rates of the main way and the side ways is low (1/5). In this case the advantages of the delays were, depending on the traffic rate of the main road, 0.3 - 2.4 seconds, the savings in fuel consumption 0.2 - 4.4 l/h and savings in total emissions 20 - 770 g/h. Delays and the likelihood of stoppages, as well as the environmental effects of transport can be reduced by proper selection of standstill periods. New methods like fuzzy logic, neural networks and generic algorithms are becoming a part of the adaptive traffic signalling. The periods of present traffic signals have been selected so that they minimize the delays. Minimization of the fuels consumption would cause relatively large increase in delays, so probably it will not become a realistic alternative for traffic signalling.

  2. Development of a Software Based Firewall System for Computer Network Traffic Control

    Directory of Open Access Journals (Sweden)

    Ikhajamgbe OYAKHILOME

    2009-12-01

    Full Text Available The connection of an internal network to an external network such as Internet has made it vulnerable to attacks. One class of network attack is unauthorized penetration into network due to the openness of networks. It is possible for hackers to sum access to an internal network, this pose great danger to the network and network resources. Our objective and major concern of network design was to build a secured network, based on software firewall that ensured the integrity and confidentiality of information on the network. We studied several mechanisms to achieve this; one of such mechanism is the implementation of firewall system as a network defence. Our developed firewall has the ability to determine which network traffic should be allowed in or out of the network. Part of our studied work was also channelled towards a comprehensive study of hardware firewall security system with the aim of developing this software based firewall system. Our software firewall goes a long way in protecting an internal network from external unauthorized traffic penetration. We included an anti virus software which is lacking in most firewalls.

  3. Traffic Light Options

    DEFF Research Database (Denmark)

    Jørgensen, Peter Løchte

    This paper introduces, prices, and analyzes traffic light options. The traffic light option is an innovative structured OTC derivative developed independently by several London-based investment banks to suit the needs of Danish life and pension (L&P) companies, which must comply with the traffic...... 2006, and supervisory authorities in many other European countries have implemented similar regulation. Traffic light options are therefore likely to attract the attention of a wider audience of pension fund managers in the future. Focusing on the valuation of the traffic light option we set up a Black...... light scenarios. These stress scenarios entail drops in interest rates as well as in stock prices, and traffic light options are thus designed to pay off and preserve sufficient capital when interest rates and stock prices fall simultaneously. Sweden's FSA implemented a traffic light system in January...

  4. Using stationary image based data collection method for evaluation of traffic sign condition

    Directory of Open Access Journals (Sweden)

    Majid Khalilikhah

    2016-12-01

    Full Text Available Transportation asset management helps monitor the transportation systems and optimize the construction, operation, and maintenance of assets. Many state Department of Transportations (DOTs have already established asset management systems for high cost and low quantity assets, e.g., bridge and tunnel assets. However, due to the sheer number of traffic signs deployed by DOTs, statewide sign inventory and condition information are not well developed. Currently, using handheld devices is the most selected method by agencies to measure signs. To address safety challenge and high cost of data collection, an innovative stationary image based method has recently been proposed. This paper discusses the advantages and disadvantages of such image based method over using handheld devices in terms of the accuracy, possibility and consistency of data, speed, safety, maintenance, and cost. At its completion, this study provides suggestions to tackle the issues associated with image based method.

  5. Epidemiology of traffic injuries and motor vehicles utilization in the Capital of Iran: A population based study

    Directory of Open Access Journals (Sweden)

    Soori Hamid

    2011-06-01

    Full Text Available Abstract Background Road traffic injuries are a serious public health problem worldwide. The incidence rate of fatal road traffic injuries is 26.4 per 100000 in the Eastern Mediterranean Region. Road traffic injuries are a major public health problem in Iran. Different routine sources are available for road traffic injuries in Iran, but they present several limitations. This study aimed to determine the epidemiology of road traffic injuries in greater Tehran, using a population-based approach which is less prone to under-estimation compared to service-based data. Methods In the year 2008, 2488 households were randomly selected for a face to face interview. Trained interviewers referred to the selected households to collect the subjects' demographic information, as well as their motor vehicle utilization and traffic injuries during the year prior to data collection. All interviews were recorded using a digital voice recorder and reviewed by a quality control team the day after the interview. The Student's t-test and ANOVA were used to analyze continuous variables. Chi-square test -including a test for trend for ordinal data- was used to analyze categorical variables. Ninety-five percent confidence interval was calculated for point estimates of incidences using Poisson or binomial distribution assumptions accordingly. Results There were 119 traffic injury cases including 3 deaths (33 per 100 000 in the survey sample (n = 9100. The annual incidence of all traffic injuries for 1000 population was 13.1 (95% CI: 10.8 - 15.6, and that of fatal traffic injuries was 33.0 per 100 000 population (95% CI: 6.80 - 96.32. The annual incidence of collision traffic injury for 1000 motorcycles was 95. Conclusion This population-based study demonstrates that the morbidity rate of RTIs is about ten times higher than the national figures reported by other available sources; and this can serve as an important warning to countries like Iran to prioritize this issue in

  6. Inkjet-based adaptive planarization (Conference Presentation)

    Science.gov (United States)

    Singhal, Shrawan; Grigas, Michelle M.; Khusnatdinov, Niyaz; Sreenivasan, Srinivasan V.

    2017-03-01

    that should have been polished away. Preventive techniques like dummy fill and patterned resist can be used to reduce the variation in pattern density. These techniques increase the complexity of the planarization process and significantly limit the device design flexibility. Contact Planarization (CP) has also been reported as an alternative to the CMP processing [7], [8]. A substrate is spin coated with a photo curable material and pre baked to remove residual solvent. An ultra-flat surface or an optical flat is pressed on the spin-coated wafer. The material is forced to reflow. Pressure is used to spread out material evenly and achieve global planarization. The substrate is then exposed to UV radiation to harden the photo curable material. Although attractive, this process is not adaptive as it does not account for differences in surface topography of the wafer and the optical flat, nor can it address all the parasitics that arise during the process itself. The optical flat leads to undesirable planarization of even the substrate nominal shape and nanotopography, which corrupts the final film thickness profile. Hence, it becomes extremely difficult to eliminate this signature to a desirable extent without introducing other parasitic signatures. An example of this is shown in Figure 1. In this paper, a novel adaptive planarization process has been presented that potentially addresses the problems associated with planarization of varying pattern density, even in the presence of pre-existing substrate topography [9]. This process is called Inkjet-enabled Adaptive Planarization (IAP). The IAP process uses an inverse optimization scheme, built around a validated fluid mechanics-based forward model [10], that takes the pre-existing substrate topography and pattern layout as inputs. It then generates an inkjet drop pattern with a material distribution that is correlated with the desired planarization film profile. This allows a contiguous film to be formed with the desired

  7. Community-based Adaptation: Lessons from the Development Marketplace 2009 on Adaptation to Climate Change

    OpenAIRE

    Rasmus Heltberg; Radhika Prabhu; Habiba Gitay

    2010-01-01

    The Development Marketplace 2009 focused on adaptation to climate change. This paper identifies lessons from the Marketplace and assesses their implications for adaptation support. The findings are based on: statistical tabulation of all proposals; in-depth qualitative and quantitative analysis of the 346 semi-finalists; and interviews with finalists and assessors. Proposals were fuelled b...

  8. Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

    KAUST Repository

    Rakia, Tamer

    2015-07-23

    Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

  9. The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

    Science.gov (United States)

    Ansari, Nirwan; Liu, Dequan

    1991-01-01

    A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

  10. Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

    Science.gov (United States)

    Desai, Prajakta; Loke, Seng W; Desai, Aniruddha

    2017-01-01

    Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

  11. Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

    Directory of Open Access Journals (Sweden)

    Prajakta Desai

    Full Text Available Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN, wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction, across variations in: (a environmental parameters such as road network topology and configuration; (b algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

  12. Turbulent Output-Based Anisotropic Adaptation

    Science.gov (United States)

    Park, Michael A.; Carlson, Jan-Renee

    2010-01-01

    Controlling discretization error is a remaining challenge for computational fluid dynamics simulation. Grid adaptation is applied to reduce estimated discretization error in drag or pressure integral output functions. To enable application to high O(10(exp 7)) Reynolds number turbulent flows, a hybrid approach is utilized that freezes the near-wall boundary layer grids and adapts the grid away from the no slip boundaries. The hybrid approach is not applicable to problems with under resolved initial boundary layer grids, but is a powerful technique for problems with important off-body anisotropic features. Supersonic nozzle plume, turbulent flat plate, and shock-boundary layer interaction examples are presented with comparisons to experimental measurements of pressure and velocity. Adapted grids are produced that resolve off-body features in locations that are not known a priori.

  13. Creating Evidence-Based Research in Adapted Physical Activity

    Science.gov (United States)

    Reid, Greg; Bouffard, Marcel; MacDonald, Catherine

    2012-01-01

    Professional practice guided by the best research evidence is a usually referred to as evidence-based practice. The aim of the present paper is to describe five fundamental beliefs of adapted physical activity practices that should be considered in an 8-step research model to create evidence-based research in adapted physical activity. The five…

  14. Smart Pedestrian Crossing Management at Traffic Light Junctions through a Fuzzy-Based Approach

    Directory of Open Access Journals (Sweden)

    Giovanni Pau

    2018-02-01

    Full Text Available In the last few years, numerous research efforts have been conducted to merge the Internet of Things (IoT with smart city environments. The goal to make a city “smart” is arising as a possible solution to lessen the issues caused by the urban population growth and fast urbanization. Attention also has focused on the pedestrian crossings because they are one of the most dangerous places in the transport field. Information and Communications Technologies (ICT can undoubtedly be an excellent support in developing infrastructures that can best manage pedestrian crossing. For this reason, this paper introduces a fuzzy logic-based solution able to manage dynamically the traffic lights’ phases in signalized pedestrian crossings. The proposed approach provides the possibility to change the phases of the traffic light taking into account the time of the day and the number of pedestrians about to cross the road. The paper presents a thorough description of the fuzzy logic controller configuration, an in-depth analysis of the application scenario and simulative assessments obtained through Vissim simulations.

  15. A video-based approach to calibrating car-following parameters in VISSIM for urban traffic

    Directory of Open Access Journals (Sweden)

    Zhengyang Lu

    2016-08-01

    Full Text Available Microscopic simulation models need to be calibrated to represent realistic local traffic conditions. Traditional calibration methods are conducted by searching for the model parameter set that minimizes the discrepancies of certain macroscopic metrics between simulation results and field observations. However, this process could easily lead to inappropriate selection of calibration parameters and thus erroneous simulation results. This paper proposes a video-based approach to incorporate direct measurements of car-following parameters into the process of VISSIM model calibration. The proposed method applies automated video processing techniques to extract vehicle trajectory data and utilizes the trajectory data to determine values of certain car-following parameters in VISSIM. This paper first describes the calibration procedure step by step, and then applies the method to a case study of simulating traffic at a signalized intersection in VISSIM. From the field-collected video footage, trajectories of 1229 through-movement vehicles were extracted and analyzed to calibrate three car-following parameters regarding desired speed, desired acceleration, and safe following distance, respectively. The case study demonstrates the advantages and feasibility of the proposed approach.

  16. Validation of Microscopic Traffic Models Based on GPS Precise Measurement of Vehicle Dynamics

    Directory of Open Access Journals (Sweden)

    Tomas Apeltauer

    2013-04-01

    Full Text Available A necessary stage in the development of traffic models is model validation, where the developed model is verified by comparing its outputs with observed data. The most frequently used variables are average value of speed, flow intensity and flow density (during a selected period.It is possible to use these values for the calibration of macroscopic models, but one cannot always obtain a relevant microscopic dynamic model in this way. A typical use of the microsimulation models is the capacity assessment, where this sort of data (flow, speed and queues is considered to be standard and sufficient. However microsimulation is also increasingly being used for other assessments (e.g. noise and emissions where the correct representation of each vehicle’s acceleration and deceleration plays a crucial role. Another emerging area is the use of microsimulation to predict near-miss situations and conflicts to identify dangerous and accident prone locations. In such assessments the vehicle trajectory, distance from other vehicles as well as velocity and acceleration are very important.Additional source of data, which can be used to validate vehicle dynamics in microsimulation models, is the Global Positioning System (GPS that is able to determine vehicle position with centimeter accuracy.In this article we discuss validation of selected microscopic traffic models, based on the comparison of simulated vehicle dynamics with observed dynamic characteristics of vehicles recorded by the precise geodetic GPS equipment.

  17. Electromechanical-Traffic Model of Compression-Based Piezoelectric Energy Harvesting

    Directory of Open Access Journals (Sweden)

    Kok B.C.

    2016-01-01

    Full Text Available Piezoelectric energy harvesting has advantages over other alternative sources due to its large power density, ease of applications, and capability to be fabricated at different scales: macro, micro, and nano. This paper presents an electromechanical-traffic model for roadway compression-based piezoelectric energy harvesting system. A two-degree-of-freedom (2-DOF electromechanical model has been developed for the piezoelectric energy harvesting unit to define its performance in power generation under a number of external excitations on road surface. Lead Zirconate Titanate (PZT-5H is selected as the piezoelectric material to be used in this paper due to its high Piezoelectric Charge Constant (d and Piezoelectric Voltage Constant (g values. The main source of vibration energy that has been considered in this paper is the moving vehicle on the road. The effect of various frequencies on possible generated power caused by different vibration characteristics of moving vehicle has been studied. A single unit of circle-shape Piezoelectric Cymbal Transducer (PCT with diameter of 32 mm and thickness of 0.3 mm be able to generate about 0.12 mW and 13 mW of electric power under 4 Hz and 20 Hz of excitation, respectively. The estimated power to be generated for multiple arrays of PCT is approximately 150 kW/ km. Thus, the developed electromechanical-traffic model has enormous potential to be used in estimating the macro scale of roadway power generation system.

  18. Predicting long-term average concentrations of traffic-related air pollutants using GIS-based information

    Science.gov (United States)

    Hochadel, Matthias; Heinrich, Joachim; Gehring, Ulrike; Morgenstern, Verena; Kuhlbusch, Thomas; Link, Elke; Wichmann, H.-Erich; Krämer, Ursula

    Global regression models were developed to estimate individual levels of long-term exposure to traffic-related air pollutants. The models are based on data of a one-year measurement programme including geographic data on traffic and population densities. This investigation is part of a cohort study on the impact of traffic-related air pollution on respiratory health, conducted at the westerly end of the Ruhr-area in North-Rhine Westphalia, Germany. Concentrations of NO 2, fine particle mass (PM 2.5) and filter absorbance of PM 2.5 as a marker for soot were measured at 40 sites spread throughout the study region. Fourteen-day samples were taken between March 2002 and March 2003 for each season and site. Annual average concentrations for the sites were determined after adjustment for temporal variation. Information on traffic counts in major roads, building densities and community population figures were collected in a geographical information system (GIS). This information was used to calculate different potential traffic-based predictors: (a) daily traffic flow and maximum traffic intensity of buffers with radii from 50 to 10 000 m and (b) distances to main roads and highways. NO 2 concentration and PM 2.5 absorbance were strongly correlated with the traffic-based variables. Linear regression prediction models, which involved predictors with radii of 50 to 1000 m, were developed for the Wesel region where most of the cohort members lived. They reached a model fit ( R2) of 0.81 and 0.65 for NO 2 and PM 2.5 absorbance, respectively. Regression models for the whole area required larger spatial scales and reached R2=0.90 and 0.82. Comparison of predicted values with NO 2 measurements at independent public monitoring stations showed a satisfactory association ( r=0.66). PM 2.5 concentration, however, was only slightly correlated and thus poorly predictable by traffic-based variables ( rGIS-based regression models offer a promising approach to assess individual levels of

  19. Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

    Directory of Open Access Journals (Sweden)

    Laisen Nie

    2018-01-01

    Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

  20. Traffic Accident Propagation Properties and Control Measures for Urban Links Based on Cellular Automata

    Directory of Open Access Journals (Sweden)

    Xian-sheng Li

    2013-01-01

    Full Text Available With the rapid development of urban transport and the sharp increase in vehicle population, traffic accidents form one of the most important causes of urban traffic congestion other than the imbalance between traffic supply and demand. Traffic congestion causes severe problems, such as environment contamination and energy dissipation. Therefore, it would be useful to analyze the congestion propagation characteristics after traffic accidents. Numerical analysis and computer simulation were two of the typical methods used at present to study the traffic congestion propagation properties. The latter was more widespread as it is more consistent with the actual traffic flow and more visual than the former. In this paper, an improved cellular automata (CA model was presented to analyze traffic congestion propagation properties and to evaluate control strategies. In order to apply them to urban traffic flow simulation, the CA models have been improved and expanded on. Computer simulations were built for congestion not only extending to the upstream intersection, but also the upstream intersection and the entire road network, respectively. Congestion propagation characteristics after road traffic accidents were obtained, and controls of different severities and durations were analyzed. The results provide the theoretical foundation and practical means for the control of congestion.

  1. A Method for Traffic Congestion Clustering Judgment Based on Grey Relational Analysis

    Directory of Open Access Journals (Sweden)

    Yingya Zhang

    2016-05-01

    Full Text Available Traffic congestion clustering judgment is a fundamental problem in the study of traffic jam warning. However, it is not satisfactory to judge traffic congestion degrees using only vehicle speed. In this paper, we collect traffic flow information with three properties (traffic flow velocity, traffic flow density and traffic volume of urban trunk roads, which is used to judge the traffic congestion degree. We first define a grey relational clustering model by leveraging grey relational analysis and rough set theory to mine relationships of multidimensional-attribute information. Then, we propose a grey relational membership degree rank clustering algorithm (GMRC to discriminant clustering priority and further analyze the urban traffic congestion degree. Our experimental results show that the average accuracy of the GMRC algorithm is 24.9% greater than that of the K-means algorithm and 30.8% greater than that of the Fuzzy C-Means (FCM algorithm. Furthermore, we find that our method can be more conducive to dynamic traffic warnings.

  2. Adaptive Social Learning Based on Crowdsourcing

    Science.gov (United States)

    Karataev, Evgeny; Zadorozhny, Vladimir

    2017-01-01

    Many techniques have been developed to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the web and adaptive educational hypermedia systems. While the web enables users to interact and collaborate with each other to create, organize, and share knowledge via…

  3. Adaptive Central Force Optimization Algorithm Based on the Stability Analysis

    Directory of Open Access Journals (Sweden)

    Weiyi Qian

    2015-01-01

    Full Text Available In order to enhance the convergence capability of the central force optimization (CFO algorithm, an adaptive central force optimization (ACFO algorithm is presented by introducing an adaptive weight and defining an adaptive gravitational constant. The adaptive weight and gravitational constant are selected based on the stability theory of discrete time-varying dynamic systems. The convergence capability of ACFO algorithm is compared with the other improved CFO algorithm and evolutionary-based algorithm using 23 unimodal and multimodal benchmark functions. Experiments results show that ACFO substantially enhances the performance of CFO in terms of global optimality and solution accuracy.

  4. A GPS-based Real-time Road Traffic Monitoring System

    Science.gov (United States)

    Tanti, Kamal Kumar

    In recent years, monitoring systems are astonishingly inclined towards ever more automatic; reliably interconnected, distributed and autonomous operation. Specifically, the measurement, logging, data processing and interpretation activities may be carried out by separate units at different locations in near real-time. The recent evolution of mobile communication devices and communication technologies has fostered a growing interest in the GIS & GPS-based location-aware systems and services. This paper describes a real-time road traffic monitoring system based on integrated mobile field devices (GPS/GSM/IOs) working in tandem with advanced GIS-based application software providing on-the-fly authentications for real-time monitoring and security enhancement. The described system is developed as a fully automated, continuous, real-time monitoring system that employs GPS sensors and Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based on the requirements of client’s satisfaction. Due to the modular architecture of the system, other sensor types may be supported with minimal effort. Data on the distributed network & measurements are transmitted via cellular SIM cards to a Control Unit, which provides for post-processing and network management. The Control Unit may be remotely accessed via an Internet connection. The new system will not only provide more consistent data about the road traffic conditions but also will provide methods for integrating with other Intelligent Transportation Systems (ITS). For communication between the mobile device and central monitoring service GSM technology is used. The resulting system is characterized by autonomy, reliability and a high degree of automation.

  5. Multi-Path OD-Matrix Estimation (MPME) based on Stochastic User Equilibrium Traffic Assignment

    DEFF Research Database (Denmark)

    Nielsen, Otto Anker

    1997-01-01

    Most conventional methods for estimating trip matrices from traffic counts assume either that the counts are error-free, determin-istic variables or they use a simplified traffic assignment model. Without these assumptions, the methods often demand prohibitive calculation times. The paper presents...... a matrix-estimation method, 'Multiple Path Matrix Estimation' (MPME), that is able to handle traffic counts with inconsistencies and uncertainties. In addition, the matrix reflects the route choice patterns given by traffic assignment models following the Method of Successive Averages (MSA). Actually...... million inhabitants). In all cases, the method gave lower deviations between traffic counts and estimated traffic than other tested methods. The method converged smoothly within calculation times of a few hours....

  6. Adaptive Feature Based Control of Compact Disk Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Vidal, Enrique Sanchez

    2005-01-01

    -players playing CDs with surface fault is derived and described. This feature based control scheme uses precomputed base to remove the surface fault influence from the position measurements. In this paper an adaptive version of the feature based control scheme is proposed and described. This adaptive scheme can...... result that the adaptive scheme clearly adapts better to the given faults compared with the non-adaptive version of the feature based control scheme.......Many have experienced the problem that their Compact Disc players have difficulties playing Compact Discs with surface faults like scratches and fingerprints. The cause of this is due to the two servo control loops used to keep the Optical Pick-up Unit focused and radially on the information track...

  7. Model for Detection and Classification of DDoS Traffic Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    D. Peraković

    2017-06-01

    Full Text Available Detection of DDoS (Distributed Denial of Service traffic is of great importance for the availability protection of services and other information and communication resources. The research presented in this paper shows the application of artificial neural networks in the development of detection and classification model for three types of DDoS attacks and legitimate network traffic. Simulation results of developed model showed accuracy of 95.6% in classification of pre-defined classes of traffic.

  8. CMAC-based adaptive backstepping synchronization of uncertain chaotic systems

    International Nuclear Information System (INIS)

    Lin, C.-M.; Peng, Y.-F.; Lin, M.-H.

    2009-01-01

    This study proposes an adaptive backstepping control system for synchronizing uncertain chaotic system by using cerebellar model articulation controller (CMAC). CMAC is a nonlinear network with simple computation, good generalization capability and fast learning property. The proposed CMAC-based adaptive backstepping control (CABC) system uses backstepping method and adaptive cerebellar model articulation controller (ACMAC) for synchronizing uncertain chaotic system. Finally, simulation results for the Genesio system are presented to illustrate the effectiveness of the proposed control system.

  9. A Priority-Based Adaptive MAC Protocol for Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Sabin Bhandari

    2016-03-01

    Full Text Available In wireless body area networks (WBANs, various sensors and actuators are placed on/inside the human body and connected wirelessly. WBANs have specific requirements for healthcare and medical applications, hence, standard protocols like the IEEE 802.15.4 cannot fulfill all the requirements. Consequently, many medium access control (MAC protocols, mostly derived from the IEEE 802.15.4 superframe structure, have been studied. Nevertheless, they do not support a differentiated quality of service (QoS for the various forms of traffic coexisting in a WBAN. In particular, a QoS-aware MAC protocol is essential for WBANs operating in the unlicensed Industrial, Scientific, and Medical (ISM bands, because different wireless services like Bluetooth, WiFi, and Zigbee may coexist there and cause severe interference. In this paper, we propose a priority-based adaptive MAC (PA-MAC protocol for WBANs in unlicensed bands, which allocates time slots dynamically, based on the traffic priority. Further, multiple channels are effectively utilized to reduce access delays in a WBAN, in the presence of coexisting systems. Our performance evaluation results show that the proposed PA-MAC outperforms the IEEE 802.15.4 MAC and the conventional priority-based MAC in terms of the average transmission time, throughput, energy consumption, and data collision ratio.

  10. A Priority-Based Adaptive MAC Protocol for Wireless Body Area Networks.

    Science.gov (United States)

    Bhandari, Sabin; Moh, Sangman

    2016-03-18

    In wireless body area networks (WBANs), various sensors and actuators are placed on/inside the human body and connected wirelessly. WBANs have specific requirements for healthcare and medical applications, hence, standard protocols like the IEEE 802.15.4 cannot fulfill all the requirements. Consequently, many medium access control (MAC) protocols, mostly derived from the IEEE 802.15.4 superframe structure, have been studied. Nevertheless, they do not support a differentiated quality of service (QoS) for the various forms of traffic coexisting in a WBAN. In particular, a QoS-aware MAC protocol is essential for WBANs operating in the unlicensed Industrial, Scientific, and Medical (ISM) bands, because different wireless services like Bluetooth, WiFi, and Zigbee may coexist there and cause severe interference. In this paper, we propose a priority-based adaptive MAC (PA-MAC) protocol for WBANs in unlicensed bands, which allocates time slots dynamically, based on the traffic priority. Further, multiple channels are effectively utilized to reduce access delays in a WBAN, in the presence of coexisting systems. Our performance evaluation results show that the proposed PA-MAC outperforms the IEEE 802.15.4 MAC and the conventional priority-based MAC in terms of the average transmission time, throughput, energy consumption, and data collision ratio.

  11. Adaptive skin detection based on online training

    Science.gov (United States)

    Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

    2007-11-01

    Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

  12. Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

    Science.gov (United States)

    Peters, Mark; Boisvert, Ben; Escala, Diego

    2009-01-01

    Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic

  13. Analysis of Traffic Engineering capabilities for SDN-based Data Center Networks

    DEFF Research Database (Denmark)

    Pilimon, Artur; Kentis, Angelos Mimidis; Ruepp, Sarah Renée

    2018-01-01

    techniques focusing on their limitations. Then, it highlights the benefits of incorporating the Software Defined Networking (SDN) paradigm to address these limitations. Furthermore, it illustrates two methodologies and addresses the scalability aspect of DCN-oriented TE, network and service testing...... Center Networks (DCN), thus creating the need to evolve them. Traffic Engineering (TE) has long been the way of attacking this problem, but as with DCN, needs to evolve by encompassing new technologies and paradigms. This paper provides a comprehensive analysis of current DCN operational and TE......In the recent years more and more existing services have moved from local execution environments into the cloud. In addition, new cloud-based services are emerging, which are characterized by very stringent delay requirements. This trend puts a stress in the existing monolithic architecture of Data...

  14. Priority-Based Resource Allocation for Downlink OFDMA Systems Supporting RT and NRT Traffics

    DEFF Research Database (Denmark)

    Wang, Hua; Dittmann, Lars

    2008-01-01

    Efficient radio resource management is essential in Quality-of-Service (QoS) provisioning for wireless communication networks. In this paper, we propose a novel priority-based packet scheduling algorithm for downlink OFDMA systems. The proposed algorithm is designed to support heterogeneous...... applications consisting of both real-time (RT) and non-real-time (NRT) traffics with the objective to increase the spectrum efficiency while satisfying diverse QoS requirements. It tightly couples the subchannel allocation and packet scheduling together through an integrated cross-layer approach in which each...... show that the proposed algorithm can significantly improve the system performance in terms of high spectral efficiency and low outage probability compared to conventional packet scheduling algorithms, thus is very suitable for the downlink of current OFDMA systems....

  15. Neural network based adaptive control for nonlinear dynamic regimes

    Science.gov (United States)

    Shin, Yoonghyun

    Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

  16. Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

    Science.gov (United States)

    Huang, Shih-Chia; Chen, Bo-Hao

    2013-12-01

    Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76

  17. Adaptive and non-adaptive data hiding methods for grayscale images based on modulus function

    Directory of Open Access Journals (Sweden)

    Najme Maleki

    2014-07-01

    Full Text Available This paper presents two adaptive and non-adaptive data hiding methods for grayscale images based on modulus function. Our adaptive scheme is based on the concept of human vision sensitivity, so the pixels in edge areas than to smooth areas can tolerate much more changes without making visible distortion for human eyes. In our adaptive scheme, the average differencing value of four neighborhood pixels into a block via a threshold secret key determines whether current block is located in edge or smooth area. Pixels in the edge areas are embedded by Q-bit of secret data with a larger value of Q than that of pixels placed in smooth areas. Also in this scholar, we represent one non-adaptive data hiding algorithm. Our non-adaptive scheme, via an error reduction procedure, produces a high visual quality for stego-image. The proposed schemes present several advantages. 1-of aspects the embedding capacity and visual quality of stego-image are scalable. In other words, the embedding rate as well as the image quality can be scaled for practical applications 2-the high embedding capacity with minimal visual distortion can be achieved, 3-our methods require little memory space for secret data embedding and extracting phases, 4-secret keys have used to protect of the embedded secret data. Thus, level of security is high, 5-the problem of overflow or underflow does not occur. Experimental results indicated that the proposed adaptive scheme significantly is superior to the currently existing scheme, in terms of stego-image visual quality, embedding capacity and level of security and also our non-adaptive method is better than other non-adaptive methods, in view of stego-image quality. Results show which our adaptive algorithm can resist against the RS steganalysis attack.

  18. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

    Directory of Open Access Journals (Sweden)

    Jisheng Zhang

    2015-06-01

    Full Text Available It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks.

  19. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications.

    Science.gov (United States)

    Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

    2015-06-12

    It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs' route planning for small and medium-scale networks.

  20. Numerical study of traffic flow considering the probability density distribution of the traffic density

    Science.gov (United States)

    Guo, L. M.; Zhu, H. B.; Zhang, N. X.

    The probability density distribution of the traffic density is analyzed based on the empirical data. It is found that the beta distribution can fit the result obtained from the measured traffic density perfectly. Then a modified traffic model is proposed to simulate the microscopic traffic flow, in which the probability density distribution of the traffic density is taken into account. The model also contains the behavior of drivers’ speed adaptation by taking into account the driving behavior difference and the dynamic headway. Accompanied by presenting the flux-density diagrams, the velocity evolution diagrams and the spatial-temporal profiles of vehicles are also given. The synchronized flow phase and the wide moving jam phase are indicated, which is the challenge for the cellular automata traffic model. Furthermore the phenomenon of the high speed car-following is exhibited, which has been observed in the measured data previously. The results set demonstrate the effectiveness of the proposed model in detecting the complicated dynamic phenomena of the traffic flow.

  1. Swarm-based adaptation: wayfinding support for lifelong learners

    NARCIS (Netherlands)

    Tattersall, Colin; Van den Berg, Bert; Van Es, René; Janssen, José; Manderveld, Jocelyn; Koper, Rob

    2004-01-01

    Powerpoint presentation of a paper with the same title (Swarm-Based Adaptation: Wayfinding Support for Lifelong Learners) at the Adaptive Hypermedia 2004 Conference, held in Eindhoven, The Netherlands, August 2004. The presentation explains the use of self-organisation principles (feedback,

  2. Immersion and Invariance Based Nonlinear Adaptive Flight Control

    NARCIS (Netherlands)

    Sonneveldt, L.; Van Oort, E.R.; Chu, Q.P.; Mulder, J.A.

    2010-01-01

    In this paper a theoretical framework for nonlinear adaptive flight control is developed and applied to a simplified, over-actuated nonlinear fighter aircraft model. The framework is based on a modular adaptive backstepping scheme with a new type of nonlinear estimator. The nonlinear estimator is

  3. Measuring the Complexity of Self-Organizing Traffic Lights

    Directory of Open Access Journals (Sweden)

    Darío Zubillaga

    2014-04-01

    Full Text Available We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.

  4. Variable Step Size Maximum Correntropy Criteria Based Adaptive Filtering Algorithm

    Directory of Open Access Journals (Sweden)

    S. Radhika

    2016-04-01

    Full Text Available Maximum correntropy criterion (MCC based adaptive filters are found to be robust against impulsive interference. This paper proposes a novel MCC based adaptive filter with variable step size in order to obtain improved performance in terms of both convergence rate and steady state error with robustness against impulsive interference. The optimal variable step size is obtained by minimizing the Mean Square Deviation (MSD error from one iteration to the other. Simulation results in the context of a highly impulsive system identification scenario show that the proposed algorithm has faster convergence and lesser steady state error than the conventional MCC based adaptive filters.

  5. An Algorithm of Traffic Perception of DDoS Attacks against SOA Based on Time United Conditional Entropy

    OpenAIRE

    Yuntao Zhao; Hengchi Liu; Yongxin Feng

    2016-01-01

    DDoS attacks can prevent legitimate users from accessing the service by consuming resource of the target nodes, whose availability of network and service is exposed to a significant threat. Therefore, DDoS traffic perception is the premise and foundation of the whole system security. In this paper the method of DDoS traffic perception for SOA network based on time united conditional entropy was proposed. According to many-to-one relationship mapping between the source IP address and destinati...

  6. Effect of traffic restriction on reducing ambient volatile organic compounds (VOCs): Observation-based evaluation during a traffic restriction drill in Guangzhou, China

    Science.gov (United States)

    Huang, Xinyu; Zhang, Yanli; Yang, Weiqiang; Huang, Zuzhao; Wang, Yujun; Zhang, Zhou; He, Quanfu; Lü, Sujun; Huang, Zhonghui; Bi, Xinhui; Wang, Xinming

    2017-07-01

    Traffic restriction (TR) is a widely adopted control measure in case of heavy air pollution particularly in urban areas, yet it is hard to evaluate the effect of TR on reducing VOC emissions based on monitoring data since ambient VOC mixing ratios are influenced not only by source emissions but also by meteorological conditions and atmospheric degradation. Here we collected air samples for analysis of VOCs before, during and after a TR drill carried out in Guangzhou in September 2010 at both a roadside and a rooftop (∼50 m above the ground) site. TR measures mainly included the "odd-even license" rule and banning high-emitting "yellow label" vehicles. The mixing ratios of non-methane hydrocarbons (NMHCs) did not show significant changes at the roadside site with total NMHCs of 39.0 ± 11.8 ppbv during non-TR period and 39.1 ± 14.8 ppbv during TR period, whereas total NMHCs decreased from 30.4 ± 14.3 ppbv during the non-TR period to 22.1 ± 10.6 ppbv during the TR period at rooftop site. However, the ratios of methyl tert-butyl ether (MTBE), benzene and toluene against carbon monoxide (MTBE/CO, T/CO and B/CO) at the both sampling sites dropped significantly. The ratios of toluene to benzene (T/B) instead increased significantly. Changes in these ratios all consistently indicated reduced input from traffic emissions particularly gasoline vehicles. Source attribution by positive matrix factorization (PMF) confirmed that during the TR period gasoline vehicles contributed less VOCs in percentages while industrial sources, biomass burning and LPG shared larger percentages. Assuming that emissions from industrial sources remained unchanged during the TR and non-TR periods, we further used the PMF-retrieved contribution percentages to deduce the reduction rate of traffic-related VOC emissions, and obtained a reduction rate of 31% based on monitoring data at the roadside site and of 34% based on the monitoring data at the rooftop site. Considering VOC emissions from all

  7. Solution Space-based Approach to Assess Sector Complexity in Air Traffic Control

    NARCIS (Netherlands)

    Abdul Rahman, S.M.B.

    2014-01-01

    Various methods have been introduced in the past in efforts to optimize airspace sector design and the allocation of air traffic controllers. This is done with the aim to accommodate growth, increase productivity and most importantly to ensure safety of air traffic. To accomplish this, a more

  8. Risk based decision support for new air traffic operations with reduced aircraft separation

    NARCIS (Netherlands)

    Speijker, L.J.P.

    2007-01-01

    With the steady increase in air traffic, the aviation system is under continuous pressure to increase aircraft handling capacity. Various new Air Traffic Management systems and flight procedures are proposed to increase airport capacity while maintaining the required level of safety. Newly proposed

  9. Model based monitoring of urban traffic noise : Field test results for road side and shielded sides

    NARCIS (Netherlands)

    Eerden, F.J.M. van der; Lutgendorf, D.; Wessels, P.W.; Basten, T.G.H.

    2012-01-01

    Urban traffic noise can be a major issue for people and (local) governments. On a local scale the use of measurements is increasing, especially when measures or changes to the local infrastructure are proposed. However, measuring (only) urban traffic noise is a challenging task. By using a model

  10. Modular adaptive implant based on smart materials.

    Science.gov (United States)

    Bîzdoacă, N; Tarniţă, Daniela; Tarniţă, D N

    2008-01-01

    Applications of biological methods and systems found in nature to the study and design of engineering systems and modern technology are defined as Bionics. The present paper describes a bionics application of shape memory alloy in construction of orthopedic implant. The main idea of this paper is related to design modular adaptive implants for fractured bones. In order to target the efficiency of medical treatment, the implant has to protect the fractured bone, for the healing period, undertaking much as is possible from the daily usual load of the healthy bones. After a particular stage of healing period is passed, using implant modularity, the load is gradually transferred to bone, assuring in this manner a gradually recover of bone function. The adaptability of this design is related to medical possibility of the physician to made the implant to correspond to patient specifically anatomy. Using a CT realistic numerical bone models, the mechanical simulation of different types of loading of the fractured bones treated with conventional method are presented. The results are commented and conclusions are formulated.

  11. Costs of traffic injuries

    DEFF Research Database (Denmark)

    Kruse, Marie

    2015-01-01

    OBJECTIVE: The aim of this study was to analyse the socioeconomic costs of traffic injuries in Denmark, notably the healthcare costs and the productivity costs related to traffic injuries, in a bottom-up, register-based perspective. METHOD: Traffic injury victims were identified using national...... emergency room data and police records. Victims were matched with five controls per case by means of propensity score, nearest-neighbour matching. In the cohort, consisting of the 52 526 individuals that experienced a traffic injury in 2000 and 262 630 matched controls, attributable healthcare costs were...... assessed using Danish national healthcare registers. Productivity costs were computed using duration analysis (Cox regression models). In a subanalysis, cost per severe traffic injury was computed for the 12 995 individuals that experienced a severe injury. RESULTS: The socioeconomic cost of a traffic...

  12. Design of an Ecological Flow-based Interface for 4D Trajectory Management in Air Traffic Control

    NARCIS (Netherlands)

    Pinto, J.; Klomp, R.E.; Borst, C.; Van Paassen, M.M.; Mulder, M.

    2015-01-01

    The concept of trajectory-based operations as proposed by SESAR and NextGen seeks to increase airspace efficiency and capacity by introducing time as an explicit control variable. Such form of operations lean heavily on the introduction of higher levels of automation to support the human air traffic

  13. An indicator based 'traffic light' model to pro-actively assess the occurrence of mycotoxins in tree nuts

    NARCIS (Netherlands)

    Jeurissen, S.M.F.; Seyhan, F.; Kandhai, M.C.; Dekkers, S.; Booij, C.J.H.; Bos, P.M.J.; Fels, van der H.J.

    2011-01-01

    This paper proposes an indicator based 'traffic light' model as a tool to pro-actively assess the occurrence of mycotoxins in tree nuts. The model is built using a holistic approach and, consequently, uses indicators from inside and outside the tree nut production chain as the basic elements.

  14. A cost-effective traffic data collection system based on the iDEN mobile telecommunication network.

    Science.gov (United States)

    2008-10-01

    This report describes a cost-effective data collection system for Caltrans 170 traffic signal : controller. The data collection system is based on TCP/IP communication over existing : low-cost mobile communication networks and Motorola iDEN1 mobile...

  15. A population-based, incidence cohort study of mid-back pain after traffic collisions

    DEFF Research Database (Denmark)

    Johansson, M S; Boyle, E; Hartvigsen, Jan

    2015-01-01

    , depression or others) has been investigated previously; however, knowledge about traffic collision-related MBP is lacking. The study objectives were to describe the incidence, course of recovery and prognosis of MBP after traffic collisions, in terms of global self-reported recovery. METHODS: Longitudinal......BACKGROUND: Traffic collisions often result in a wide range of symptoms included in the umbrella term whiplash-associated disorders. Mid-back pain (MBP) is one of these symptoms. The incidence and prognosis of different traffic injuries and their related conditions (e.g. neck pain, low back pain......: These findings show that MBP is common after traffic collisions, may result in a long recovery process and that a range of biopsychosocial factors are associated with recovery....

  16. Short-term traffic flow forecasting based on feature selection with mutual information

    Science.gov (United States)

    Yuan, Zhengwu; Tu, Chuan

    2017-05-01

    Traffic flow forecasting is related to many traffic variables, and how to select appropriate traffic variable combination is very important to traffic flow forecasting, which can reduce the cost of calculation and improve the forecasting precision. In this paper, a feature selection technique with mutual information is proposed for this purpose. Firstly, the mutual information is used to evaluate the relevance and redundancy of variables, and feature selection is used to select the relevant variables and filter out the redundancy between the selected variables. Secondly, BP neural network is used as the forecasting engine. Finally, a numerical example of traffic flow data from Pems is used to verify the forecasting performance of the proposed method, the results indicate that the proposed method can effectively reduce the cost of calculation and also improve the model forecasting precision.

  17. A Multi-Classification Method of Improved SVM-based Information Fusion for Traffic Parameters Forecasting

    Directory of Open Access Journals (Sweden)

    Hongzhuan Zhao

    2016-04-01

    Full Text Available With the enrichment of perception methods, modern transportation system has many physical objects whose states are influenced by many information factors so that it is a typical Cyber-Physical System (CPS. Thus, the traffic information is generally multi-sourced, heterogeneous and hierarchical. Existing research results show that the multisourced traffic information through accurate classification in the process of information fusion can achieve better parameters forecasting performance. For solving the problem of traffic information accurate classification, via analysing the characteristics of the multi-sourced traffic information and using redefined binary tree to overcome the shortcomings of the original Support Vector Machine (SVM classification in information fusion, a multi-classification method using improved SVM in information fusion for traffic parameters forecasting is proposed. The experiment was conducted to examine the performance of the proposed scheme, and the results reveal that the method can get more accurate and practical outcomes.

  18. Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

    Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

  19. Traffic pollution and countermeasures of urban traffic environment

    Science.gov (United States)

    He, Yuhong; Zheng, Chaocheng

    2018-01-01

    Background: Traffic environment has become a serious social problem in China currently, therefore, urban traffic environment governance is the requirement to solve this issue because as an important place in people's social life, urban traffic environment shows a strong city's energy. Objective: Based on analysis on social function of city traffic environment and its influence of traffic on urban environment in this paper, the goal to establish a healthy urban traffic environment must be included under the aim of sustainable development eternally and feasible measures were put forward afterwards. Method, result, conclusion and possible applications.

  20. Self Adaptive Hypermedia Navigation Based On Learner Model Characters

    NARCIS (Netherlands)

    Vassileva, Dessislava; Bontchev, Boyan

    2006-01-01

    Dessislava Vassileva, Boyan Bontchev "Self Adaptive Hypermedia Navigation Based On Learner Model Characters", IADAT-e2006, 3rd International Conference on Education, Barcelona (Spain), July 12-14, 2006, ISBN: 84-933971-9-9

  1. Adaptive IR Sensing Based on Advanced Nanostructures with Tunable Kinetics

    Science.gov (United States)

    2015-11-05

    AFRL-AFOSR-VA-TR-2015-0360 ADAPTIVE IR SENSING BASED ON ADVANCED NANOSTRUCTURES WITH TUNABLE KINETICS Vladimir Mitin RESEARCH FOUNDATION OF STATE...1 August 2010 - 31 July 2015 4. TITLE AND SUBTITLE Adaptive IR Sensing Based on Advanced Nanostructures with Tunable Kinetics 5a. CONTRACT NUMBER...engineering, and technological basis for further development of IR nanomaterials with nanoscale potential profile that can be effectively controlled by

  2. Residential exposure to traffic noise and leisure-time sports - A population-based study.

    Science.gov (United States)

    Roswall, Nina; Ammitzbøll, Gunn; Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Jensen, Steen Solvang; Tjønneland, Anne; Sørensen, Mette

    2017-08-01

    Traffic levels have been found a significant environmental predictor for physical inactivity. A recent study suggested that traffic noise annoyance was associated with lower physical activity. We investigated associations between modelled residential traffic noise and leisure-time sports. In the Diet, Cancer and Health cohort, we performed cross-sectional analyses using data from the baseline questionnaire (1993-97), and longitudinal analyses of change between baseline and follow-up (2000-02). People reported participation (yes/no) and hours of leisure-time sport, from which we calculated MET hrs/week. Present and historical addresses from 1987 to 2002 were found in national registries, and traffic noise was modelled 1 and 5 years before enrolment, and from baseline to follow-up. Analyses were performed using logistic and linear regression. Traffic noise exposure 5 years before baseline was associated with higher prevalence odds ratio of non-participation in leisure-time sports; significantly for road traffic noise (odds ratio (OR): 1.10; 95% confidence interval (CI): 1.07-1.13) and borderline for railway noise (OR: 1.03; 95% CI: 0.99-1.07), per 10dB. In longitudinal analyses, a 10dB higher road traffic noise was associated with a higher prevalence odds ratio of ceasing (OR: 1.12; 95% CI: 1.07-1.18) and a lower prevalence odds ratio of initiating (OR: 0.92; 95% CI: 0.87-0.96) leisure-time sports. Exposure to railway noise was negatively associated with baseline MET hrs/week, whereas no association was found in longitudinal analyses, or for road traffic noise. The study suggests that long-term exposure to residential road traffic noise is negatively associated with leisure-time sports. Results for railway noise were less consistent. Copyright © 2017 Elsevier GmbH. All rights reserved.

  3. Adaptive Measurement-Based Policy-Driven QoS Management with Fuzzy-Rule-based Resource Allocation

    Directory of Open Access Journals (Sweden)

    Philip J. Morrow

    2012-07-01

    Full Text Available Fixed and wireless networks are increasingly converging towards common connectivity with IP-based core networks. Providing effective end-to-end resource and QoS management in such complex heterogeneous converged network scenarios requires unified, adaptive and scalable solutions to integrate and co-ordinate diverse QoS mechanisms of different access technologies with IP-based QoS. Policy-Based Network Management (PBNM is one approach that could be employed to address this challenge. Hence, a policy-based framework for end-to-end QoS management in converged networks, CNQF (Converged Networks QoS Management Framework has been proposed within our project. In this paper, the CNQF architecture, a Java implementation of its prototype and experimental validation of key elements are discussed. We then present a fuzzy-based CNQF resource management approach and study the performance of our implementation with real traffic flows on an experimental testbed. The results demonstrate the efficacy of our resource-adaptive approach for practical PBNM systems.

  4. Cooperative and Adaptive Network Coding for Gradient Based Routing in Wireless Sensor Networks with Multiple Sinks

    Directory of Open Access Journals (Sweden)

    M. E. Migabo

    2017-01-01

    Full Text Available Despite its low computational cost, the Gradient Based Routing (GBR broadcast of interest messages in Wireless Sensor Networks (WSNs causes significant packets duplications and unnecessary packets transmissions. This results in energy wastage, traffic load imbalance, high network traffic, and low throughput. Thanks to the emergence of fast and powerful processors, the development of efficient network coding strategies is expected to enable efficient packets aggregations and reduce packets retransmissions. For multiple sinks WSNs, the challenge consists of efficiently selecting a suitable network coding scheme. This article proposes a Cooperative and Adaptive Network Coding for GBR (CoAdNC-GBR technique which considers the network density as dynamically defined by the average number of neighbouring nodes, to efficiently aggregate interest messages. The aggregation is performed by means of linear combinations of random coefficients of a finite Galois Field of variable size GF(2S at each node and the decoding is performed by means of Gaussian elimination. The obtained results reveal that, by exploiting the cooperation of the multiple sinks, the CoAdNC-GBR not only improves the transmission reliability of links and lowers the number of transmissions and the propagation latency, but also enhances the energy efficiency of the network when compared to the GBR-network coding (GBR-NC techniques.

  5. Effect of Water Flows on Ship Traffic in Narrow Water Channels Based on Cellular Automata

    Directory of Open Access Journals (Sweden)

    Hu Hongtao

    2017-11-01

    Full Text Available In narrow water channels, ship traffic may be affected by water flows and ship interactions. Studying their effects can help maritime authorities to establish appropriate management strategies. In this study, a two-lane cellular automation model is proposed. Further, the behavior of ship traffic is analyzed by setting different water flow velocities and considering ship interactions. Numerical experiment results show that the ship traffic density-flux relation is significantly different from the results obtained by classical models. Furthermore, due to ship interactions, the ship lane-change rate is influenced by the water flow to a certain degree.

  6. An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

    Science.gov (United States)

    Bongiorno, Christian; Miccichè, Salvatore; Mantegna, Rosario N

    2017-01-01

    We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast.

  7. An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

    Directory of Open Access Journals (Sweden)

    Christian Bongiorno

    Full Text Available We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i in the presence of perfect forecast ability of controllers, and (ii in the presence of some degree of uncertainty in flight trajectory forecast.

  8. Crowdsourcing based subjective quality assessment of adaptive video streaming

    DEFF Research Database (Denmark)

    Shahid, M.; Søgaard, Jacob; Pokhrel, J.

    2014-01-01

    humans are considered to be the most valid method of the as- sessment of QoE. Besides lab-based subjective experiments, crowdsourcing based subjective assessment of video quality is gaining popularity as an alternative method. This paper presents insights into a study that investigates perceptual pref......- erences of various adaptive video streaming scenarios through crowdsourcing based subjective quality assessment....

  9. Scheduling of high-speed rail traffic based on discrete-time movement model

    International Nuclear Information System (INIS)

    Sun Ya-Hua; Cao Cheng-Xuan; Xu Yan; Wu Chao

    2013-01-01

    In this paper, a new simulation approach for solving the mixed train scheduling problem on the high-speed double-track rail line is presented. Based on the discrete-time movement model, we propose control strategies for mixed train movement with different speeds on a high-speed double-track rail line, including braking strategy, priority rule, travelling strategy, and departing rule. A new detailed algorithm is also presented based on the proposed control strategies for mixed train movement. Moreover, we analyze the dynamic properties of rail traffic flow on a high-speed rail line. Using our proposed method, we can effectively simulate the mixed train schedule on a rail line. The numerical results demonstrate that an appropriate decrease of the departure interval can enhance the capacity, and a suitable increase of the distance between two adjacent stations can enhance the average speed. Meanwhile, the capacity and the average speed will be increased by appropriately enhancing the ratio of faster train number to slower train number from 1. (general)

  10. Simplified web-based decision support method for traffic management and work zone analysis.

    Science.gov (United States)

    2015-06-01

    Traffic congestion mitigation is one of the key challenges that transportation planners and operations engineers face when : planning for construction and maintenance activities. There is a wide variety of approaches and methods that address work : z...

  11. Optimal signal timing design for urban street networks under user equilibrium based traffic conditions : final report.

    Science.gov (United States)

    2016-09-20

    In the ever-growing travel demand, traffic congestion on freeways and expressways : recurs more frequently at a higher number of locations and for longer durations with : added severity. This becomes especially true in large metropolitan areas. Parti...

  12. An Ad-Hoc Opportunistic Dissemination Protocol for Smartphone-based Participatory Traffic Monitoring

    NARCIS (Netherlands)

    Türkes, Okan; Seraj, Fatjon; Scholten, Johan; Meratnia, Nirvana; Havinga, Paul J.M.

    2015-01-01

    This study introduces an ad-hoc opportunistic data dissemination protocol, called VADISS, that facilitates participatory traffic monitoring applications with smartphones. As a ubiquitous alternative to existing vehicular networking methods, VADISS uses the default WiFi interfaces universally adopted

  13. Incorporating Traffic Control and Safety Hardware Performance Functions into Risk-based Highway Safety Analysis

    Directory of Open Access Journals (Sweden)

    Zongzhi Li

    2017-04-01

    Full Text Available Traffic control and safety hardware such as traffic signs, lighting, signals, pavement markings, guardrails, barriers, and crash cushions form an important and inseparable part of highway infrastructure affecting safety performance. Significant progress has been made in recent decades to develop safety performance functions and crash modification factors for site-specific crash predictions. However, the existing models and methods lack rigorous treatments of safety impacts of time-deteriorating conditions of traffic control and safety hardware. This study introduces a refined method for computing the Safety Index (SI as a means of crash predictions for a highway segment that incorporates traffic control and safety hardware performance functions into the analysis. The proposed method is applied in a computation experiment using five-year data on nearly two hundred rural and urban highway segments. The root-mean square error (RMSE, Chi-square, Spearman’s rank correlation, and Mann-Whitney U tests are employed for validation.

  14. Machine learning for identifying botnet network traffic

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2013-01-01

    . Due to promise of non-invasive and resilient detection, botnet detection based on network traffic analysis has drawn a special attention of the research community. Furthermore, many authors have turned their attention to the use of machine learning algorithms as the mean of inferring botnet......-related knowledge from the monitored traffic. This paper presents a review of contemporary botnet detection methods that use machine learning as a tool of identifying botnet-related traffic. The main goal of the paper is to provide a comprehensive overview on the field by summarizing current scientific efforts....... The contribution of the paper is three-fold. First, the paper provides a detailed insight on the existing detection methods by investigating which bot-related heuristic were assumed by the detection systems and how different machine learning techniques were adapted in order to capture botnet-related knowledge...

  15. Model-based design of adaptive embedded systems

    CERN Document Server

    Hamberg, Roelof; Reckers, Frans; Verriet, Jacques

    2013-01-01

    Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product trade-offs between system qualities at system level. The main challenge in the development of adaptive systems is keeping control of the intrinsic complexity of such systems while working with multi-disciplinary teams to create different parts of the system. Model-Based Development of Adaptive Embedded Systems focuses on the development of adaptive embedded systems both from an architectural and methodological point of view. It describes architectural solution patterns for adaptive systems and state-of-the-art model-based methods and techniques to support adaptive system development. In particular, the book describes the outcome of the Octopus project, a cooperation of a multi-disciplinary team of academic and indus...

  16. Energy Saving Scheme Based On Traffic Forwarding For Optical Fiber Access Networks

    DEFF Research Database (Denmark)

    Lopez, G. Arturo Rodes; Estaran Tolosa, Jose Manuel; Vegas Olmos, Juan José

    2013-01-01

    We report on an energy saving block that regroups and powers off OLTs during low traffic periods, resulting in energy savings up to 87,5% in the central office of optical access networks.......We report on an energy saving block that regroups and powers off OLTs during low traffic periods, resulting in energy savings up to 87,5% in the central office of optical access networks....

  17. Algorithm for detecting violations of traffic rules based on computer vision approaches

    Directory of Open Access Journals (Sweden)

    Ibadov Samir

    2017-01-01

    Full Text Available We propose a new algorithm for automatic detect violations of traffic rules for improving the people safety on the unregulated pedestrian crossing. The algorithm uses multi-step proceedings. They are zebra detection, cars detection, and pedestrian detection. For car detection, we use faster R-CNN deep learning tool. The algorithm shows promising results in the detection violations of traffic rules.

  18. Optimal Positioning of Emergency Preparedness Assets based on Dynamic Traffic Situation

    OpenAIRE

    Støwer, Knut Skaseth

    2015-01-01

    The objective of this thesis is to create a method that utilizes mathematical models and tools to measure the threat posed to the environment by the merchant traffic along the Norwegian coast. This is done so that operators at Vessel Traffic Service(VTS) centers in Norway can assess dangers and allocate emergency assets to the correct areas so that the existing assets are utilized to their potential. If the existing emergency assets are utilized fully, the risk of catastroph...

  19. Physics of Autonomous Driving based on Three-Phase Traffic Theory

    OpenAIRE

    Kerner, Boris S.

    2017-01-01

    We have revealed physical features of autonomous driving in the framework of the three-phase traffic theory for which there is no fixed time headway to the preceding vehicle. A comparison with the classical model approach to autonomous driving for which an autonomous driving vehicle tries to reach a fixed (desired or "optimal") time headway to the preceding vehicle has been made. It turns out that autonomous driving in the framework of the three-phase traffic theory exhibits the following adv...

  20. Traffic Light Options

    DEFF Research Database (Denmark)

    Jørgensen, Peter Løchte

    2007-01-01

    This paper introduces, prices, and analyzes traffic light options. The traffic light option is an innovative structured OTC derivative developed independently by several London-based investment banks to suit the needs of Danish life and pension (L&P) companies, which must comply with the traffic...... light solvency stress test system introduced by the Danish Financial Supervisory Authority (DFSA) in June 2001. This monitoring system requires L&P companies to submit regular reports documenting the sensitivity of the companies' base capital to certain pre-defined market shocks - the red and yellow...... light scenarios. These stress scenarios entail drops in interest rates as well as in stock prices, and traffic light options are thus designed to pay off and preserve sufficient capital when interest rates and stock prices fall simultaneously. Sweden's FSA implemented a traffic light system in January...

  1. Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation

    Directory of Open Access Journals (Sweden)

    Tan-Hsu Tan

    2017-01-01

    Full Text Available This study presents a new ubiquitous emergency medical service system (UEMS that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients’ biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient’s biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios.

  2. An Interference-Aware Traffic-Priority-Based Link Scheduling Algorithm for Interference Mitigation in Multiple Wireless Body Area Networks

    Directory of Open Access Journals (Sweden)

    Thien T. T. Le

    2016-12-01

    Full Text Available Currently, wireless body area networks (WBANs are effectively used for health monitoring services. However, in cases where WBANs are densely deployed, interference among WBANs can cause serious degradation of network performance and reliability. Inter-WBAN interference can be reduced by scheduling the communication links of interfering WBANs. In this paper, we propose an interference-aware traffic-priority-based link scheduling (ITLS algorithm to overcome inter-WBAN interference in densely deployed WBANs. First, we model a network with multiple WBANs as an interference graph where node-level interference and traffic priority are taken into account. Second, we formulate link scheduling for multiple WBANs as an optimization model where the objective is to maximize the throughput of the entire network while ensuring the traffic priority of sensor nodes. Finally, we propose the ITLS algorithm for multiple WBANs on the basis of the optimization model. High spatial reuse is also achieved in the proposed ITLS algorithm. The proposed ITLS achieves high spatial reuse while considering traffic priority, packet length, and the number of interfered sensor nodes. Our simulation results show that the proposed ITLS significantly increases spatial reuse and network throughput with lower delay by mitigating inter-WBAN interference.

  3. Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation.

    Science.gov (United States)

    Tan, Tan-Hsu; Gochoo, Munkhjargal; Chen, Yung-Fu; Hu, Jin-Jia; Chiang, John Y; Chang, Ching-Su; Lee, Ming-Huei; Hsu, Yung-Nian; Hsu, Jiin-Chyr

    2017-01-21

    This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients' biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient's biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios.

  4. Supporting Security against SYN Flooding Attack in Distributed DoS Via Measuring IPFIX-Based Traffic

    Science.gov (United States)

    Alipour, H.; Kia, M. Kashefi; Esmaeili, M.

    Distributed denial-of-service attacks on public servers after 2000 have become a serious problem. In the distributed denial-of-service (DDoS) attacks often seen recently, multiple distributed nodes concurrently attack a single server. To assure that network services will not be interrupted, faster and more effective defense mechanisms is needed to protect against malicious traffic, especially SYN floods. One problem in detecting SYN flood traffic is that server nodes or firewalls cannot distinguish the SYN packets of normal TCP connections from those of a SYN flood attack. Our method, FDFIX, relies on the use of monitoring and measurement techniques to evaluate the impact of DoS attacks. It uses flow based measurements. Capturing flow information is very important for detecting DoS and also other kinds of attacks. Flow monitoring allows detecting suspicious traffics and in the next step can analyze attacking flows and the results can be used for defense methods. Our method provides required information for many mechanisms that use traffic measurement as their input.

  5. A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Nadia Adnan Shiltagh

    2015-11-01

    Full Text Available Wireless Multimedia Sensor Networks (WMSNs are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC. The Modify Spike Neural Network controller (MSNC can calculate the appropriate traffic load parameter μ for each parent node and then use in the EWPBRC algorithm to estimate the transmission rate of parent nodes and then assign a suitable transmission rate for each child node. A comparative study between (MSNTLP with EWBPRC and fuzzy logic controller for traffic load parameter with Exponential Weight of Priority Based Rate Control algorithm (FTLP with EWBPRC algorithm shows that the (MSNTLP with EWBPRC is more efficient than (FTLP with EWBPRC algorithm in terms of packet loss, queue delay and throughput. Another comparative study between (MSNTLP with EWBPRC and EWBPRC with fixed traffic load parameter (µ shows that the MSNTLP with EWBPRC is more efficient than EWBPRC with fixed traffic load parameter (µ in terms of packet loss ratio and queue delay. A simulation process is developed and tested using the network simulator _2 (NS2 in a computer having the following properties: windows 7 (64-bit, core i7, RAM 8GB, hard 1TB.

  6. The years lived with disability due to road traffic accidents based on the nature of injuries in Kermanshah province (2010

    Directory of Open Access Journals (Sweden)

    Neda Izadi

    2015-03-01

    Full Text Available Background: Traffic accidents, with lots of casualties and injuries, cause a lot of economic loss. This study was conducted to determine the Years Lived with Disability (YLD due to road traffic accidents according to the nature of injuries in Kermanshah province. Methods: following a pilot study, a sample of 3258 people was analyzed in order to calculate the YLD. Then, based on various factors, the age, gender and nature of injury of 10070 people were estimated. The YLD was calculated using the Global Burden of Disease (GBD (2010. The data concerning age and gender of the total population of the province was taken from the Statistical Center of Iran. All calculations were performed based on age and gender in Excel software. Results: The mean age of the injured people was 32.7±17.1. Men constituted 67.7 % of patients. The incidence rate of traffic accidents was 283.6 per 100,000. The highest levels of YLD in outpatients, men and women were reported for patella, tibia, fibula and ankle fractures and fractures of clavicle, scapula, humerus and skull, respectively. The highest rate of inpatient YLDs by nature of injury belonged to the fractures of sternum, ribs and face bone. The years lived with disability was calculated to be 2365.96 years (2.46 per 1000 and 1039.01 years (1.1 per 1000 for men and women, respectively. It was 3404.97 years (1.79 per 1000 in both genders. The highest YLD was in the age group of 15–29. Conclusion: Traffic accidents are high rate of YLD is resulted by traffic accidents. The most affected age group are youngsters and fracture are more frequent.

  7. Building the Multi-agent Based Adaptive Security System

    Directory of Open Access Journals (Sweden)

    Sergey Andreevich Petrov

    2013-06-01

    Full Text Available This article is concerned with security of information system. Multi-agent based adaptive security system is offered. Advantages of the system and its potential architecture are presented. The author describes requirements for agents’ functionality and possible variants of agents’ operability. The suggested approach is intended to use for building adaptive security system in accordance with network structure, required safety level and available compute resources.

  8. A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems

    OpenAIRE

    González Rodríguez, Diego; Hernández Carrión, José Rodolfo

    2014-01-01

    Paper presented at the 13th International Conference on Simulation of Adaptive Behavior which took place at Castellón, Spain in 2014, July 22-25. Bacteria have demonstrated an amazing capacity to overcome envi-ronmental changes by collective adaptation through genetic exchanges. Using a distributed communication system and sharing individual strategies, bacteria propagate mutations as innovations that allow them to survive in different envi-ronments. In this paper we present an agent-based...

  9. Adaptive Device Context Based Mobile Learning Systems

    Science.gov (United States)

    Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng

    2011-01-01

    Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…

  10. Bicycle traffic in urban areas

    Directory of Open Access Journals (Sweden)

    Anđelković Zorica

    2015-01-01

    Full Text Available Cycling is a term describing the use of bicycles, but also any mean of transport driven solely by human power. Development of bicycle traffic in urban areas involves construction of cycling infrastructure, adapting streets and other traffic infrastructure to a form suitable for cycling and other means of transport (individual motorized traffic, public transport, walking, ensuring the adequate budget and systematic planning and development of sustainable transport in cities. The paper presents basic settings and conditions as input elements to plan bicycle traffic in urban areas, as well as program- design conditions which lead the activities of planners and designers of urban roads in connection with cyclists.

  11. Size Adaptive Region Based Huffman Compression Technique

    OpenAIRE

    Nandi, Utpal; Mandal, Jyotsna Kumar

    2014-01-01

    A loss-less compression technique is proposed which uses a variable length Region formation technique to divide the input file into a number of variable length regions. Huffman codes are obtained for entire file after formation of regions. Symbols of each region are compressed one by one. Comparisons are made among proposed technique, Region Based Huffman compression technique and classical Huffman technique. The proposed technique offers better compression ratio for some files than other two.

  12. Achieving Adaptability through Inquiry Based Learning

    Science.gov (United States)

    2010-06-01

    knowledge. IBL is based on a different conception of learning, one traceable back to John Dewey (1910) and Jean Piaget (1972; von Glasersfeld, 1995) and...Dewey, 1910; Duffy 2009; Piaget , 1972; Schank, Fano, Bell, and Jona, 1993). If the learners are focused on figuring out what the instructor wants...errors or the inability to fully make sense of a situation provides the basis for learning ( Piaget , 1973; Schank, et al, 1993). Thus the errors

  13. An Efficient Methodology for Calibrating Traffic Flow Models Based on Bisection Analysis

    Directory of Open Access Journals (Sweden)

    Enzo C. Jia

    2014-01-01

    Full Text Available As urban planning becomes more sophisticated, the accurate detection and counting of pedestrians and cyclists become more important. Accurate counts can be used to determine the need for additional pedestrian walkways and intersection reorganization, among other planning initiatives. In this project, a camera-based approach is implemented to create a real-time pedestrian and cyclist counting system which is regularly accurate to 85% and often achieves higher accuracy. The approach retasks a state-of-the-art traffic camera, the Autoscope Solo Terra, for pedestrian and bicyclist counting. Object detection regions are sized to identify multiple pedestrians moving in either direction on an urban sidewalk and bicyclists in an adjacent bicycle lane. Collected results are processed in real time, eliminating the need for video storage and postprocessing. In this paper, results are presented for a pedestrian walkway for pedestrian flow up to 108 persons/min and the limitations of the implemented system are enumerated. Both pedestrian and cyclist counting accuracy of over 90% is achieved.

  14. Two-hybrid-based systems: powerful tools for investigation of membrane traffic machineries.

    Science.gov (United States)

    Stasi, Mariangela; De Luca, Maria; Bucci, Cecilia

    2015-05-20

    Protein-protein interactions regulate biological processes and are fundamental for cell functions. Recently, efforts have been made to define interactomes, which are maps of protein-protein interactions that are useful for understanding biological pathways and networks and for investigating how perturbations of these networks lead to diseases. Therefore, interactomes are becoming fundamental for establishing the molecular basis of human diseases and contributing to the discovery of effective therapies. Interactomes are constructed based on experimental data present in the literature and computational predictions of interactions. Several biochemical, genetic and biotechnological techniques have been used in the past to identify protein-protein interactions. The yeast two-hybrid system has beyond doubt represented a revolution in the field, being a versatile tool and allowing the immediate identification of the interacting proteins and isolation of the cDNA coding for the interacting peptide after in vivo screening. Recently, variants of the yeast two-hybrid assay have been developed, including high-throughput systems that promote the rapidly growing field of proteomics. In this review we will focus on the role of this technique in the discovery of Rab interacting proteins, highlighting the importance of high-throughput two-hybrid screening as a tool to study the complexity of membrane traffic machineries. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Real-Time Traffic Signal Control for Optimization of Traffic Jam Probability

    Science.gov (United States)

    Cui, Cheng-You; Shin, Ji-Sun; Miyazaki, Michio; Lee, Hee-Hyol

    Real-time traffic signal control is an integral part of urban traffic control system. It can control traffic signals online according to variation of traffic flow. In this paper, we propose a new method for the real-time traffic signal control system. The system uses a Cellular Automaton model and a Bayesian Network model to predict probabilistic distributions of standing vehicles, and uses a Particle Swarm Optimization method to calculate optimal traffic signals. A simulation based on real traffic data was carried out to show the effectiveness of the proposed real-time traffic signal control system CAPSOBN using a micro traffic simulator.

  16. Complaints of Poor Sleep and Risk of Traffic Accidents: A Population-Based Case-Control Study.

    Directory of Open Access Journals (Sweden)

    Pierre Philip

    Full Text Available This study aimed to determine the sleepiness-related factors associated with road traffic accidents.A population based case-control study was conducted in 2 French agglomerations. 272 road accident cases hospitalized in emergency units and 272 control drivers matched by time of day and randomly stopped by police forces were included in the study. Odds ratios were calculated for the risk of road traffic accidents.As expected, the main predictive factor for road traffic accidents was having a sleep episode at the wheel just before the accident (OR 9.97, CI 95%: 1.57-63.50, p<0.05. The increased risk of traffic accidents was 3.35 times higher in subjects who reported very poor quality sleep during the last 3 months (CI 95%: 1.30-8.63, p<0.05, 1.69 times higher in subjects reporting sleeping 6 hours or fewer per night during the last 3 months (CI 95%: 1.00-2.85, p<0.05, 2.02 times higher in subjects reporting symptoms of anxiety or nervousness in the previous day (CI 95%: 1.03-3.97, p<0.05, and 3.29 times higher in subjects reporting taking more than 2 medications in the last 24 h (CI 95%: 1.14-9.44, p<0.05. Chronic daytime sleepiness measured by the Epworth Sleepiness Scale, expressed heavy snoring and nocturnal leg movements did not explain traffic accidents.Physicians should be attentive to complaints of poor sleep quality and quantity, symptoms of anxiety-nervousness and/or drug consumption in regular car drivers.

  17. Effective Factors in Severity of Traffic Accident-Related Traumas; an Epidemiologic Study Based on the Haddon Matrix

    Directory of Open Access Journals (Sweden)

    Kambiz Masoumi

    2016-04-01

    Full Text Available Introduction: Traffic accidents are the 8th cause of mortality in different countries and are expected to rise to the 3rd rank by 2020. Based on the Haddon matrix numerous factors such as environment, host, and agent can affect the severity of traffic-related traumas. Therefore, the present study aimed to evaluate the effective factors in severity of these traumas based on Haddon matrix. Methods: In the present 1-month cross-sectional study, all the patients injured in traffic accidents, who were referred to the ED of Imam Khomeini and Golestan Hospitals, Ahvaz, Iran, during March 2013 were evaluated. Based on the Haddon matrix, effective factors in accident occurrence were defined in 3 groups of host, agent, and environment. Demographic data of the patients and data regarding Haddon risk factors were extracted and analyzed using SPSS version 20. Results: 700 injured people with the mean age of 29.66 ± 12.64 years (3-82 were evaluated (92.4% male. Trauma mechanism was car-pedestrian in 308 (44% of the cases and car-motorcycle in 175 (25%. 610 (87.1% cases were traffic accidents and 371 (53% occurred in the time between 2 pm and 8 pm. Violation of speed limit was the most common violation with 570 (81.4% cases, followed by violation of right-of-way in 57 (8.1% patients. 59.9% of the severe and critical injuries had occurred on road accidents, while 61.3% of the injuries caused by traffic accidents were mild to moderate (p < 0.001. The most common mechanisms of trauma for critical injuries were rollover (72.5%, motorcycle-pedestrian (23.8%, and car-motorcycle (13.14% accidents (p < 0.001. Conclusion: Based on the results of the present study, the most important effective factors in severity of traffic accident-related traumas were age over 50, not using safety tools, and undertaking among host-related factors; insufficient environment safety, road accidents and time between 2 pm and 8 pm among environmental factors; and finally, rollover, car

  18. Research on three-phase traffic flow modeling based on interaction range

    Science.gov (United States)

    Zeng, Jun-Wei; Yang, Xu-Gang; Qian, Yong-Sheng; Wei, Xu-Ting

    2017-12-01

    On the basis of the multiple velocity difference effect (MVDE) model and under short-range interaction, a new three-phase traffic flow model (S-MVDE) is proposed through careful consideration of the influence of the relationship between the speeds of the two adjacent cars on the running state of the rear car. The random slowing rule in the MVDE model is modified in order to emphasize the influence of vehicle interaction between two vehicles on the probability of vehicles’ deceleration. A single-lane model which without bottleneck structure under periodic boundary conditions is simulated, and it is proved that the traffic flow simulated by S-MVDE model will generate the synchronous flow of three-phase traffic theory. Under the open boundary, the model is expanded by adding an on-ramp, the congestion pattern caused by the bottleneck is simulated at different main road flow rates and on-ramp flow rates, which is compared with the traffic congestion pattern observed by Kerner et al. and it is found that the results are consistent with the congestion characteristics in the three-phase traffic flow theory.

  19. A framework for privacy and security analysis of probe-based traffic information systems

    KAUST Repository

    Canepa, Edward S.

    2013-01-01

    Most large scale traffic information systems rely on fixed sensors (e.g. loop detectors, cameras) and user generated data, this latter in the form of GPS traces sent by smartphones or GPS devices onboard vehicles. While this type of data is relatively inexpensive to gather, it can pose multiple security and privacy risks, even if the location tracks are anonymous. In particular, creating bogus location tracks and sending them to the system is relatively easy. This bogus data could perturb traffic flow estimates, and disrupt the transportation system whenever these estimates are used for actuation. In this article, we propose a new framework for solving a variety of privacy and cybersecurity problems arising in transportation systems. The state of traffic is modeled by the Lighthill-Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. The resulting framework is very flexible, and can in particular be used to detect spoofing attacks in real time, or carry out attacks on location tracks. Numerical implementations are performed on experimental data from the Mobile Century experiment to validate this framework. © 2013 ACM.

  20. Analysis of ITMS System Impact Mechanism in Beijing Based on FD and Traffic Entropy

    Directory of Open Access Journals (Sweden)

    Ailing Huang

    2012-01-01

    Full Text Available Although more attention has been attracted to benefit evaluation of Intelligent Transportation Systems (ITS deployment, how ITS impact the traffic system and make great effects is little considered. As a subsystem of ITS, in this paper, Intelligent Transportation Management System (ITMS is studied with its impact mechanism on the road traffic system. Firstly, the correlative factors between ITMS and the road traffic system are presented and 3 positive feedback chains are defined. Secondly, we introduce the theory of Fundamental Diagram (FD and traffic system entropy to demonstrate the correlative relationship between ITMS and feedback chains. The analyzed results show that ITMS, as a negative feedback factor, has damping functions on the coupling relationship of all 3 positive feedback chains. It indicates that with its deployment in Beijing, ITMS has impacted the improvement of efficiency and safety for the road traffic system. Finally, related benefits brought by ITMS are presented corresponding to the correlative factors, and effect standards are identified for evaluating ITMS comprehensive benefits.

  1. Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

    Energy Technology Data Exchange (ETDEWEB)

    Aziz, H. M. Abdul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Zhu, Feng [Purdue University, West Lafayette, IN (United States). Lyles School of Civil Engineering; Ukkusuri, Satish V. [Purdue University, West Lafayette, IN (United States). Lyles School of Civil Engineering

    2017-10-04

    Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better at higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO2, NOx, VOC, PM10) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.

  2. 4D Trajectory Estimation for Air Traffic Control Automation System Based on Hybrid System Theory

    Directory of Open Access Journals (Sweden)

    Xin-Min Tang

    2012-03-01

    Full Text Available To resolve the problem of future airspace management under great traffic flow and high density condition, 4D trajectory estimation has become one of the core technologies of the next new generation air traffic control automation system. According to the flight profile and the dynamics models of different aircraft types under different flight conditions, a hybrid system model that switches the aircraft from one flight stage to another with aircraft state changing continuously in one state is constructed. Additionally, air temperature and wind speed are used to modify aircraft true airspeed as well as ground speed, and the hybrid system evolution simulation is used to estimate aircraft 4D trajectory. The case study proves that 4D trajectory estimated through hybrid system model can image the flight dynamic states of aircraft and satisfy the needs of the planned flight altitude profile.KEY WORDSair traffic management, 4D trajectory estimation, hybrid system model, aircraft dynamic model

  3. Modified Pagerank Algorithm Based Real-Time Metropolitan Vehicular Traffic Routing Using GPS Crowdsourcing Data

    Directory of Open Access Journals (Sweden)

    Adithya Guru Vaishnav.S

    2015-08-01

    Full Text Available This paper aims at providing a theoretical framework to find an optimized route from any source to destination considering the real-time traffic congestion issues. The distance of various possible routes from the source and destination are calculated and a PathRank is allocated in the descending order of distance to each possible path. Each intermediate locations are considered as nodes of a graph and the edges are represented by real-time traffic flow monitored using GoogleMaps GPS crowdsourcing data. The Page Rank is calculated for each intermediate node. From the values of PageRank and PathRank the minimum sum term is used to find an optimized route with minimal trade-off between shortest path and real-time traffic.

  4. Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation

    Directory of Open Access Journals (Sweden)

    Sekhar S Chandra

    2004-01-01

    Full Text Available We address the problem of estimating instantaneous frequency (IF of a real-valued constant amplitude time-varying sinusoid. Estimation of polynomial IF is formulated using the zero-crossings of the signal. We propose an algorithm to estimate nonpolynomial IF by local approximation using a low-order polynomial, over a short segment of the signal. This involves the choice of window length to minimize the mean square error (MSE. The optimal window length found by directly minimizing the MSE is a function of the higher-order derivatives of the IF which are not available a priori. However, an optimum solution is formulated using an adaptive window technique based on the concept of intersection of confidence intervals. The adaptive algorithm enables minimum MSE-IF (MMSE-IF estimation without requiring a priori information about the IF. Simulation results show that the adaptive window zero-crossing-based IF estimation method is superior to fixed window methods and is also better than adaptive spectrogram and adaptive Wigner-Ville distribution (WVD-based IF estimators for different signal-to-noise ratio (SNR.

  5. Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories

    Science.gov (United States)

    Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.

    2016-06-01

    For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

  6. ANALYSIS OF SPATIO-TEMPORAL TRAFFIC PATTERNS BASED ON PEDESTRIAN TRAJECTORIES

    Directory of Open Access Journals (Sweden)

    S. Busch

    2016-06-01

    Full Text Available For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.

  7. Adaptive radiotherapy based on contrast enhanced cone beam CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Soevik, Aaste; Skogmo, Hege K. (Dept. of Companion Animal Clinical Sciences, Norwegian School of Veterinary Science, Oslo (Norway)), E-mail: aste.sovik@nvh.no; Roedal, Jan (Dept. of Companion Animal Clinical Sciences, Norwegian School of Veterinary Science, Oslo (Norway)); Lervaag, Christoffer; Eilertsen, Karsten; Malinen, Eirik (Dept. of Medical Physics, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway))

    2010-10-15

    Cone beam CT (CBCT) imaging has become an integral part of radiation therapy, with images typically used for offline or online patient setup corrections based on bony anatomy co-registration. Ideally, the co-registration should be based on tumor localization. However, soft tissue contrast in CBCT images may be limited. In the present work, contrast enhanced CBCT (CECBCT) images were used for tumor visualization and treatment adaptation. Material and methods. A spontaneous canine maxillary tumor was subjected to repeated cone beam CT imaging during fractionated radiotherapy (10 fractions in total). At five of the treatment fractions, CECBCT images, employing an iodinated contrast agent, were acquired, as well as pre-contrast CBCT images. The tumor was clearly visible in post-contrast minus pre-contrast subtraction images, and these contrast images were used to delineate gross tumor volumes. IMRT dose plans were subsequently generated. Four different strategies were explored: 1) fully adapted planning based on each CECBCT image series, 2) planning based on images acquired at the first treatment fraction and patient repositioning following bony anatomy co-registration, 3) as for 2), but with patient repositioning based on co-registering contrast images, and 4) a strategy with no patient repositioning or treatment adaptation. The equivalent uniform dose (EUD) and tumor control probability (TCP) calculations to estimate treatment outcome for each strategy. Results. Similar translation vectors were found when bony anatomy and contrast enhancement co-registration were compared. Strategy 1 gave EUDs closest to the prescription dose and the highest TCP. Strategies 2 and 3 gave EUDs and TCPs close to that of strategy 1, with strategy 3 being slightly better than strategy 2. Even greater benefits from strategies 1 and 3 are expected with increasing tumor movement or deformation during treatment. The non-adaptive strategy 4 was clearly inferior to all three adaptive strategies

  8. Adaptive radiotherapy based on contrast enhanced cone beam CT imaging

    International Nuclear Information System (INIS)

    Soevik, Aaste; Skogmo, Hege K.; Roedal, Jan; Lervaag, Christoffer; Eilertsen, Karsten; Malinen, Eirik

    2010-01-01

    Cone beam CT (CBCT) imaging has become an integral part of radiation therapy, with images typically used for offline or online patient setup corrections based on bony anatomy co-registration. Ideally, the co-registration should be based on tumor localization. However, soft tissue contrast in CBCT images may be limited. In the present work, contrast enhanced CBCT (CECBCT) images were used for tumor visualization and treatment adaptation. Material and methods. A spontaneous canine maxillary tumor was subjected to repeated cone beam CT imaging during fractionated radiotherapy (10 fractions in total). At five of the treatment fractions, CECBCT images, employing an iodinated contrast agent, were acquired, as well as pre-contrast CBCT images. The tumor was clearly visible in post-contrast minus pre-contrast subtraction images, and these contrast images were used to delineate gross tumor volumes. IMRT dose plans were subsequently generated. Four different strategies were explored: 1) fully adapted planning based on each CECBCT image series, 2) planning based on images acquired at the first treatment fraction and patient repositioning following bony anatomy co-registration, 3) as for 2), but with patient repositioning based on co-registering contrast images, and 4) a strategy with no patient repositioning or treatment adaptation. The equivalent uniform dose (EUD) and tumor control probability (TCP) calculations to estimate treatment outcome for each strategy. Results. Similar translation vectors were found when bony anatomy and contrast enhancement co-registration were compared. Strategy 1 gave EUDs closest to the prescription dose and the highest TCP. Strategies 2 and 3 gave EUDs and TCPs close to that of strategy 1, with strategy 3 being slightly better than strategy 2. Even greater benefits from strategies 1 and 3 are expected with increasing tumor movement or deformation during treatment. The non-adaptive strategy 4 was clearly inferior to all three adaptive strategies

  9. TBO-AID: Trajectory-Based Operations Adaptive Information Display, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Trajectory-based operations (TBO) are at the forefront of the Next Generation Air Traffic Management System (NextGen). The vision of NextGen is one in which pilots...

  10. Design of an adaptive neural network based power system stabilizer.

    Science.gov (United States)

    Liu, Wenxin; Venayagamoorthy, Ganesh K; Wunsch, Donald C

    2003-01-01

    Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp the low frequency power system oscillations. To overcome the drawbacks of conventional PSS (CPSS), numerous techniques have been proposed in the literature. Based on the analysis of existing techniques, this paper presents an indirect adaptive neural network based power system stabilizer (IDNC) design. The proposed IDNC consists of a neuro-controller, which is used to generate a supplementary control signal to the excitation system, and a neuro-identifier, which is used to model the dynamics of the power system and to adapt the neuro-controller parameters. The proposed method has the features of a simple structure, adaptivity and fast response. The proposed IDNC is evaluated on a single machine infinite bus power system under different operating conditions and disturbances to demonstrate its effectiveness and robustness.

  11. SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs

    Directory of Open Access Journals (Sweden)

    Muhammad Aslam

    2017-12-01

    Full Text Available Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN. Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR’s routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS. This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime

  12. SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs.

    Science.gov (United States)

    Aslam, Muhammad; Hu, Xiaopeng; Wang, Fan

    2017-12-13

    Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR's routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability

  13. A Novel Through Capacity Model for One-way Channel Based on Characteristics of the Vessel Traffic Flow

    Directory of Open Access Journals (Sweden)

    Yuanyuan Nie

    2017-09-01

    Full Text Available Vessel traffic flow is a key parameter for channel-through capacity and is of great significance to vessel traffic management, channel and port design and navigational risk evaluation. Based on the study of parameters of characteristics of vessel traffic flow related to channel-through capacity, this paper puts forward a brand-new mathematical model for one-way channel-through capacity in which parameters of channel length, vessel arrival rate and velocity difference in different vessels are involved and a theoretical calculating mechanism for the channel-through capacity is provided. In order to verify availability and reliability of the model, extensive simulation studies have been carried out and based on the historical AIS data, an analytical case study on the Xiazhimen Channel validating the proposed model is presented. Both simulation studies and the case study show that the proposed model is valid and all relative parameters can be readjusted and optimized to further improve the channel-through capacity. Thus, all studies demonstrate that the model is valuable for channel design and vessel management.

  14. Distinguishing between Rural and Urban Road Segment Traffic Safety Based on Zero-Inflated Negative Binomial Regression Models

    Directory of Open Access Journals (Sweden)

    Xuedong Yan

    2012-01-01

    Full Text Available In this study, the traffic crash rate, total crash frequency, and injury and fatal crash frequency were taken into consideration for distinguishing between rural and urban road segment safety. The GIS-based crash data during four and half years in Pikes Peak Area, US were applied for the analyses. The comparative statistical results show that the crash rates in rural segments are consistently lower than urban segments. Further, the regression results based on Zero-Inflated Negative Binomial (ZINB regression models indicate that the urban areas have a higher crash risk in terms of both total crash frequency and injury and fatal crash frequency, compared to rural areas. Additionally, it is found that crash frequencies increase as traffic volume and segment length increase, though the higher traffic volume lower the likelihood of severe crash occurrence; compared to 2-lane roads, the 4-lane roads have lower crash frequencies but have a higher probability of severe crash occurrence; and better road facilities with higher free flow speed can benefit from high standard design feature thus resulting in a lower total crash frequency, but they cannot mitigate the severe crash risk.

  15. Communicating climate change adaptation information using web-based platforms

    Science.gov (United States)

    Karali, Eleni; Mattern, Kati

    2017-07-01

    To facilitate progress in climate change adaptation policy and practice, it is important not only to ensure the production of accurate, comprehensive and relevant information, but also the easy, timely and affordable access to it. This can contribute to better-informed decisions and improve the design and implementation of adaptation policies and other relevant initiatives. Web-based platforms can play an important role in communicating and distributing data, information and knowledge that become constantly available, reaching out to a large group of potential users. Indeed in the last decade there has been an extensive increase in the number of platforms developed for this purpose in many fields including climate change adaptation. This short paper concentrates on the web-based adaptation platforms developed in Europe. It provides an overview of the recently emerged landscape, examines the basic characteristics of a set of platforms that operate at national, transnational and European level, and discusses some of the key challenges related to their development, maintenance and overall management. Findings presented in this short paper are discussed in greater detailed in the Technical Report of the European Environment Agency Overview of climate change adaptation platforms in Europe.

  16. 49 CFR 1139.2 - Traffic study.

    Science.gov (United States)

    2010-10-01

    ... “base-calendar year—actual.” The study shall include a probability sampling of the actual traffic... 49 Transportation 8 2010-10-01 2010-10-01 false Traffic study. 1139.2 Section 1139.2... of General Commodities § 1139.2 Traffic study. (a) The respondents shall submit a traffic study for...

  17. Real-Time Microscopic Traffic Simulation and Optimization at Intersections with Video Traffic Detection

    OpenAIRE

    Liang, Zijun; Flötteröd, Yun-Pang; Chen, Hong; Sohr, Alexander; Bei, Xiaoxu; Bottazzi, Maximiliano; Trumpold, Jan

    2018-01-01

    In this paper, real-time vehicular data from video traffic detection (VTD) are used for minimizing the travel delay at intersections and a real-time traffic optimization model, based on the SUMO traffic simulation software, is established accordingly. The proposed model is implemented in a small industrial control computer which serves as the communication interface between the traffic signal control system, the traffic simulation and optimization model and the real-time video traffic detecti...

  18. Adaptive Knowledge Management of Project-Based Learning

    Science.gov (United States)

    Tilchin, Oleg; Kittany, Mohamed

    2016-01-01

    The goal of an approach to Adaptive Knowledge Management (AKM) of project-based learning (PBL) is to intensify subject study through guiding, inducing, and facilitating development knowledge, accountability skills, and collaborative skills of students. Knowledge development is attained by knowledge acquisition, knowledge sharing, and knowledge…

  19. Coupled interference based rate adaptation in ad hoc networks

    CSIR Research Space (South Africa)

    Awuor, F

    2011-09-01

    Full Text Available to transmit at the minimum transmission power enough to sustain connectivity. This paper proposes coupled interference network utility maximization (NUM) strategy (i.e. CIN) for rate adaptation in WLANs that is solved using ”reverse-engineering” based...

  20. Neuro- PI controller based model reference adaptive control for ...

    African Journals Online (AJOL)

    The control input to the plant is given by the sum of the output of conventional MRAC and the output of NN. The proposed Neural Network -based Model Reference Adaptive Controller (NN-MRAC) can significantly improve the system behavior and force the system to follow the reference model and minimize the error ...

  1. Vision-based adaptive cruise control using pattern matching

    CSIR Research Space (South Africa)

    Kanjee, R

    2013-10-01

    Full Text Available Adaptive Cruise Control (ACC) is a relatively new system designed to assist automobile drivers in maintaining a safe following distance. This paper proposes and validates a vision-based ACC system which uses a single camera to obtain the clearance...

  2. An adaptive image denoising method based on local parameters ...

    Indian Academy of Sciences (India)

    An adaptive image denoising method based on local parameters optimization. 881 the computations and the directional decomposition is done using the directional filter banks. (DFB). Then, the Donoho and Johnstone's threshold is used to modify the coefficients, which in turn provide the noise-free image on applying the ...

  3. Rate adaptation in ad hoc networks based on pricing

    CSIR Research Space (South Africa)

    Awuor, F

    2011-09-01

    Full Text Available to transmit at high power leading to abnormal interference in the network hence degrades network performance (i.e. low data rates, loss of connectivity among others). In this paper, the authors propose rate adaptation based on pricing (RAP) algorithm...

  4. Power Efficient Service Differentiation Based on Traffic-Aware Survivable Elastic Optical Networks

    DEFF Research Database (Denmark)

    Turus, Ioan; Fagertun, Anna Manolova; Dittmann, Lars

    2014-01-01

    sections.Best-effort connections do not have any associated protection.Two scenarios are implemented and compared. The first, the baseline approach,does not take into account any traffic-aware strategies while the second one, the proposed approach,includes energy reduction strategies taking into account...

  5. A scalable acoustic sensor network for model based monitoring of urban traffic noise

    NARCIS (Netherlands)

    Basten, T.G.H.; Wessels, P.W.; Eerden, F.J.M. van der

    2012-01-01

    A good understanding of the acoustic environment due to traffic in urban areas is very important. Long term monitoring within large areas provides a clear insight in the actual noise situation. This is needed to take appropriate and cost efficient measures; to asses the effect of measures by

  6. A smart camera based traffic enforcement system: experiences from the field

    Science.gov (United States)

    Sidla, Oliver; Loibner, Gernot

    2013-03-01

    The observation and monitoring of traffic with smart vision systems for the purpose of improving traffic safety has a big potential. Embedded vision systems can count vehicles and estimate the state of traffic along the road, they can supplement or replace loop sensors with their limited local scope, radar which measures the speed, presence and number of vehicles. This work presents a vision system which has been built to detect and report traffic rule violations at unsecured railway crossings which pose a threat to drivers day and night. Our system is designed to detect and record vehicles passing over the railway crossing after the red light has been activated. Sparse optical flow in conjunction with motion clustering is used for real-time motion detection in order to capture these safety critical events. The cameras are activated by an electrical signal from the railway when the red light turns on. If they detect a vehicle moving over the stopping line, and it is well over this limit, an image sequence will be recorded and stored onboard for later evaluation. The system has been designed to be operational in all weather conditions, delivering human-readable license plate images even under the worst illumination conditions like direct incident sunlight direct view into or vehicle headlights. After several months of operation in the field we can report on the performance of the system, its hardware implementation as well as the implementation of algorithms which have proven to be usable in this real-world application.

  7. Volunteer-Based System for classification of traffic in computer networks

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Balachandran, Kartheepan; Riaz, M. Tahir

    2011-01-01

    To overcome the drawbacks of existing methods for traffic classification (by ports, Deep Packet Inspection, statistical classification) a new system was developed, in which the data are collected from client machines. This paper presents design of the system, implementation, initial runs...

  8. A behavior-based framework for assessing barrier effects to wildlife from vehicle traffic volume

    Science.gov (United States)

    Sandra L. Jacobson; Leslie L. Bliss-Ketchum; Catherine E. de Rivera; Winston P. Smith; D. P. C. Peters

    2016-01-01

    Roads, while central to the function of human society, create barriers to animal movement through collisions and habitat fragmentation. Barriers to animal movement affect the evolution and trajectory of populations. Investigators have attempted to use traffic volume, the number of vehicles passing a point on a road segment, to predict effects to wildlife populations...

  9. Multivariate correlation analysis technique based on euclidean distance map for network traffic characterization

    NARCIS (Netherlands)

    Tan, Zhiyuan; Jamdagni, Aruna; He, Xiangjian; Nanda, Priyadarsi; Liu, Ren Ping; Qing, Sihan; Susilo, Willy; Wang, Guilin; Liu, Dongmei

    2011-01-01

    The quality of feature has significant impact on the performance of detection techniques used for Denial-of-Service (DoS) attack. The features that fail to provide accurate characterization for network traffic records make the techniques suffer from low accuracy in detection. Although researches

  10. Adaptation.

    Science.gov (United States)

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  11. Improving the evidence for ecosystem-based adaptation

    Energy Technology Data Exchange (ETDEWEB)

    Reid, Hannah

    2011-11-15

    Ecosystem-based approaches to adaptation (EBA) integrate the use of biodiversity and ecosystem services into an overall strategy for helping people adapt to climate change. The body of scientific evidence that indicates how effective they are is in some cases lacking but in other cases is dispersed across a range of related fields, such as natural resource management, disaster risk reduction and agroecology, from which it needs to be synthesised. Without presenting and strengthening this evidence in a consolidated way, EBA cannot secure the policy traction at local, national and international levels that it merits.

  12. A phoneme-based student model for adaptive spelling training

    OpenAIRE

    Baschera, Gian-Marco; Gross, Markus H.

    2009-01-01

    We present a novel phoneme-based student model for spelling training. Our model is data driven, adapts to the user and provides information for, e.g., optimal word selection. We describe spelling errors using a set of features accounting for phonemic, capitalization, typo, and other error categories. We compute the influence of individual features on the error expectation values based on previous input data using Poisson regression. This enables us to predict error expectation values and to c...

  13. Biological Bases for Radiation Adaptive Responses in the Lung

    Energy Technology Data Exchange (ETDEWEB)

    Scott, Bobby R. [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Lin, Yong [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Wilder, Julie [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Belinsky, Steven [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States)

    2015-03-01

    Our main research objective was to determine the biological bases for low-dose, radiation-induced adaptive responses in the lung, and use the knowledge gained to produce an improved risk model for radiation-induced lung cancer that accounts for activated natural protection, genetic influences, and the role of epigenetic regulation (epiregulation). Currently, low-dose radiation risk assessment is based on the linear-no-threshold hypothesis, which now is known to be unsupported by a large volume of data.

  14. An Innovative Adaptive Pushover Procedure Based on Storey Shear

    International Nuclear Information System (INIS)

    Shakeri, Kazem; Shayanfar, Mohsen A.

    2008-01-01

    Since the conventional pushover analyses are unable to consider the effect of the higher modes and progressive variation in dynamic properties, recent years have witnessed the development of some advanced adaptive pushover methods. However in these methods, using the quadratic combination rules to combine the modal forces result in a positive value in load pattern at all storeys and the reversal sign of the modes is removed; consequently these methods do not have a major advantage over their non-adaptive counterparts. Herein an innovative adaptive pushover method based on storey shear is proposed which can take into account the reversal signs in higher modes. In each storey the applied load pattern is derived from the storey shear profile; consequently, the sign of the applied loads in consecutive steps could be changed. Accuracy of the proposed procedure is examined by applying it to a 20-storey steel building. It illustrates a good estimation of the peak response in inelastic phase

  15. Adaptive Control for Robotic Manipulators Base on RBF Neural Network

    Directory of Open Access Journals (Sweden)

    MA Jing

    2013-09-01

    Full Text Available An adaptive neural network controller is brought forward by the paper to solve trajectory tracking problems of robotic manipulators with uncertainties. The first scheme consists of a PD feedback and a dynamic compensator which is composed by neural network controller and variable structure controller. Neutral network controller is designed to adaptive learn and compensate the unknown uncertainties, variable structure controller is designed to eliminate approach errors of neutral network. The adaptive weight learning algorithm of neural network is designed to ensure online real-time adjustment, offline learning phase is not need; Global asymptotic stability (GAS of system base on Lyapunov theory is analysised to ensure the convergence of the algorithm. The simulation result s show that the kind of the control scheme is effective and has good robustness.

  16. Searching for adaptive traits in genetic resources - phenology based approach

    Science.gov (United States)

    Bari, Abdallah

    2015-04-01

    Searching for adaptive traits in genetic resources - phenology based approach Abdallah Bari, Kenneth Street, Eddy De Pauw, Jalal Eddin Omari, and Chandra M. Biradar International Center for Agricultural Research in the Dry Areas, Rabat Institutes, Rabat, Morocco Phenology is an important plant trait not only for assessing and forecasting food production but also for searching in genebanks for adaptive traits. Among the phenological parameters we have been considering to search for such adaptive and rare traits are the onset (sowing period) and the seasonality (growing period). Currently an application is being developed as part of the focused identification of germplasm strategy (FIGS) approach to use climatic data in order to identify crop growing seasons and characterize them in terms of onset and duration. These approximations of growing period characteristics can then be used to estimate flowering and maturity dates for dryland crops, such as wheat, barley, faba bean, lentils and chickpea, and assess, among others, phenology-related traits such as days to heading [dhe] and grain filling period [gfp]. The approach followed here is based on first calculating long term average daily temperatures by fitting a curve to the monthly data over days from beginning of the year. Prior to the identification of these phenological stages the onset is extracted first from onset integer raster GIS layers developed based on a model of the growing period that considers both moisture and temperature limitations. The paper presents some examples of real applications of the approach to search for rare and adaptive traits.

  17. Design and Evaluation of a Mathematical Optimization Model for Traffic Signal Plan Transition Based on Social Cost Function

    Directory of Open Access Journals (Sweden)

    Rita Peñabaena-Niebles

    2017-01-01

    Full Text Available Signal plan transition is the process of changing from one timing plan to another. It begins when the first intersection starts adjusting signal timing plans and ends when the last intersection completes adjusting signal timing plans. The transition between signal timing plans is required because traffic patterns change during the day. Therefore, it is necessary to modify signal timing parameters offset, phase split, and cycle length for different expectations of traffic volume. This paper presents an alternative and new mathematical model to enhance the performance of traffic signals coordination at intersections during the transition phase. This model is oriented to describe the transition regarding coordination parameters in all intersections of an arterial road for minimizing the social cost during the transition phase expressed in function of costs due to delays, fuel consumption, and air emissions. An ant colony algorithm was designed, coded, and simulated to find the optimal transition parameters using available data. The model was evaluated based on its ability to minimize social costs during the transition period. Results showed that the proposed method performs better than traditional ones.

  18. Energy-efficient multicast traffic grooming strategy based on light-tree splitting for elastic optical networks

    Science.gov (United States)

    Liu, Huanlin; Yin, Yarui; Chen, Yong

    2017-07-01

    In order to address the problem of optimizing the spectrum resources and power consumption in elastic optical networks (EONs), we investigate the potential gains by jointly employing the light-tree splitting and traffic grooming for multicast requests. An energy-efficient multicast traffic grooming strategy based on light-tree splitting (EED-MTGS-LS) is proposed in this paper. Firstly, we design a traffic pre-processing mechanism to decide the multicast requests' routing order, which considers the request's bandwidth requirement and physical hops synthetically. Then, by dividing a light-tree to some sub-light-trees and grooming the request to these sub-light-trees, the light-tree sharing ratios of multicast requests can be improved. What's more, a priority scheduling vector is constructed, which aims to improve the success rate of spectrum assignment for grooming requests. Finally, a grooming strategy is designed to optimize the total power consumption by reducing the use of transponders and IP routers during routing. Simulation results show that the proposed strategy can significantly improve the spectrum utilization and save the power consumption.

  19. "I CAMMINI DELLA REGINA" - Open Source based tools for preserving and culturally exploring historical traffic routes.

    Science.gov (United States)

    Cannata, Massimiliano; Colombo, Massimo; Antonovic, Milan; Cardoso, Mirko; Delucchi, Andrea; Gianocca, Giancarlo; Brovelli, Maria Antonia

    2015-04-01

    "I CAMMINI DELLA REGINA" (The Via Regina Paths) is an Interreg project funded within the transnational cooperation program between Italy and Switzerland 2007-2013. The aim of this project is the preservation and valorization of the cultural heritage linked to the walking historically paths crossing, connecting and serving the local territories. With the approach of leveraging the already existing tools, which generally consist of technical descriptions of the paths, the project uses the open source geospatial technologies to deploy innovative solutions which can fill some of the gaps in historical-cultural tourism offers. The Swiss part, and particularly the IST-SUPSI team, has been focusing its activities in the realization of two innovative solutions: a mobile application for the survey of historical paths and a storytelling system for immersive cultural exploration of the historical paths. The former, based on Android, allows to apply in a revised manner a consolidated and already successfully used methodology of survey focused on the conservation of the historical paths (Inventory of historical traffic routes in Switzerland). Up to now operators could rely only on hand work based on a combination of notes, pictures and GPS devices synthesized in manually drawn maps; this procedure is error prone and shows many problems both in data updating and extracting for elaborations. Thus it has been created an easy to use interface which allows to map, according to a newly developed spatially enabled data model, paths, morphological elements, and multimedia notes. When connected to the internet the application can send the data to a web service which, after applying linear referencing and further elaborating the data, makes them available using open standards. The storytelling system has been designed to provide users with cultural insights embedded in a multimedial and immersive geospatial portal. Whether the tourist is exploring physically or virtually the desired

  20. Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator

    International Nuclear Information System (INIS)

    Zhao, Yibo; Jiang, Yi; Feng, Jiuchao; Wu, Lifu

    2016-01-01

    Highlights: • A novel nonlinear Wiener adaptive filters based on the backslash operator are proposed. • The identification approach to the memristor-based chaotic systems using the proposed adaptive filters. • The weight update algorithm and convergence characteristics for the proposed adaptive filters are derived. - Abstract: Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error.

  1. Receiver Based Traffic Control Mechanism to Protect Low Capacity Network in Infrastructure Based Wireless Mesh Network

    Science.gov (United States)

    Gilani, Syed Sherjeel Ahmad; Zubair, Muhammad; Khan, Zeeshan Shafi

    Infrastructure-based Wireless Mesh Networks are emerging as an affordable, robust, flexible and scalable technology. With the advent of Wireless Mesh Networks (WMNs) the dream of connecting multiple technology based networks seems to come true. A fully secure WMN is still a challenge for the researchers. In infrastructure-based WMNs almost all types of existing Wireless Networks like Wi-Fi, Cellular, WiMAX, and Sensor etc can be connected through Wireless Mesh Routers (WMRs). This situation can lead to a security problem. Some nodes can be part of the network with high processing power, large memory and least energy issues while others may belong to a network having low processing power, small memory and serious energy limitations. The later type of the nodes is very much vulnerable to targeted attacks. In our research we have suggested to set some rules on the WMR to mitigate these kinds of targeted flooding attacks. The WMR will then share those set of rules with other WMRs for Effective Utilization of Resources.

  2. Stochastic Model of Traffic Jam and Traffic Signal Control

    Science.gov (United States)

    Shin, Ji-Sun; Cui, Cheng-You; Lee, Tae-Hong; Lee, Hee-Hyol

    Traffic signal control is an effective method to solve the traffic jam. and forecasting traffic density has been known as an important part of the Intelligent Transportation System (ITS). The several methods of the traffic signal control are known such as random walk method, Neuron Network method, Bayesian Network method, and so on. In this paper, we propose a new method of a traffic signal control using a predicted distribution of traffic jam based on a Dynamic Bayesian Network model. First, a forecasting model to predict a probabilistic distribution of the traffic jam during each period of traffic lights is built. As the forecasting model, the Dynamic Bayesian Network is used to predict the probabilistic distribution of a density of the traffic jam. According to measurement of two crossing points for each cycle, the inflow and outflow of each direction and the number of standing vehicles at former cycle are obtained. The number of standing vehicle at k-th cycle will be calculated synchronously. Next, the probabilistic distribution of the density of standing vehicle in each cycle will be predicted using the Dynamic Bayesian Network constructed for the traffic jam. And then a control rule to adjust the split and the cycle to increase the probability between a lower limit and ceiling of the standing vehicles is deduced. As the results of the simulation using the actual traffic data of Kitakyushu city, the effectiveness of the method is shown.

  3. Effect of cooling procedure on final denture base adaptation.

    Science.gov (United States)

    Ganzarolli, S M; Rached, R N; Garcia, R C M R; Del Bel Cury, A A

    2002-08-01

    Well-fitted dentures prevent hyperplasic lesions, provide chewing efficiency and promote patient's comfort. Several factors may affect final adaptation of dentures, as the type of the acrylic resin, the flask cooling procedure and the water uptake. This investigation evaluated the effect of water storage and two different cooling procedures [bench cooling (BC) for 2 h; running water (RW) at 20 degrees C for 45 min] on the final adaptation of denture bases. A heat-cured acrylic resin (CL, Clássico, Clássico Artigos Odontológicos) and two microwave-cured acrylic resins [Acron MC, (AC) GC Dent. Ind. Corp.; Onda Cryl (OC), Clássico Artigos Odontológicos] were used to make the bases. Adaptation was assessed by measuring the weight of an intervening layer of silicone impression material between the base and the master die. Data was submitted to ANOVA and Tukey's test (0.05). The following means were found: (BC) CL=0.72 +/- 0.03 a; AC=0.70 +/- 0.03 b; OC=0.76 +/- 0.04 c//(RW) CL= 1.00 +/- 0.11 a; AC=1.00 +/- 0.12 a; OC=0.95 +/- 0.10 a. Different labels join groups that are not statistically different (P > 0.05). Comparisons are made among groups submitted to the same cooling procedure (BC or RW). The conclusions are: interaction of type of material and cooling procedure had a statistically significant effect on the final adaptation of the denture bases (P 0.05) on the final adaptation.

  4. Contraction theory based adaptive synchronization of chaotic systems

    International Nuclear Information System (INIS)

    Sharma, B.B.; Kar, I.N.

    2009-01-01

    Contraction theory based stability analysis exploits the incremental behavior of trajectories of a system with respect to each other. Application of contraction theory provides an alternative way for stability analysis of nonlinear systems. This paper considers the design of a control law for synchronization of certain class of chaotic systems based on backstepping technique. The controller is selected so as to make the error dynamics between the two systems contracting. Synchronization problem with and without uncertainty in system parameters is discussed and necessary stability proofs are worked out using contraction theory. Suitable adaptation laws for unknown parameters are proposed based on the contraction principle. The numerical simulations verify the synchronization of the chaotic systems. Also parameter estimates converge to their true values with the proposed adaptation laws.

  5. Adaptive Human aware Navigation based on Motion Pattern Analysis

    DEFF Research Database (Denmark)

    Tranberg, Søren; Svenstrup, Mikael; Andersen, Hans Jørgen

    2009-01-01

    Respecting people’s social spaces is an important prerequisite for acceptable and natural robot navigation in human environments. In this paper, we describe an adaptive system for mobile robot navigation based on estimates of whether a person seeks to interact with the robot or not. The estimates...... are based on run-time motion pattern analysis compared to stored experience in a database. Using a potential field centered around the person, the robot positions itself at the most appropriate place relative to the person and the interaction status. The system is validated through qualitative tests...... in a real world setting. The results demonstrate that the system is able to learn to navigate based on past interaction experiences, and to adapt to different behaviors over time....

  6. a Curvature Based Adaptive Neighborhood for Individual Point Cloud Classification

    Science.gov (United States)

    He, E.; Chen, Q.; Wang, H.; Liu, X.

    2017-09-01

    As a key step in 3D scene analysis, point cloud classification has gained a great deal of concerns in the past few years. Due to the uneven density, noise and data missing in point cloud, how to automatically classify the point cloud with a high precision is a very challenging task. The point cloud classification process typically includes the extraction of neighborhood based statistical information and machine learning algorithms. However, the robustness of neighborhood is limited to the density and curvature of the point cloud which lead to a label noise behavior in classification results. In this paper, we proposed a curvature based adaptive neighborhood for individual point cloud classification. Our main improvement is the curvature based adaptive neighborhood method, which could derive ideal 3D point local neighborhood and enhance the separability of features. The experiment result on Oakland benchmark dataset shows that the proposed method can effectively improve the classification accuracy of point cloud.

  7. Characterization and Modeling of Network Traffic

    DEFF Research Database (Denmark)

    Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

    2011-01-01

    This paper attempts to characterize and model backbone network traffic, using a small number of statistics. In order to reduce cost and processing power associated with traffic analysis. The parameters affecting the behaviour of network traffic are investigated and the choice is that inter......-arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values....... The model investigates the traffic generation mechanisms, and grouping traffic into flows and applications....

  8. Adaptive algorithm based on antenna arrays for radio communication systems

    Directory of Open Access Journals (Sweden)

    Fedosov Valentin

    2017-01-01

    always noticeably accelerate traffic at short distances from the access point, but, they are very effective at long distances. The MIMO principle allows reducing the number of errors in radio data interchange (BER without reducing the transmission rate under conditions of multiple signal re-reflections. The work aims at developing an adaptive space-time signal algorithm for a wireless data transmission system designed to improve the efficiency of this system, as well as to study the efficiency of the algorithm to minimizing the error bit probability and maximizing the channel capacity.

  9. A V2I-based real-time traffic density estimation system in urban scenarios

    OpenAIRE

    Barrachina, Javier; Garrido, Piedad; Fogue, Manuel; Martínez, Francisco J.; Cano Escribá, Juan Carlos; Tavares De Araujo Cesariny Calafate, Carlos Miguel; Manzoni, Pietro

    2015-01-01

    The final publication is available at Springer via http://dx.doi.org/10.1007/s11277-015-2392-4 The number of vehicles in our roads is drastically increasing, especially in developing countries. In addition, these vehicles tend to be concentrated in urban areas which present a large population. Since traffic jams have important and mostly negative consequences, such as increasing travel time, fuel consumption, and air pollution, governments are making efforts to alleviate the i...

  10. Prescription medicines and the risk of road traffic crashes: a French registry-based study.

    Directory of Open Access Journals (Sweden)

    Ludivine Orriols

    2010-11-01

    Full Text Available In recent decades, increased attention has been focused on the impact of disabilities and medicinal drug use on road safety. The aim of our study was to investigate the association between prescription medicines and the risk of road traffic crashes, and estimate the attributable fraction.We extracted and matched data from three French nationwide databases: the national health care insurance database, police reports, and the national police database of injurious crashes. Drivers identified by their national health care number involved in an injurious crash in France, between July 2005 and May 2008, were included in the study. Medicines were grouped according to the four risk levels of the French classification system (from 0 [no risk] to 3 [high risk]. We included 72,685 drivers involved in injurious crashes. Users of level 2 (odds ratio [OR]  = 1.31 [1.24-1.40] and level 3 (OR  = 1.25 [1.12-1.40] prescription medicines were at higher risk of being responsible for a crash. The association remained after adjustment for the presence of a long-term chronic disease. The fraction of road traffic crashes attributable to levels 2 and 3 medications was 3.3% [2.7%-3.9%]. A within-person case-crossover analysis showed that drivers were more likely to be exposed to level 3 medications on the crash day than on a control day, 30 days earlier (OR  = 1.15 [1.05-1.27].The use of prescription medicines is associated with a substantial number of road traffic crashes in France. In light of the results, warning messages appear to be relevant for level 2 and 3 medications and questionable for level 1 medications. A follow-up study is needed to evaluate the impact of the warning labeling system on road traffic crash prevention.

  11. Implications of plan-based generalization in sensorimotor adaptation.

    Science.gov (United States)

    McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A

    2017-07-01

    Generalization is a fundamental aspect of behavior, allowing for the transfer of knowledge from one context to another. The details of this transfer are thought to reveal how the brain represents what it learns. Generalization has been a central focus in studies of sensorimotor adaptation, and its pattern has been well characterized: Learning of new dynamic and kinematic transformations in one region of space tapers off in a Gaussian-like fashion to neighboring untrained regions, echoing tuned population codes in the brain. In contrast to common allusions to generalization in cognitive science, generalization in visually guided reaching is usually framed as a passive consequence of neural tuning functions rather than a cognitive feature of learning. While previous research has presumed that maximum generalization occurs at the instructed task goal or the actual movement direction, recent work suggests that maximum generalization may occur at the location of an explicitly accessible movement plan. Here we provide further support for plan-based generalization, formalize this theory in an updated model of adaptation, and test several unexpected implications of the model. First, we employ a generalization paradigm to parameterize the generalization function and ascertain its maximum point. We then apply the derived generalization function to our model and successfully simulate and fit the time course of implicit adaptation across three behavioral experiments. We find that dynamics predicted by plan-based generalization are borne out in the data, are contrary to what traditional models predict, and lead to surprising implications for the behavioral, computational, and neural characteristics of sensorimotor adaptation. NEW & NOTEWORTHY The pattern of generalization is thought to reveal how the motor system represents learned actions. Recent work has made the intriguing suggestion that maximum generalization in sensorimotor adaptation tasks occurs at the location of the

  12. Mixing stream and datagram traffic on satellite: A FIFO Order-based Demand Assignment (FODA) Time Division Multiple Access (TDMA) scheme

    Science.gov (United States)

    Beltrame, R.; Bonito, A. B.; Celandroni, N.; Ferro, E.

    1985-11-01

    A FIFO Order based Demand Assignment (FODA) access scheme was designed to handle packetized data and voice traffic in a multiple access satellite broadcast channel of Mbits band. The channel is shared by as many as 64 simultaneously active stations in a range of 255 addressable stations. A sophisticated traffic environment is assumed, including different types of service requirements and an arbitrary load distribution among the stations. The results of 2Mbit/sec simulation tests for an existing hardware environment are presented.

  13. Islanding detection scheme based on adaptive identifier signal estimation method.

    Science.gov (United States)

    Bakhshi, M; Noroozian, R; Gharehpetian, G B

    2017-11-01

    This paper proposes a novel, passive-based anti-islanding method for both inverter and synchronous machine-based distributed generation (DG) units. Unfortunately, when the active/reactive power mismatches are near to zero, majority of the passive anti-islanding methods cannot detect the islanding situation, correctly. This study introduces a new islanding detection method based on exponentially damped signal estimation method. The proposed method uses adaptive identifier method for estimating of the frequency deviation of the point of common coupling (PCC) link as a target signal that can detect the islanding condition with near-zero active power imbalance. Main advantage of the adaptive identifier method over other signal estimation methods is its small sampling window. In this paper, the adaptive identifier based islanding detection method introduces a new detection index entitled decision signal by estimating of oscillation frequency of the PCC frequency and can detect islanding conditions, properly. In islanding conditions, oscillations frequency of PCC frequency reach to zero, thus threshold setting for decision signal is not a tedious job. The non-islanding transient events, which can cause a significant deviation in the PCC frequency are considered in simulations. These events include different types of faults, load changes, capacitor bank switching, and motor starting. Further, for islanding events, the capability of the proposed islanding detection method is verified by near-to-zero active power mismatches. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juarez, Chihuahua (Mexico)

    International Nuclear Information System (INIS)

    Raysoni, Amit U.; Sarnat, Jeremy A.; Sarnat, Stefanie Ebelt; Garcia, Jose Humberto; Holguin, Fernando; Flores Luevano, Silvia; Li, Wen-Whai

    2011-01-01

    Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO 2 ) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO 2 appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children's exposures to these pollutants vary based on the location of their school. - Highlights: → First binational investigation characterizing traffic air pollutants at four schools in El Paso, USA and Cd. Juarez, Mexico. → Paired in-outdoor sampling of PM 2.5 , PM 10-2.5 , reflectance [black carbon(BC)], and NO 2 for 16 weeks in 2008 at each school. → Two schools (one in each city) were located in high traffic density areas and the other two in areas of low traffic density. → Usage of spatially resolved environmental indictors of traffic pollutants in a range of exposure settings. → Substantial intra-urban spatial variability in pollutant concentrations observed between and within the two cities. - Spatial variability in traffic-mediated pollutant concentrations can exist at the intra-urban level and ambient monitoring sites may not accurately represent these concentration gradients.

  15. Adaptation

    International Development Research Centre (IDRC) Digital Library (Canada)

    . Dar es Salaam. Durban. Bloemfontein. Antananarivo. Cape Town. Ifrane ... program strategy. A number of CCAA-supported projects have relevance to other important adaptation-related themes such as disaster preparedness and climate.

  16. Contrast-based sensorless adaptive optics for retinal imaging.

    Science.gov (United States)

    Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

    2015-09-01

    Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

  17. Programmable Ultra-Lightweight System Adaptable Radio Satellite Base Station

    Science.gov (United States)

    Varnavas, Kosta; Sims, Herb

    2015-01-01

    With the explosion of the CubeSat, small sat, and nanosat markets, the need for a robust, highly capable, yet affordable satellite base station, capable of telemetry capture and relay, is significant. The Programmable Ultra-Lightweight System Adaptable Radio (PULSAR) is NASA Marshall Space Flight Center's (MSFC's) software-defined digital radio, developed with previous Technology Investment Programs and Technology Transfer Office resources. The current PULSAR will have achieved a Technology Readiness Level-6 by the end of FY 2014. The extensibility of the PULSAR will allow it to be adapted to perform the tasks of a mobile base station capable of commanding, receiving, and processing satellite, rover, or planetary probe data streams with an appropriate antenna.

  18. Drip irrigation using a PLC based adaptive irrigation system

    OpenAIRE

    Shahidian, S.; Serralheiro, R. P.; Teixeira, J. L.; Santos, F. L.; Oliveira, M. R. G.; Costa, J. L.; Toureiro, C.; Haie, Naim; Machado, R. M.

    2009-01-01

    Most of the water used by man goes to irrigation. A major part of this water is used to irrigate small plots where it is not feasible to implement full-scale Evapotranspiration based irrigation controllers. During the growth season crop water needs do not remain constant and varies depending on the canopy, growth stage and climate conditions such as temperature, wind, relative humidity and solar radiation. Thus, it is necessary to find an economic irrigation controller that can adapt the dail...

  19. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    This paper introduces Rank-based Interactive Evolution (RIE) which is an alternative to interactive evolution driven by computational models of user preferences to generate personalized content. In RIE, the computational models are adapted to the preferences of users which, in turn, are used...... artificial agents. Results suggest that RIE is both faster and more robust than standard interactive evolution and outperforms other state-of-the-art interactive evolution approaches....

  20. Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

    Science.gov (United States)

    Zhang, Yanjun; Tao, Gang; Chen, Mou

    2016-09-01

    This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

  1. Visual-adaptation-mechanism based underwater object extraction

    Science.gov (United States)

    Chen, Zhe; Wang, Huibin; Xu, Lizhong; Shen, Jie

    2014-03-01

    Due to the major obstacles originating from the strong light absorption and scattering in a dynamic underwater environment, underwater optical information acquisition and processing suffer from effects such as limited range, non-uniform lighting, low contrast, and diminished colors, causing it to become the bottleneck for marine scientific research and projects. After studying and generalizing the underwater biological visual mechanism, we explore its advantages in light adaption which helps animals to precisely sense the underwater scene and recognize their prey or enemies. Then, aiming to transform the significant advantage of the visual adaptation mechanism into underwater computer vision tasks, a novel knowledge-based information weighting fusion model is established for underwater object extraction. With this bionic model, the dynamical adaptability is given to the underwater object extraction task, making them more robust to the variability of the optical properties in different environments. The capability of the proposed method to adapt to the underwater optical environments is shown, and its outperformance for the object extraction is demonstrated by comparison experiments.

  2. An adaptive watershed management assessment based on watershed investigation data.

    Science.gov (United States)

    Kang, Min Goo; Park, Seung Woo

    2015-05-01

    The aim of this study was to assess the states of watersheds in South Korea and to formulate new measures to improve identified inadequacies. The study focused on the watersheds of the Han River basin and adopted an adaptive watershed management framework. Using data collected during watershed investigation projects, we analyzed the management context of the study basin and identified weaknesses in water use management, flood management, and environmental and ecosystems management in the watersheds. In addition, we conducted an interview survey to obtain experts' opinions on the possible management of watersheds in the future. The results of the assessment show that effective management of the Han River basin requires adaptive watershed management, which includes stakeholders' participation and social learning. Urbanization was the key variable in watershed management of the study basin. The results provide strong guidance for future watershed management and suggest that nonstructural measures are preferred to improve the states of the watersheds and that consistent implementation of the measures can lead to successful watershed management. The results also reveal that governance is essential for adaptive watershed management in the study basin. A special ordinance is necessary to establish governance and aid social learning. Based on the findings, a management process is proposed to support new watershed management practices. The results will be of use to policy makers and practitioners who can implement the measures recommended here in the early stages of adaptive watershed management in the Han River basin. The measures can also be applied to other river basins.

  3. Citizen Science for Traffic Planning: A Practical Example

    Science.gov (United States)

    Rieke, Matthes; Stasch, Christoph; Autermann, Christian; de Wall, Arne; Remke, Albert; Wulffius, Herwig; Jirka, Simon

    2017-04-01

    Measures affecting traffic flows in urban areas, e.g. changing the configuration of traffic lights, are often causing emotional debates by citizens who are affected by these measures. Up to now, citizens are usually not involved in traffic planning and the evaluation of the decisions that were taken. The enviroCar project provides an open platform for collecting and analyzing car sensor data with GPS position data. On the hardware side, enviroCar relies on using Android smartphones and OBD-II Bluetooth adapters. A Web server component collects and aggregates the readings from the cars, anonymizes them and publishes the data as open data which scientists, public administrations or other third parties can utilize for further analysis. In this work, we provide a general overview on the enviroCar project and present a project in a mid-size city in Germany. The city's administration utilized the enviroCar platform with the help of a traffic system consultancy for including citizens in the evaluation process of different traffic light configurations along major traffic axes. Therefore, a public campaign was started including local workshops to engage the citizens. More than 150 citizens were actively collecting more about 9.500 tracks including about 2.5 million measurements. Dedicated evaluation results for the different traffic axes were computed based on the collected data set. Because the data is publicly available as open data, others may prove and reproduce the evaluation results contributing to an objective discussion of traffic planning measures. In summary, the project illustrates how Citizen Science methods and technologies improve traffic planning and related discussions.

  4. Congestion management in traffic-light intersections via Infinitesimal Perturbation Analysis

    OpenAIRE

    Seatzu, Carla; Wardi, Yorai

    2015-01-01

    We present a flow-control technique in traffic-light intersections, aiming at regulating queue lengths to given reference setpoints. The technique is based on multivariable integrators with adaptive gains, computed at each control cycle by assessing the IPA gradients of the plant functions. Moreover, the IPA gradients are computable on-line despite the absence of detailed models of the traffic flows. The technique is applied to a two-intersection system where it exhibits robustness with respe...

  5. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  6. Framework for consistent traffic and accident statistical data bases = Cadre pour des bases de données statistiques cohérentes sur la circulation et les accidents.

    NARCIS (Netherlands)

    OECD Scientific Expert Group T8

    1988-01-01

    The OECD Road Transport Research Scientific Expert Group T8 "Framework for Consistent Traffic and Accident Statistical Data Bases" was confronted with the old problem of the inconsistency of data between countries, and the lack of some data altogether, especially traffic data for use as a measure of

  7. New Solutions Based On Wireless Networks For Dynamic Traffic Lights Management: A Comparison Between IEEE 802.15.4 And Bluetooth

    Directory of Open Access Journals (Sweden)

    Collotta Mario

    2015-09-01

    Full Text Available The Wireless Sensor Networks are widely used to detect and exchange information and in recent years they have been increasingly involved in Intelligent Transportation System applications, especially in dynamic management of signalized intersections. In fact, the real-time knowledge of information concerning traffic light junctions represents a valid solution to congestion problems. In this paper, a wireless network architecture, based on IEEE 802.15.4 or Bluetooth, in order to monitor vehicular traffic flows near to traffic lights, is introduced. Moreover, an innovative algorithm is proposed in order to determine dynamically green times and phase sequence of traffic lights, based on measured values of traffic flows. Several simulations compare IEEE 802.15.4 and Bluetooth protocols in order to identify the more suitable communication protocol for ITS applications. Furthermore, in order to confirm the validity of the proposed algorithm for the dynamic management of traffic lights, some case studies have been considered and several simulations have been performed.

  8. Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

    Science.gov (United States)

    Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

    2012-01-01

    This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

  9. Profile-based adaptive anomaly detection for network security.

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Pengchu C. (Sandia National Laboratories, Albuquerque, NM); Durgin, Nancy Ann

    2005-11-01

    As information systems become increasingly complex and pervasive, they become inextricably intertwined with the critical infrastructure of national, public, and private organizations. The problem of recognizing and evaluating threats against these complex, heterogeneous networks of cyber and physical components is a difficult one, yet a solution is vital to ensuring security. In this paper we investigate profile-based anomaly detection techniques that can be used to address this problem. We focus primarily on the area of network anomaly detection, but the approach could be extended to other problem domains. We investigate using several data analysis techniques to create profiles of network hosts and perform anomaly detection using those profiles. The ''profiles'' reduce multi-dimensional vectors representing ''normal behavior'' into fewer dimensions, thus allowing pattern and cluster discovery. New events are compared against the profiles, producing a quantitative measure of how ''anomalous'' the event is. Most network intrusion detection systems (IDSs) detect malicious behavior by searching for known patterns in the network traffic. This approach suffers from several weaknesses, including a lack of generalizability, an inability to detect stealthy or novel attacks, and lack of flexibility regarding alarm thresholds. Our research focuses on enhancing current IDS capabilities by addressing some of these shortcomings. We identify and evaluate promising techniques for data mining and machine-learning. The algorithms are ''trained'' by providing them with a series of data-points from ''normal'' network traffic. A successful algorithm can be trained automatically and efficiently, will have a low error rate (low false alarm and miss rates), and will be able to identify anomalies in ''pseudo real-time'' (i.e., while the intrusion is still in progress

  10. Traffic sign recognition based on a context-aware scale-invariant feature transform approach

    Science.gov (United States)

    Yuan, Xue; Hao, Xiaoli; Chen, Houjin; Wei, Xueye

    2013-10-01

    A new context-aware scale-invariant feature transform (CASIFT) approach is proposed, which is designed for the use in traffic sign recognition (TSR) systems. The following issues remain in previous works in which SIFT is used for matching or recognition: (1) SIFT is unable to provide color information; (2) SIFT only focuses on local features while ignoring the distribution of global shapes; (3) the template with the maximum number of matching points selected as the final result is instable, especially for images with simple patterns; and (4) SIFT is liable to result in errors when different images share the same local features. In order to resolve these problems, a new CASIFT approach is proposed. The contributions of the work are as follows: (1) color angular patterns are used to provide the color distinguishing information; (2) a CASIFT which effectively combines local and global information is proposed; and (3) a method for computing the similarity between two images is proposed, which focuses on the distribution of the matching points, rather than using the traditional SIFT approach of selecting the template with maximum number of matching points as the final result. The proposed approach is particularly effective in dealing with traffic signs which have rich colors and varied global shape distribution. Experiments are performed to validate the effectiveness of the proposed approach in TSR systems, and the experimental results are satisfying even for images containing traffic signs that have been rotated, damaged, altered in color, have undergone affine transformations, or images which were photographed under different weather or illumination conditions.

  11. Modeling Vehicle Collision Angle in Traffic Crashes Based on Three-Dimensional Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Nengchao Lyu

    2017-02-01

    Full Text Available In road traffic accidents, the analysis of a vehicle’s collision angle plays a key role in identifying a traffic accident’s form and cause. However, because accurate estimation of vehicle collision angle involves many factors, it is difficult to accurately determine it in cases in which less physical evidence is available and there is a lack of monitoring. This paper establishes the mathematical relation model between collision angle, deformation, and normal vector in the collision region according to the equations of particle deformation and force in Hooke’s law of classical mechanics. At the same time, the surface reconstruction method suitable for a normal vector solution is studied. Finally, the estimation model of vehicle collision angle is presented. In order to verify the correctness of the model, verification of multi-angle collision experiments and sensitivity analysis of laser scanning precision for the angle have been carried out using three-dimensional (3D data obtained by a 3D laser scanner in the collision deformation zone. Under the conditions with which the model has been defined, validation results show that the collision angle is a result of the weighted synthesis of the normal vector of the collision point and the weight value is the deformation of the collision point corresponding to normal vectors. These conclusions prove the applicability of the model. The collision angle model proposed in this paper can be used as the theoretical basis for traffic accident identification and cause analysis. It can also be used as a theoretical reference for the study of the impact deformation of elastic materials.

  12. Adaptive Sensing Based on Profiles for Sensor Systems

    Directory of Open Access Journals (Sweden)

    Yoshiteru Ishida

    2009-10-01

    Full Text Available This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission.

  13. Episodic memories predict adaptive value-based decision-making

    Science.gov (United States)

    Murty, Vishnu; FeldmanHall, Oriel; Hunter, Lindsay E.; Phelps, Elizabeth A; Davachi, Lila

    2016-01-01

    Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory—specifically item versus associative memory—in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to re-engage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to re-engage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations—such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior. PMID:26999046

  14. Intelligent lightening system of urban and rural road traffic based on pyroelectric infrared detector

    Science.gov (United States)

    Miao, Man-Xiang

    2007-12-01

    By using the photo-voltage characteristics of pyroelectric infrared detector to fulfill signal acquisition, the detecting signal is processed with the core of a single chip microprocessor AT89C51. AT89C51 controls the CAN bus controller SJA1000/transceiver 82C250 to structure CAN bus communication system to transmit data through serial interface MAX232 connected with PC. The intelligent lightening system of urban and rural road traffic was carried out. In this paper, its construction and part's methods of hardware and software design were introduced in detail.

  15. Image Superresolution Based on Locally Adaptive Mixed-Norm

    Directory of Open Access Journals (Sweden)

    Osama A. Omer

    2010-01-01

    Full Text Available In a typical superresolution algorithm, fusion error modeling, including registration error and additive noise, has a great influence on the performance of the super-resolution algorithms. In this letter, we show that the quality of the reconstructed high-resolution image can be increased by exploiting proper model for the fusion error. To properly model the fusion error, we propose to minimize a cost function that consists of locally and adaptively weighted L1- and L2-norms considering the error model. Binary weights are used so as to adaptively select L1- or L2-norm, based on the local errors. Simulation results demonstrate that proposed algorithm can overcome disadvantages of using either L1- or L2-norm.

  16. An adaptive single pole autoreclosure based on zero sequence power

    Energy Technology Data Exchange (ETDEWEB)

    Elkalashy, Nagy I.; Darwish, Hatem A.; Taalab, Abdel-Maksoud I.; Izzularab, Mohmmad A. [Electrical Engineering Department, Faculty of Engineering, Menoufiya University, Shebin Elkom 32511 (Egypt)

    2007-04-15

    In this paper, a novel adaptive single pole autoreclosure is introduced. This reclosure is based on monitoring the fundamental component of the zero sequence instantaneous power to detect the extinction instant of the arc in its secondary period. Thus, adaptive closing instant can be achieved. The concept of reclosure is validated via typical examples of transmission line exposed to ground arcing fault. Effects of fault location and load flow on the accuracy of the technique are examined. Discriminatory zones of the secondary arc period in the zero sequence power domains are determined. A proposed threshold for the reclosing instant is introduced and examined. Validation of the proposed algorithm is verified via Digital Signal Processing (DSP) experimental test set-up. The test results corroborate the efficacy of proposed technique. (author)

  17. Community-based adaptation to climate change: an update

    Energy Technology Data Exchange (ETDEWEB)

    Ayers, Jessica; Huq, Saleemul

    2009-06-15

    Over a billion people - the world's poorest and most bulnerable communities – will bear the brunt of climate change. For them, building local capacity to cope is a vital step towards resilience. Community-based adaptation (CBA) is emerging as a key response to this challenge. Tailored to local cultures and conditions, CBA supports and builds on autonomous adaptations to climate variability, such as the traditional baira or floating gardens of Bangladesh, which help small farmers' crops survive climate-driven floods. Above all, CBA is participatory – a process involving both local stakeholders, and development and disaster risk reduction practitioners. As such, it builds on existing cultural norms while addressing local development issues that contribute to climate vulnerability. CBA is now gaining ground in many regions, and is ripe for the reassessment offered here.

  18. Adaptive differential correspondence imaging based on sorting technique

    Directory of Open Access Journals (Sweden)

    Heng Wu

    2017-04-01

    Full Text Available We develop an adaptive differential correspondence imaging (CI method using a sorting technique. Different from the conventional CI schemes, the bucket detector signals (BDS are first processed by a differential technique, and then sorted in a descending (or ascending order. Subsequently, according to the front and last several frames of the sorted BDS, the positive and negative subsets (PNS are created by selecting the relative frames from the reference detector signals. Finally, the object image is recovered from the PNS. Besides, an adaptive method based on two-step iteration is designed to select the optimum number of frames. To verify the proposed method, a single-detector computational ghost imaging (GI setup is constructed. We experimentally and numerically compare the performance of the proposed method with different GI algorithms. The results show that our method can improve the reconstruction quality and reduce the computation cost by using fewer measurement data.

  19. Low-power adaptive filter based on RNS components

    DEFF Research Database (Denmark)

    Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Del Re, Andrea

    2007-01-01

    In this paper a low-power implementation of an adaptive FIR filter is presented. The filter is designed to meet the constraints of channel equalization for fixed wireless communications that typically requires a large number of taps, but a serial updating of the filter coefficients, based...... on the least mean squares (LMS) algorithm, is allowed. Previous work showed that the use of the residue number system (RNS) for the variable FIR filter grants advantages both in area and power consumption. On the other hand, the use of a binary serial implementation of the adaptation algorithm eliminates...... the need for complex scaling circuits in RNS. The advantages in terms of area and speed of the presented filter, with respect to its two's complement counterpart, are evaluated for implementations in standard cells....

  20. Evaluation-Function-based Model-free Adaptive Fuzzy Control

    Directory of Open Access Journals (Sweden)

    Agus Naba

    2016-12-01

    Full Text Available Designs of adaptive fuzzy controllers (AFC are commonly based on the Lyapunov approach, which requires a known model of the controlled plant. They need to consider a Lyapunov function candidate as an evaluation function to be minimized. In this study these drawbacks were handled by designing a model-free adaptive fuzzy controller (MFAFC using an approximate evaluation function defined in terms of the current state, the next state, and the control action. MFAFC considers the approximate evaluation function as an evaluative control performance measure similar to the state-action value function in reinforcement learning. The simulation results of applying MFAFC to the inverted pendulum benchmark verified the proposed scheme’s efficacy.

  1. Goal based mesh adaptivity for fixed source radiation transport calculations

    International Nuclear Information System (INIS)

    Baker, C.M.J.; Buchan, A.G.; Pain, C.C.; Tollit, B.S.; Goffin, M.A.; Merton, S.R.; Warner, P.

    2013-01-01

    Highlights: ► Derives an anisotropic goal based error measure for shielding problems. ► Reduces the error in the detector response by optimizing the finite element mesh. ► Anisotropic adaptivity captures material interfaces using fewer elements than AMR. ► A new residual based on the numerical scheme chosen forms the error measure. ► The error measure also combines the forward and adjoint metrics in a novel way. - Abstract: In this paper, the application of goal based error measures for anisotropic adaptivity applied to shielding problems in which a detector is present is explored. Goal based adaptivity is important when the response of a detector is required to ensure that dose limits are adhered to. To achieve this, a dual (adjoint) problem is solved which solves the neutron transport equation in terms of the response variables, in this case the detector response. The methods presented can be applied to general finite element solvers, however, the derivation of the residuals are dependent on the underlying finite element scheme which is also discussed in this paper. Once error metrics for the forward and adjoint solutions have been formed they are combined using a novel approach. The two metrics are combined by forming the minimum ellipsoid that covers both the error metrics rather than taking the maximum ellipsoid that is contained within the metrics. Another novel approach used within this paper is the construction of the residual. The residual, used to form the goal based error metrics, is calculated from the subgrid scale correction which is inherent in the underlying spatial discretisation employed

  2. Adaptation

    International Development Research Centre (IDRC) Digital Library (Canada)

    Nairobi, Kenya. 28 Adapting Fishing Policy to Climate Change with the Aid of Scientific and Endogenous Knowledge. Cap Verde, Gambia,. Guinea, Guinea Bissau,. Mauritania and Senegal. Environment and Development in the Third World. (ENDA-TM). Dakar, Senegal. 29 Integrating Indigenous Knowledge in Climate Risk ...

  3. Symbols and warrants for major traffic generator guide signing.

    Science.gov (United States)

    2009-09-01

    The Texas Manual on Uniform Traffic Control Devices (TMUTCD) provides the definition of regular traffic generators based on four population types but not for major traffic generators (MTGs). MTG signs have been considered to supplement the overall si...

  4. An Automatic Traffic Sign Detection and Recognition System Based on Colour Segmentation, Shape Matching, and SVM

    Directory of Open Access Journals (Sweden)

    Safat B. Wali

    2015-01-01

    Full Text Available The main objective of this study is to develop an efficient TSDR system which contains an enriched dataset of Malaysian traffic signs. The developed technique is invariant in variable lighting, rotation, translation, and viewing angle and has a low computational time with low false positive rate. The development of the system has three working stages: image preprocessing, detection, and recognition. The system demonstration using a RGB colour segmentation and shape matching followed by support vector machine (SVM classifier led to promising results with respect to the accuracy of 95.71%, false positive rate (0.9%, and processing time (0.43 s. The area under the receiver operating characteristic (ROC curves was introduced to statistically evaluate the recognition performance. The accuracy of the developed system is relatively high and the computational time is relatively low which will be helpful for classifying traffic signs especially on high ways around Malaysia. The low false positive rate will increase the system stability and reliability on real-time application.

  5. Note on Studying Change Point of LRD Traffic Based on Li's Detection of DDoS Flood Attacking

    Directory of Open Access Journals (Sweden)

    Zhengmin Xia

    2010-01-01

    Full Text Available Distributed denial-of-service (DDoS flood attacks remain great threats to the Internet. To ensure network usability and reliability, accurate detection of these attacks is critical. Based on Li's work on DDoS flood attack detection, we propose a DDoS detection method by monitoring the Hurst variation of long-range dependant traffic. Specifically, we use an autoregressive system to estimate the Hurst parameter of normal traffic. If the actual Hurst parameter varies significantly from the estimation, we assume that DDoS attack happens. Meanwhile, we propose two methods to determine the change point of Hurst parameter that indicates the occurrence of DDoS attacks. The detection rate associated with one method and false alarm rate for the other method are also derived. The test results on DARPA intrusion detection evaluation data show that the proposed approaches can achieve better detection performance than some well-known self-similarity-based detection methods.

  6. Injury characteristics and outcome of road traffic accident among victims at Adult Emergency Department of Tikur Anbessa specialized hospital, Addis Ababa, Ethiopia: a prospective hospital based study.

    Science.gov (United States)

    Seid, Mohammed; Azazh, Aklilu; Enquselassie, Fikre; Yisma, Engida

    2015-05-20

    Road traffic injuries are the eighth leading cause of death globally, and the leading cause of death for young people. More than a million people die each year on the world's roads, and the risk of dying as a result of a road traffic injury is highest in Africa. A prospective hospital based study was undertaken to assess injury characteristics and outcome of road traffic accident among victims at Adult Emergency Department of Tikur Anbessa specialized hospital, Addis Ababa, Ethiopia. A structured pre-tested questionnaire was used to gather the required data. The collected data were analyzed using SPSS version 20.0. Hierarchical multiple regression analysis was used to identify predictors of fatalities among the road traffic crash victims. A total of 230 road traffic accident victims were studied. The majority of the study subjects were men 165 (71.7%) and the male/female ratio was 2.6:1. The victims' ages ranged from 14 to 80 years with the mean and standard deviations of 32.15 and ± 14.38 years respectively. Daily laborers (95 (41.3%)) and students (28 (12.2%)) were the majority of road traffic accident victims. Head (50.4%) and musculoskeletal (extremities) (47.0%) were the most common body region injured. Fractures (78.0%) and open wounds (56.5%) were the most common type of injuries sustained. The overall length of hospital stay (LOS) ranged from 1 day to 61 days with mean (± standard deviation) of 7.12 ± 10.5 days and the mortality rate was 7.4%. Hierarchical multiple regression analysis showed that age of the victims (ß = 0.16, p road traffic accident is a major public health problem. Urgent road traffic accident preventive measures and prompt treatment of the victims are warranted in order to reduce morbidity and mortality among the victims.

  7. New Adaptive Image Quality Assessment Based on Distortion Classification

    Directory of Open Access Journals (Sweden)

    Xin JIN

    2014-01-01

    Full Text Available This paper proposes a new adaptive image quality assessment (AIQA method, which is based on distortion classifying. AIQA contains two parts, distortion classification and image quality assessment. Firstly, we analysis characteristics of the original and distorted images, including the distribution of wavelet coefficient, the ratio of edge energy and inner energy of the differential image block, we divide distorted images into White Noise distortion, JPEG compression distortion and fuzzy distortion. To evaluate the quality of first two type distortion images, we use pixel based structure similarity metric and DCT based structural similarity metric respectively. For those blurriness pictures, we present a new wavelet-based structure similarity algorithm. According to the experimental results, AIQA takes the advantages of different structural similarity metrics, and it’s able to simulate the human visual perception effectively.

  8. Adaptive Rate Sampling and Filtering Based on Level Crossing Sampling

    Directory of Open Access Journals (Sweden)

    Saeed Mian Qaisar

    2009-01-01

    Full Text Available The recent sophistications in areas of mobile systems and sensor networks demand more and more processing resources. In order to maintain the system autonomy, energy saving is becoming one of the most difficult industrial challenges, in mobile computing. Most of efforts to achieve this goal are focused on improving the embedded systems design and the battery technology, but very few studies target to exploit the input signal time-varying nature. This paper aims to achieve power efficiency by intelligently adapting the processing activity to the input signal local characteristics. It is done by completely rethinking the processing chain, by adopting a non conventional sampling scheme and adaptive rate filtering. The proposed approach, based on the LCSS (Level Crossing Sampling Scheme presents two filtering techniques, able to adapt their sampling rate and filter order by online analyzing the input signal variations. Indeed, the principle is to intelligently exploit the signal local characteristics—which is usually never considered—to filter only the relevant signal parts, by employing the relevant order filters. This idea leads towards a drastic gain in the computational efficiency and hence in the processing power when compared to the classical techniques.

  9. Adaptive autoimmunity and Foxp3-based immunoregulation in zebrafish.

    Directory of Open Access Journals (Sweden)

    Francisco J Quintana

    2010-03-01

    Full Text Available Jawed vertebrates generate their immune-receptor repertoire by a recombinatorial mechanism that has the potential to produce harmful autoreactive lymphocytes. In mammals, peripheral tolerance to self-antigens is enforced by Foxp3(+ regulatory T cells. Recombinatorial mechanisms also operate in teleosts, but active immunoregulation is thought to be a late incorporation to the vertebrate lineage.Here we report the characterization of adaptive autoimmunity and Foxp3-based immunoregulation in the zebrafish. We found that zebrafish immunization with an homogenate of zebrafish central nervous system (zCNS triggered CNS inflammation and specific antibodies. We cloned the zebrafish ortholog for mammalian Foxp3 (zFoxp3 which induced a regulatory phenotype on mouse T cells and controlled IL-17 production in zebrafish embryos.Our findings demonstrate the acquisition of active mechanisms of self-tolerance early in vertebrate evolution, suggesting that active regulatory mechanisms accompany the development of the molecular potential for adaptive autoimmunity. Moreover, they identify the zebrafish as a tool to study the molecular pathways controlling adaptive immunity.

  10. An extended framework for adaptive playback-based video summarization

    Science.gov (United States)

    Peker, Kadir A.; Divakaran, Ajay

    2003-11-01

    In our previous work, we described an adaptive fast playback framework for video summarization where we changed the playback rate using the motion activity feature so as to maintain a constant "pace." This method provides an effective way of skimming through video, especially when the motion is not too complex and the background is mostly still, such as in surveillance video. In this paper, we present an extended summarization framework that, in addition to motion activity, uses semantic cues such as face or skin color appearance, speech and music detection, or other domain dependent semantically significant events to control the playback rate. The semantic features we use are computationally inexpensive and can be computed in compressed domain, yet are robust, reliable, and have a wide range of applicability across different content types. The presented framework also allows for adaptive summaries based on preference, for example, to include more dramatic vs. action elements, or vice versa. The user can switch at any time between the skimming and the normal playback modes. The continuity of the video is preserved, and complete omission of segments that may be important to the user is avoided by using adaptive fast playback instead of skipping over long segments. The rule-set and the input parameters can be further modified to fit a certain domain or application. Our framework can be used by itself, or as a subsequent presentation stage for a summary produced by any other summarization technique that relies on generating a sub-set of the content.

  11. Adaptive PID control based on orthogonal endocrine neural networks.

    Science.gov (United States)

    Milovanović, Miroslav B; Antić, Dragan S; Milojković, Marko T; Nikolić, Saša S; Perić, Staniša Lj; Spasić, Miodrag D

    2016-12-01

    A new intelligent hybrid structure used for online tuning of a PID controller is proposed in this paper. The structure is based on two adaptive neural networks, both with built-in Chebyshev orthogonal polynomials. First substructure network is a regular orthogonal neural network with implemented artificial endocrine factor (OENN), in the form of environmental stimuli, to its weights. It is used for approximation of control signals and for processing system deviation/disturbance signals which are introduced in the form of environmental stimuli. The output values of OENN are used to calculate artificial environmental stimuli (AES), which represent required adaptation measure of a second network-orthogonal endocrine adaptive neuro-fuzzy inference system (OEANFIS). OEANFIS is used to process control, output and error signals of a system and to generate adjustable values of proportional, derivative, and integral parameters, used for online tuning of a PID controller. The developed structure is experimentally tested on a laboratory model of the 3D crane system in terms of analysing tracking performances and deviation signals (error signals) of a payload. OENN-OEANFIS performances are compared with traditional PID and 6 intelligent PID type controllers. Tracking performance comparisons (in transient and steady-state period) showed that the proposed adaptive controller possesses performances within the range of other tested controllers. The main contribution of OENN-OEANFIS structure is significant minimization of deviation signals (17%-79%) compared to other controllers. It is recommended to exploit it when dealing with a highly nonlinear system which operates in the presence of undesirable disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Adaptive solution of partial differential equations in multiwavelet bases

    International Nuclear Information System (INIS)

    Alpert, B.; Beylkin, G.; Gines, D.; Vozovoi, L.

    2002-01-01

    We construct multiresolution representations of derivative and exponential operators with linear boundary conditions in multiwavelet bases and use them to develop a simple, adaptive scheme for the solution of nonlinear, time-dependent partial differential equations. The emphasis on hierarchical representations of functions on intervals helps to address issues of both high-order approximation and efficient application of integral operators, and the lack of regularity of multiwavelets does not preclude their use in representing differential operators. Comparisons with finite difference, finite element, and spectral element methods are presented, as are numerical examples with the heat equation and Burgers' equation

  13. Scalable video on demand adaptive Internet-based distribution

    CERN Document Server

    Zink, Michael

    2013-01-01

    In recent years, the proliferation of available video content and the popularity of the Internet have encouraged service providers to develop new ways of distributing content to clients. Increasing video scaling ratios and advanced digital signal processing techniques have led to Internet Video-on-Demand applications, but these currently lack efficiency and quality. Scalable Video on Demand: Adaptive Internet-based Distribution examines how current video compression and streaming can be used to deliver high-quality applications over the Internet. In addition to analysing the problems

  14. Ranking of XML Files by Compiler Based Adaptive Search

    OpenAIRE

    Varun Varma Sangaraju; Mary Posonia

    2014-01-01

    The Ranking of XML files can be performed by using Adaptive keyword search and Reverse indexing of the XML data within which critical metrics are weighed and assigned to the XML data. Compiler for correcting search words will act as an added benefit. This proposed system can act as an upgrade to the existing XML keyword searching pattern. The search results obtained in LCA based systems are non-adjustable and some important features like compactness and size are missed. So this proposed syste...

  15. Optimal model-based sensorless adaptive optics for epifluorescence microscopy.

    Science.gov (United States)

    Pozzi, Paolo; Soloviev, Oleg; Wilding, Dean; Vdovin, Gleb; Verhaegen, Michel

    2018-01-01

    We report on a universal sample-independent sensorless adaptive optics method, based on modal optimization of the second moment of the fluorescence emission from a point-like excitation. Our method employs a sample-independent precalibration, performed only once for the particular system, to establish the direct relation between the image quality and the aberration. The method is potentially applicable to any form of microscopy with epifluorescence detection, including the practically important case of incoherent fluorescence emission from a three dimensional object, through minor hardware modifications. We have applied the technique successfully to a widefield epifluorescence microscope and to a multiaperture confocal microscope.

  16. A Novel Performance Framework and Methodology to Analyze the Impact of 4D Trajectory Based Operations in the Future Air Traffic Management System

    Directory of Open Access Journals (Sweden)

    Sergio Ruiz

    2018-01-01

    Full Text Available The introduction of new Air Traffic Management (ATM concepts such as Trajectory Based Operations (TBO may produce a significant impact in all performance areas, that is, safety, capacity, flight efficiency, and others. The performance framework in use today has been tailored to the operational needs of the current ATM system and must evolve to fulfill the new needs and challenges brought by the TBO content. This paper presents a novel performance assessment framework and methodology adapted to the TBO concept. This framework can assess the key performance areas (KPAs of safety, capacity, and flight efficiency; equity and fairness are also considered in this research, in line with recent ATM trends. A case study is presented to show the applicability of the framework and to illustrate how some of the complex interdependencies among KPAs can be captured with the proposed approach. This case study explores the TBO concept of “strategic 4D trajectory deconfliction,” where the early separation tasks of 4D trajectories at multisector level are assessed. The framework presented in this paper could potentially support the target-setting and performance requirements identification that should be fulfilled in the future ATM system to ensure determined levels of performance.

  17. Effect of Stone Cast Type on Complete Denture Base Adaptation

    Directory of Open Access Journals (Sweden)

    Salman Hamdan

    2016-06-01

    Full Text Available Introduction: Few researches have been conducted researches on the influence of the type of dental stone used for fabrication of casts on the adaptation of denture bases. The purpose of this study was to compare the effect of two types of stone casts on the accuracy of fit in complete denture bases. Methods: Using sixty fully replicated master casts obtained by duplicating a metal die representing an edentulous maxillary arch, 30 casts were poured in type III dental stone and 30 made from type V dental stone. All dentures were completely waxed using a same thickness of base plate wax and teeth were made for the purpose of accuracy. Following polymerization in the same working conditions, dentures were trimmed. After silicone injection between each denture and metal die was performed, weighing the elastomeric silicone layer was performed to study adaptation of dentures. Metal die was used both before copying the casts and   after storing them in water for two months. Results: The values ​​for silicone layer weight (in grams in the group with dental stone type III were greater than the values in type V  regardless of the studied period (both after polymerization and after water immersion for a period of two months in the sample (p

  18. An adaptive ES with a ranking based constraint handling strategy

    Directory of Open Access Journals (Sweden)

    Kusakci Ali Osman

    2014-01-01

    Full Text Available To solve a constrained optimization problem, equality constraints can be used to eliminate a problem variable. If it is not feasible, the relations imposed implicitly by the constraints can still be exploited. Most conventional constraint handling methods in Evolutionary Algorithms (EAs do not consider the correlations between problem variables imposed by the constraints. This paper relies on the idea that a proper search operator, which captures mentioned implicit correlations, can improve performance of evolutionary constrained optimization algorithms. To realize this, an Evolution Strategy (ES along with a simplified Covariance Matrix Adaptation (CMA based mutation operator is used with a ranking based constraint-handling method. The proposed algorithm is tested on 13 benchmark problems as well as on a real life design problem. The outperformance of the algorithm is significant when compared with conventional ES-based methods.

  19. Enhancing Student Adaption to a Case Based Learning Environment

    DEFF Research Database (Denmark)

    Jensen, Lars Peter

    2010-01-01

    INTRODUCTION Since Aalborg University (AAU) was started it has been using an educational model, where Problem Based Learning is the turning point. Each semester the students on the Engineering Educations form groups of 3-6 persons, which uses half of the study time within the semester to solve...... and document a real-world engineering problem. Four years ago a new engineer education: “Medicine with an industrial specialization” started, and for the Medicine part of the education (Bachelor level) it was decided to use a case based PBL model in combination with project work (app. 1/3 of each semester...... and a good adaption to it. Based on a deeper investigation of the results presented in chapter 4 it will be concluded if the experiment was a success or not and give recommendations to further development. REFERENCES [1]Hull York Medical School curriculum: http://www.hyms.ac.uk/undergraduate/HYMS-curriculum.aspx...

  20. Adaptive Landmark-Based Navigation System Using Learning Techniques

    DEFF Research Database (Denmark)

    Zeidan, Bassel; Dasgupta, Sakyasingha; Wörgötter, Florentin

    2014-01-01

    The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal. In...... hexapod robots. As a result, it allows the robots to successfully learn to navigate to distal goals in complex environments.......The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal....... Inspired by this, we develop an adaptive landmark-based navigation system based on sequential reinforcement learning. In addition, correlation-based learning is also integrated into the system to improve learning performance. The proposed system has been applied to simulated simple wheeled and more complex...

  1. Adaptive fiber optics collimator based on flexible hinges.

    Science.gov (United States)

    Zhi, Dong; Ma, Yanxing; Ma, Pengfei; Si, Lei; Wang, Xiaolin; Zhou, Pu

    2014-08-20

    In this manuscript, we present a new design for an adaptive fiber optics collimator (AFOC) based on flexible hinges by using piezoelectric stacks actuators for X-Y displacement. Different from traditional AFOC, the new structure is based on flexible hinges to drive the fiber end cap instead of naked fiber. We fabricated a real AFOC based on flexible hinges, and the end cap's deviation and resonance frequency of the device were measured. Experimental results show that this new AFOC can provide fast control of tip-tilt deviation of the laser beam emitting from the end cap. As a result, the fiber end cap can support much higher power than naked fiber, which makes the new structure ideal for tip-tilt controlling in a high-power fiber laser system.

  2. Adaptive PCA based fault diagnosis scheme in imperial smelting process.

    Science.gov (United States)

    Hu, Zhikun; Chen, Zhiwen; Gui, Weihua; Jiang, Bin

    2014-09-01

    In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  3. A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative

    Science.gov (United States)

    Mei, Haibo; Poslad, Stefan; Du, Shuang

    2017-01-01

    Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers’ mobile patterns, travellers’ modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service. PMID:29232907

  4. Nonlinear relative-proportion-based route adjustment process for day-to-day traffic dynamics: modeling, equilibrium and stability analysis

    Science.gov (United States)

    Zhu, Wenlong; Ma, Shoufeng; Tian, Junfang; Li, Geng

    2016-11-01

    Travelers' route adjustment behaviors in a congested road traffic network are acknowledged as a dynamic game process between them. Existing Proportional-Switch Adjustment Process (PSAP) models have been extensively investigated to characterize travelers' route choice behaviors; PSAP has concise structure and intuitive behavior rule. Unfortunately most of which have some limitations, i.e., the flow over adjustment problem for the discrete PSAP model, the absolute cost differences route adjustment problem, etc. This paper proposes a relative-Proportion-based Route Adjustment Process (rePRAP) maintains the advantages of PSAP and overcomes these limitations. The rePRAP describes the situation that travelers on higher cost route switch to those with lower cost at the rate that is unilaterally depended on the relative cost differences between higher cost route and its alternatives. It is verified to be consistent with the principle of the rational behavior adjustment process. The equivalence among user equilibrium, stationary path flow pattern and stationary link flow pattern is established, which can be applied to judge whether a given network traffic flow has reached UE or not by detecting the stationary or non-stationary state of link flow pattern. The stability theorem is proved by the Lyapunov function approach. A simple example is tested to demonstrate the effectiveness of the rePRAP model.

  5. A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative.

    Science.gov (United States)

    Mei, Haibo; Poslad, Stefan; Du, Shuang

    2017-12-11

    Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers' mobile patterns, travellers' modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service.

  6. Influence of lateral discomfort on the stability of traffic flow based on visual angle car-following model

    Science.gov (United States)

    Zheng, Liang; Zhong, Shiquan; Jin, Peter J.; Ma, Shoufeng

    2012-12-01

    Due to the poor road markings and irregular driving behaviors, not every vehicle is positioned in the center of the lane. The deviation from the center can cause discomfort to drivers in the neighboring lane, which is referred to as lateral discomfort (or lateral friction). Such lateral discomfort can be incorporated into the driver stimulus-response framework by considering the visual angle and its changing rate from the psychological viewpoint. In this study, a two-lane visual angle based car-following model is proposed and its stability condition is obtained through linear stability theory. Further derivations indicate that the neutral stability line of the model is asymmetry and four factors including the vehicle width and length, the lateral separation and the sensitivity regarding the changing rate of visual angle have large impacts on the stability of traffic flow. Numerical simulations further verify these theoretical results, and demonstrate that the behaviors of diverging, merging and lane changing can break the original steady state and cause traffic fluctuations. However, these fluctuations may be alleviated to some extent by reducing the lateral discomfort.

  7. A Vehicular Mobile Standard Instrument for Field Verification of Traffic Speed Meters Based on Dual-Antenna Doppler Radar Sensor.

    Science.gov (United States)

    Du, Lei; Sun, Qiao; Cai, Changqing; Bai, Jie; Fan, Zhe; Zhang, Yue

    2018-04-05

    Traffic speed meters are important legal measuring instruments specially used for traffic speed enforcement and must be tested and verified in the field every year using a vehicular mobile standard speed-measuring instrument to ensure speed-measuring performances. The non-contact optical speed sensor and the GPS speed sensor are the two most common types of standard speed-measuring instruments. The non-contact optical speed sensor requires extremely high installation accuracy, and its speed-measuring error is nonlinear and uncorrectable. The speed-measuring accuracy of the GPS speed sensor is rapidly reduced if the amount of received satellites is insufficient enough, which often occurs in urban high-rise regions, tunnels, and mountainous regions. In this paper, a new standard speed-measuring instrument using a dual-antenna Doppler radar sensor is proposed based on a tradeoff between the installation accuracy requirement and the usage region limitation, which has no specified requirements for its mounting distance and no limitation on usage regions and can automatically compensate for the effect of an inclined installation angle on its speed-measuring accuracy. Theoretical model analysis, simulated speed measurement results, and field experimental results compared with a GPS speed sensor with high accuracy showed that the dual-antenna Doppler radar sensor is effective and reliable as a new standard speed-measuring instrument.

  8. Real time traffic models, decision support for traffic management

    NARCIS (Netherlands)

    Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  9. Real Time Traffic Models, Decision Support for Traffic Management

    NARCIS (Netherlands)

    Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  10. INCITE: Edge-based Traffic Processing and Inference for High-Performance Networks

    Energy Technology Data Exchange (ETDEWEB)

    Baraniuk, Richard G.; Feng, Wu-chun; Cottrell, Les; Knightly, Edward; Nowak, Robert; Riedi, Rolf

    2005-06-20

    The INCITE (InterNet Control and Inference Tools at the Edge) Project developed on-line tools to characterize and map host and network performance as a function of space, time, application, protocol, and service. In addition to their utility for trouble-shooting problems, these tools will enable a new breed of applications and operating systems that are network aware and resource aware. Launching from the foundation provided our recent leading-edge research on network measurement, multifractal signal analysis, multiscale random fields, and quality of service, our effort consisted of three closely integrated research thrusts that directly attack several key networking challenges of DOE's SciDAC program. These are: Thrust 1, Multiscale traffic analysis and modeling techniques; Thrust 2, Inference and control algorithms for network paths, links, and routers, and Thrust 3, Data collection tools.

  11. Poster Abstract: Automatic Calibration of Device Attitude in Inertial Measurement Unit Based Traffic Probe Vehicles

    KAUST Repository

    Mousa, Mustafa

    2016-04-28

    Probe vehicles consist in mobile traffic sensor networks that evolve with the flow of vehicles, transmitting velocity and position measurements along their path, generated using GPSs. To address the urban positioning issues of GPSs, we propose to replace them with inertial measurement units onboard vehicles, to estimate vehicle location and attitude using inertial data only. While promising, this technology requires one to carefully calibrate the orientation of the device inside the vehicle to be able to process the acceleration and rate gyro data. In this article, we propose a scheme that can perform this calibration automatically by leveraging the kinematic constraints of ground vehicles, and that can be implemented on low-end computational platforms. Preliminary testing shows that the proposed scheme enables one to accurately estimate the actual accelerations and rotation rates in the vehicle coordinates. © 2016 IEEE.

  12. Neural network based adaptive output feedback control: Applications and improvements

    Science.gov (United States)

    Kutay, Ali Turker

    Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis. The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems. We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers. A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller. In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment. The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities. Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller. It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented. Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented. The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators. Behavior of such actuators in dynamic flight conditions is not known. To test the adaptive controller design in

  13. Traffic Light Detection at Night

    DEFF Research Database (Denmark)

    Jensen, Morten Bornø; Philipsen, Mark Philip; Bahnsen, Chris

    2015-01-01

    of three detectors based on heuristic models and one learning-based detector. Evaluation is done on night-time data from the public LISA Traffic Light Dataset. The learning-based detector out- performs the model-based detectors in both precision and recall. The learning-based detector achieves an average......Traffic light recognition (TLR) is an integral part of any in- telligent vehicle, it must function both at day and at night. However, the majority of TLR research is focused on day-time scenarios. In this paper we will focus on detection of traffic lights at night and evalu- ate the performance...

  14. Adaptive Micro-Grid Operation Based on IEC 61850

    Directory of Open Access Journals (Sweden)

    Wei Deng

    2015-05-01

    Full Text Available Automatically identifying the new equipment after its integration and adjusting operation strategy to realize “plug and play” functionality are becoming essential for micro-grid operations. In order to improve and perfect the micro-grid “plug and play” function with the increased amount of equipment with different information protocols and more diverse system applications, this paper presents a solution for adaptive micro-grid operation based on IEC 61850, and proposes the design and specific implementation methods of micro-grid “plug and play” function and system operation mode conversion in detail, by using the established IEC 61850 information model of a micro-grid. Actual operation tests based on the developed IED and micro-grid test platform are performed to verify the feasibility and validity of the proposed solution. The tests results show that the solution can automatically identify the IEC 61850 information model of equipment after its integration, intelligently adjust the operation strategies to adapt to new system states and achieves a reliable system operation mode conversion.

  15. Center of Mass-Based Adaptive Fast Block Motion Estimation

    Directory of Open Access Journals (Sweden)

    Yeh Kuo-Liang

    2007-01-01

    Full Text Available This work presents an efficient adaptive algorithm based on center of mass (CEM for fast block motion estimation. Binary transform, subsampling, and horizontal/vertical projection techniques are also proposed. As the conventional CEM calculation is computationally intensive, binary transform and subsampling approaches are proposed to simplify CEM calculation; the binary transform center of mass (BITCEM is then derived. The BITCEM motion types are classified by percentage of (0,0 BITCEM motion vectors. Adaptive search patterns are allocated according to the BITCEM moving direction and the BITCEM motion type. Moreover, the BITCEM motion vector is utilized as the initial search point for near-still or slow BITCEM motion types. To support the variable block sizes, the horizontal/vertical projections of a binary transformed macroblock are utilized to determine whether the block requires segmentation. Experimental results indicate that the proposed algorithm is better than the five conventional algorithms, that is, three-step search (TSS, new three-step search (N3SS, four three-step search (4SS, block-based gradient decent search (BBGDS, and diamond search (DS, in terms of speed or picture quality for eight benchmark sequences.

  16. Cloud-based adaptive exon prediction for DNA analysis.

    Science.gov (United States)

    Putluri, Srinivasareddy; Zia Ur Rahman, Md; Fathima, Shaik Yasmeen

    2018-02-01

    Cloud computing offers significant research and economic benefits to healthcare organisations. Cloud services provide a safe place for storing and managing large amounts of such sensitive data. Under conventional flow of gene information, gene sequence laboratories send out raw and inferred information via Internet to several sequence libraries. DNA sequencing storage costs will be minimised by use of cloud service. In this study, the authors put forward a novel genomic informatics system using Amazon Cloud Services, where genomic sequence information is stored and accessed for processing. True identification of exon regions in a DNA sequence is a key task in bioinformatics, which helps in disease identification and design drugs. Three base periodicity property of exons forms the basis of all exon identification techniques. Adaptive signal processing techniques found to be promising in comparison with several other methods. Several adaptive exon predictors (AEPs) are developed using variable normalised least mean square and its maximum normalised variants to reduce computational complexity. Finally, performance evaluation of various AEPs is done based on measures such as sensitivity, specificity and precision using various standard genomic datasets taken from National Center for Biotechnology Information genomic sequence database.

  17. Adaptation of evidence-based surgical wound care algorithm.

    Science.gov (United States)

    Han, Jung Yeon; Choi-Kwon, Smi

    2011-12-01

    This study was designed to adapt a surgical wound care algorithm that is used to provide evidence-based surgical wound care in a critical care unit. This study used, the 'ADAPTE process', an international clinical practice guideline development method. The 'Bonnie Sue wound care algorithm' was used as a draft for the new algorithm. A content validity index (CVI) targeting 135 critical care nurses was conducted. A 5-point Likert scale was applied to the CVI test using a statistical criterion of .75. A surgical wound care algorithm comprised 9 components: wound assessment, infection control, necrotic tissue management, wound classification by exudates and depths, dressing selection, consideration of systemic factors, wound expected outcome, reevaluate non-healing wounds, and special treatment for non-healing wounds. All of the CVI tests were ≥.75. Compared to existing wound care guidelines, the new wound care algorithm provides precise wound assessment, reliabilities of wound care, expands applicability of wound care to critically ill patients, and provides evidence and strength of recommendations. The new surgical wound care algorithm will contribute to the advancement of evidence-based nursing care, and its use is expected as a nursing intervention in critical care.

  18. Real-time context aware reasoning in on-board intelligent traffic systems: An Architecture for Ontology-based Reasoning using Finite State Machines

    NARCIS (Netherlands)

    Stoter, Arjan; Dalmolen, Simon; Drenth, Eduard; Cornelisse, Erik; Mulder, Wico

    2011-01-01

    In-vehicle information management is vital in intelligent traffic systems. In this paper we motivate an architecture for ontology-based context-aware reasoning for in-vehicle information management. An ontology is essential for system standardization and communication, and ontology-based reasoning

  19. GPS-based ionospheric tomography with a constrained adaptive ...

    Indian Academy of Sciences (India)

    Wen Debao1 Zhang Xiao1 Tong Yangjin1 Zhang Guangsheng2 Zhang Min1 Leng Rusong1. School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410004, China. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, ...

  20. Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model

    Science.gov (United States)

    Zhu, Wen-Xing; Zhang, H. M.

    2018-04-01

    We investigated the mixed traffic flow with human-driving and autonomous cars. A new mathematical model with adjustable sensitivity and smooth factor was proposed to describe the autonomous car's moving behavior in which smooth factor is used to balance the front and back headway in a flow. A lemma and a theorem were proved to support the stability criteria in traffic flow. A series of simulations were carried out to analyze the mixed traffic flow. The fundamental diagrams were obtained from the numerical simulation results. The varying sensitivity and smooth factor of autonomous cars affect traffic flux, which exhibits opposite varying tendency with increasing parameters before and after the critical density. Moreover, the sensitivity of sensors and smooth factors play an important role in stabilizing the mixed traffic flow and suppressing the traffic jam.

  1. Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

    Directory of Open Access Journals (Sweden)

    Yu Li-ping

    2014-01-01

    Full Text Available Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene.

  2. A dual-adaptive support-based stereo matching algorithm

    Science.gov (United States)

    Zhang, Yin; Zhang, Yun

    2017-07-01

    Many stereo matching algorithms use fixed color thresholds and a rigid cross skeleton to segment supports (viz., Cross method), which, however, does not work well for different images. To address this issue, this paper proposes a novel dual adaptive support (viz., DAS)-based stereo matching method, which uses both appearance and shape information of a local region to segment supports automatically, and, then, integrates the DAS-based cost aggregation with the absolute difference plus census transform cost, scanline optimization and disparity refinement to develop a stereo matching system. The performance of the DAS method is also evaluated in the Middlebury benchmark and by comparing with the Cross method. The results show that the average error for the DAS method 25.06% lower than that for the Cross method, indicating that the proposed method is more accurate, with fewer parameters and suitable for parallel computing.

  3. Optimization-based wavefront sensorless adaptive optics for multiphoton microscopy.

    Science.gov (United States)

    Antonello, Jacopo; van Werkhoven, Tim; Verhaegen, Michel; Truong, Hoa H; Keller, Christoph U; Gerritsen, Hans C

    2014-06-01

    Optical aberrations have detrimental effects in multiphoton microscopy. These effects can be curtailed by implementing model-based wavefront sensorless adaptive optics, which only requires the addition of a wavefront shaping device, such as a deformable mirror (DM) to an existing microscope. The aberration correction is achieved by maximizing a suitable image quality metric. We implement a model-based aberration correction algorithm in a second-harmonic microscope. The tip, tilt, and defocus aberrations are removed from the basis functions used for the control of the DM, as these aberrations induce distortions in the acquired images. We compute the parameters of a quadratic polynomial that is used to model the image quality metric directly from experimental input-output measurements. Finally, we apply the aberration correction by maximizing the image quality metric using the least-squares estimate of the unknown aberration.

  4. IMPLEMENTATION AND EVALUATION OF A MOBILE MAPPING SYSTEM BASED ON INTEGRATED RANGE AND INTENSITY IMAGES FOR TRAFFIC SIGNS LOCALIZATION

    Directory of Open Access Journals (Sweden)

    M. Shahbazi

    2012-07-01

    Full Text Available Recent advances in positioning techniques have made it possible to develop Mobile Mapping Systems (MMS for detection and 3D localization of various objects from a moving platform. On the other hand, automatic traffic sign recognition from an equipped mobile platform has recently been a challenging issue for both intelligent transportation and municipal database collection. However, there are several inevitable problems coherent to all the recognition methods completely relying on passive chromatic or grayscale images. This paper presents the implementation and evaluation of an operational MMS. Being distinct from the others, the developed MMS comprises one range camera based on Photonic Mixer Device (PMD technology and one standard 2D digital camera. The system benefits from certain algorithms to detect, recognize and localize the traffic signs by fusing the shape, color and object information from both range and intensity images. As the calibrating stage, a self-calibration method based on integrated bundle adjustment via joint setup with the digital camera is applied in this study for PMD camera calibration. As the result, an improvement of 83 % in RMS of range error and 72 % in RMS of coordinates residuals for PMD camera, over that achieved with basic calibration is realized in independent accuracy assessments. Furthermore, conventional photogrammetric techniques based on controlled network adjustment are utilized for platform calibration. Likewise, the well-known Extended Kalman Filtering (EKF is applied to integrate the navigation sensors, namely GPS and INS. The overall acquisition system along with the proposed techniques leads to 90 % true positive recognition and the average of 12 centimetres 3D positioning accuracy.

  5. IMPLEMENTATION AND EVALUATION OF A MOBILE MAPPING SYSTEM BASED ON INTEGRATED RANGE AND INTENSITY IMAGES FOR TRAFFIC SIGNS LOCALIZATION

    Directory of Open Access Journals (Sweden)

    M. Shahbazi

    2012-07-01

    Full Text Available Recent advances in positioning techniques have made it possible to develop Mobile Mapping Systems (MMS for detection and 3D localization of various objects from a moving platform. On the other hand, automatic traffic sign recognition from an equipped mobile platform has recently been a challenging issue for both intelligent transportation and municipal database collection. However, there are several inevitable problems coherent to all the recognition methods completely relying on passive chromatic or grayscale images. This paper presents the implementation and evaluation of an operational MMS. Being distinct from the others, the developed MMS comprises one range camera based on Photonic Mixer Device (PMD technology and one standard 2D digital camera. The system benefits from certain algorithms to detect, recognize and localize the traffic signs by fusing the shape, color and object information from both range and intensity images. As the calibrating stage, a self-calibration method based on integrated bundle adjustment via joint setup with the digital camera is applied in this study for PMD camera calibration. As the result, an improvement of 83% in RMS of range error and 72% in RMS of coordinates residuals for PMD camera, over that achieved with basic calibration is realized in independent accuracy assessments. Furthermore, conventional photogrammetric techniques based on controlled network adjustment are utilized for platform calibration. Likewise, the well-known Extended Kalman Filtering (EKF is applied to integrate the navigation sensors, namely GPS and INS. The overall acquisition system along with the proposed techniques leads to 90% true positive recognition and the average of 12 centimetres 3D positioning accuracy.

  6. Evaluation of countermeasures for red light running by traffic simulator-based surrogate safety measures.

    Science.gov (United States)

    Lee, Changju; So, Jaehyun Jason; Ma, Jiaqi

    2018-01-02

    The conflicts among motorists entering a signalized intersection with the red light indication have become a national safety issue. Because of its sensitivity, efforts have been made to investigate the possible causes and effectiveness of countermeasures using comparison sites and/or before-and-after studies. Nevertheless, these approaches are ineffective when comparison sites cannot be found, or crash data sets are not readily available or not reliable for statistical analysis. Considering the random nature of red light running (RLR) crashes, an inventive approach regardless of data availability is necessary to evaluate the effectiveness of each countermeasure face to face. The aims of this research are to (1) review erstwhile literature related to red light running and traffic safety models; (2) propose a practical methodology for evaluation of RLR countermeasures with a microscopic traffic simulation model and surrogate safety assessment model (SSAM); (3) apply the proposed methodology to actual signalized intersection in Virginia, with the most prevalent scenarios-increasing the yellow signal interval duration, installing an advance warning sign, and an RLR camera; and (4) analyze the relative effectiveness by RLR frequency and the number of conflicts (rear-end and crossing). All scenarios show a reduction in RLR frequency (-7.8, -45.5, and -52.4%, respectively), but only increasing the yellow signal interval duration results in a reduced total number of conflicts (-11.3%; a surrogate safety measure of possible RLR-related crashes). An RLR camera makes the greatest reduction (-60.9%) in crossing conflicts (a surrogate safety measure of possible angle crashes), whereas increasing the yellow signal interval duration results in only a 12.8% reduction of rear-end conflicts (a surrogate safety measure of possible rear-end crash). Although increasing the yellow signal interval duration is advantageous because this reduces the total conflicts (a possibility of total

  7. Traffic Infrastructure in the Development of the Croatian Traffic System

    Directory of Open Access Journals (Sweden)

    Damir Šimulčik

    2012-10-01

    Full Text Available The absence of a long-term traffic policy and of the policyof financing the constntction and maintenance of traffic infrastructurefacilities, represents a synthesis of numerous unresolvedrelations whose negative effects are felt in the overalleconomic and traffic development and consequently theevaluation of national potentials in the field. Adverse aspectcaused by the lack of a clear and feasible policy of financing thetraffic infrastructure facilities, is also a result of not having definedan adequate traffic policy, programme and strategiccourses of development, nor financing models that would be inaccordance with the market and economy system.This indicates that it is necessary to determine a policy forfinancing the constntction and maintenance of traffic infrastntcture,which has to be based on scientific development,team work, availability of plans and programmes to scientistsand experts, determined methodology based on marketing andeconomic logic in defining the programme and strategic tasksand assignments so as to make them feasible.In the near future, intensive preparations for investments inthe overall traffic sysiem are necessary, especially regarding thetraffic infrastntcture facilities - the pivotal points in the processof evaluating the traffic in our national tenitory. Croatia needsto define clearly its strategy in constructing and maintaining thegeneral traffic infrastructure, appointing at the same time thosewho will carry out the given tasks.

  8. Integrated coding-aware intra-ONU scheduling for passive optical networks with inter-ONU traffic

    Science.gov (United States)

    Li, Yan; Dai, Shifang; Wu, Weiwei

    2016-12-01

    Recently, with the soaring of traffic among optical network units (ONUs), network coding (NC) is becoming an appealing technique for improving the performance of passive optical networks (PONs) with such inter-ONU traffic. However, in the existed NC-based PONs, NC can only be implemented by buffering inter-ONU traffic at the optical line terminal (OLT) to wait for the establishment of coding condition, such passive uncertain waiting severely limits the effect of NC technique. In this paper, we will study integrated coding-aware intra-ONU scheduling in which the scheduling of inter-ONU traffic within each ONU will be undertaken by the OLT to actively facilitate the forming of coding inter-ONU traffic based on the global inter-ONU traffic distribution, and then the performance of PONs with inter-ONU traffic can be significantly improved. We firstly design two report message patterns and an inter-ONU traffic transmission framework as the basis for the integrated coding-aware intra-ONU scheduling. Three specific scheduling strategies are then proposed for adapting diverse global inter-ONU traffic distributions. The effectiveness of the work is finally evaluated by both theoretical analysis and simulations.

  9. Ultrasonic Sensors in Urban Traffic Driving-Aid Systems

    Directory of Open Access Journals (Sweden)

    Teresa de Pedro

    2011-01-01

    Full Text Available Currently, vehicles are often equipped with active safety systems to reduce the risk of accidents, most of which occur in urban environments. The most prominent include Antilock Braking Systems (ABS, Traction Control and Stability Control. All these systems use different kinds of sensors to constantly monitor the conditions of the vehicle, and act in an emergency. In this paper the use of ultrasonic sensors in active safety systems for urban traffic is proposed, and the advantages and disadvantages when compared to other sensors are discussed. Adaptive Cruise Control (ACC for urban traffic based on ultrasounds is presented as an application example. The proposed system has been implemented in a fully-automated prototype vehicle and has been tested under real traffic conditions. The results confirm the good performance of ultrasonic sensors in these systems.

  10. Solutions to Traffic Jam on East Road of Beijing Jiaotong University in Rush Hours Based on Analogue Simulation

    Directory of Open Access Journals (Sweden)

    Zou Yanwen

    2015-01-01

    Full Text Available Based on the simulation theory and method, this paper establishes a status analogue simulation model in peak hours, realizes an effective assessment on the road, finds out bottlenecks to improve the level of road services and puts forward the corresponding road improvement program. This paper simulates the improvement program by the use of VISSIM simulation model, and verifies the improvement effect of four programs and carries out promotion. The research obtains an effective method of solving the problem of jam on the sub-arterial road: It needs to set up by-pass and control over traffic flow of the by-pass, and give full play to the role of by-pass in city.

  11. Knowledge-based control of an adaptive interface

    Science.gov (United States)

    Lachman, Roy

    1989-01-01

    The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

  12. Intelligent Traffic Quantification System

    Science.gov (United States)

    Mohanty, Anita; Bhanja, Urmila; Mahapatra, Sudipta

    2017-08-01

    Currently, city traffic monitoring and controlling is a big issue in almost all cities worldwide. Vehicular ad-hoc Network (VANET) technique is an efficient tool to minimize this problem. Usually, different types of on board sensors are installed in vehicles to generate messages characterized by different vehicle parameters. In this work, an intelligent system based on fuzzy clustering technique is developed to reduce the number of individual messages by extracting important features from the messages of a vehicle. Therefore, the proposed fuzzy clustering technique reduces the traffic load of the network. The technique also reduces congestion and quantifies congestion.

  13. Adaptive density trajectory cluster based on time and space distance

    Science.gov (United States)

    Liu, Fagui; Zhang, Zhijie

    2017-10-01

    There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

  14. Space-based RF signal classification using adaptive wavelet features

    Energy Technology Data Exchange (ETDEWEB)

    Caffrey, M.; Briles, S.

    1995-04-01

    RF signals are dispersed in frequency as they propagate through the ionosphere. For wide-band signals, this results in nonlinearly- chirped-frequency, transient signals in the VHF portion of the spectrum. This ionospheric dispersion provide a means of discriminating wide-band transients from other signals (e.g., continuous-wave carriers, burst communications, chirped-radar signals, etc.). The transient nature of these dispersed signals makes them candidates for wavelet feature selection. Rather than choosing a wavelet ad hoc, we adaptively compute an optimal mother wavelet via a neural network. Gaussian weighted, linear frequency modulate (GLFM) wavelets are linearly combined by the network to generate our application specific mother wavelet, which is optimized for its capacity to select features that discriminate between the dispersed signals and clutter (e.g., multiple continuous-wave carriers), not for its ability to represent the dispersed signal. The resulting mother wavelet is then used to extract features for a neutral network classifier. The performance of the adaptive wavelet classifier is the compared to an FFT based neural network classifier.

  15. Adaptive Timer-Based Countermeasures against TCP SYN Flood Attacks

    Science.gov (United States)

    Tanabe, Masao; Akaike, Hirofumi; Aida, Masaki; Murata, Masayuki; Imase, Makoto

    As a result of the rapid development of the Internet in recent years, network security has become an urgent issue. Distributed denial of service (DDoS) attacks are one of the most serious security issues. In particular, 60 percent of the DDoS attacks found on the Internet are TCP attacks, including SYN flood attacks. In this paper, we propose adaptive timer-based countermeasures against SYN flood attacks. Our proposal utilizes the concept of soft-state protocols that are widely used for resource management on the Internet. In order to avoid deadlock, a server releases resources using a time-out mechanism without any explicit requests from its clients. If we change the value of the timer in accordance with the network conditions, we can add more flexibility to the soft-state protocols. The timer is used to manage the resources assigned to half-open connections in a TCP 3-way handshake mechanism, and its value is determined adaptively according to the network conditions. In addition, we report our simulation results to show the effectiveness of our approach.

  16. MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

    Science.gov (United States)

    Tuta, Jure; Juric, Matjaz B

    2018-03-24

    This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

  17. Active materials for adaptive architectural envelopes based on plant adaptation principles

    Directory of Open Access Journals (Sweden)

    Marlen Lopez

    2015-06-01

    Full Text Available In this paper, the authors present research into adaptive architectural envelopes that adapt to environmental changes using active materials, as a result of application of biomimetic principles from plants to architecture. Buildings use large amounts of energy in order to maintain their internal comfort, because conventional buildings are designed to provide a static design solution. Most of the current solutions for facades are not designed for optimum adaptation to contextual issues and needs, while biological solutions to adaptation are often complex, multi-functional and highly responsive. We focus on plant adaptations to the environment, as, due to their immobility, they have developed special means of protection against weather changing conditions. Furthermore, recent developments in new technologies are allowing the possibility to transfer these plant adaptation strategies to technical implementation. These technologies include: multi-material 3D printing, advances in materials science and new capabilities in simulation software. Unlike traditional mechanical activation used for dynamic systems in kinetic facades, adaptive architectural envelopes require no complex electronics, sensors, or actuators. The paper proposes a research of the relationship that can be developed between active materials and environmental issues in order to propose innovative and low-tech design strategies to achieve living envelopes according to plant adaptation principles.  

  18. Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

    Science.gov (United States)

    Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

    2014-01-01

    Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

  19. Network-Wide Traffic Anomaly Detection and Localization Based on Robust Multivariate Probabilistic Calibration Model

    Directory of Open Access Journals (Sweden)

    Yuchong Li

    2015-01-01

    Full Text Available Network anomaly detection and localization are of great significance to network security. Compared with the traditional methods of host computer, single link and single path, the network-wide anomaly detection approaches have distinctive advantages with respect to detection precision and range. However, when facing the actual problems of noise interference or data loss, the network-wide anomaly detection approaches also suffer significant performance reduction or may even become unavailable. Besides, researches on anomaly localization are rare. In order to solve the mentioned problems, this paper presents a robust multivariate probabilistic calibration model for network-wide anomaly detection and localization. It applies the latent variable probability theory with multivariate t-distribution to establish the normal traffic model. Not only does the algorithm implement network anomaly detection by judging whether the sample’s Mahalanobis distance exceeds the threshold, but also it locates anomalies by contribution analysis. Both theoretical analysis and experimental results demonstrate its robustness and wider use. The algorithm is applicable when dealing with both data integrity and loss. It also has a stronger resistance over noise interference and lower sensitivity to the change of parameters, all of which indicate its performance stability.

  20. Adaptive Queue Management with Restraint on Non-Responsive Flows

    Directory of Open Access Journals (Sweden)

    Lan Li

    2003-12-01

    Full Text Available This paper proposes an adaptive queue management scheme (adaptive RED to improve Random Early Detection (RED on restraining non-responsive flows. Due to a lack of flow control mechanism, non-responsive flows can starve responsive flows for buffer and bandwidth at the gateway. In order to solve the disproportionate resource problem, RED framework is modified in this way: on detecting when the non-responsive flows starve the queue, packet-drop intensity (Max_p in RED can be adaptively adjusted to curb non-responsive flows for resource fair-sharing, such as buffer and bandwidth fair-sharing. Based on detection of traffic behaviors, intentionally restraining nonresponsive flows is to increase the throughput and decrease the drop rate of responsive flows. Our experimental results based on adaptive RED shows that the enhancement of responsive traffic and the better sharing of buffer and bandwidth can be achieved under a variety of traffic scenarios.

  1. Probabilistic description of traffic flow

    International Nuclear Information System (INIS)

    Mahnke, R.; Kaupuzs, J.; Lubashevsky, I.

    2005-01-01

    A stochastic description of traffic flow, called probabilistic traffic flow theory, is developed. The general master equation is applied to relatively simple models to describe the formation and dissolution of traffic congestions. Our approach is mainly based on spatially homogeneous systems like periodically closed circular rings without on- and off-ramps. We consider a stochastic one-step process of growth or shrinkage of a car cluster (jam). As generalization we discuss the coexistence of several car clusters of different sizes. The basic problem is to find a physically motivated ansatz for the transition rates of the attachment and detachment of individual cars to a car cluster consistent with the empirical observations in real traffic. The emphasis is put on the analogy with first-order phase transitions and nucleation phenomena in physical systems like supersaturated vapour. The results are summarized in the flux-density relation, the so-called fundamental diagram of traffic flow, and compared with empirical data. Different regimes of traffic flow are discussed: free flow, congested mode as stop-and-go regime, and heavy viscous traffic. The traffic breakdown is studied based on the master equation as well as the Fokker-Planck approximation to calculate mean first passage times or escape rates. Generalizations are developed to allow for on-ramp effects. The calculated flux-density relation and characteristic breakdown times coincide with empirical data measured on highways. Finally, a brief summary of the stochastic cellular automata approach is given

  2. An Adaptive UKF Based SLAM Method for Unmanned Underwater Vehicle

    Directory of Open Access Journals (Sweden)

    Hongjian Wang

    2013-01-01

    Full Text Available This work proposes an improved unscented Kalman filter (UKF-based simultaneous localization and mapping (SLAM algorithm based on an adaptive unscented Kalman filter (AUKF with a noise statistic estimator. The algorithm solves the issue that conventional UKF-SLAM algorithms have declining accuracy, with divergence occurring when the prior noise statistic is unknown and time-varying. The new SLAM algorithm performs an online estimation of the statistical parameters of unknown system noise by introducing a modified Sage-Husa noise statistic estimator. The algorithm also judges whether the filter is divergent and restrains potential filtering divergence using a covariance matching method. This approach reduces state estimation error, effectively improving navigation accuracy of the SLAM system. A line feature extraction is implemented through a Hough transform based on the ranging sonar model. Test results based on unmanned underwater vehicle (UUV sea trial data indicate that the proposed AUKF-SLAM algorithm is valid and feasible and provides better accuracy than the standard UKF-SLAM system.

  3. Capacitance Online Estimation Based on Adaptive Model Observer

    Directory of Open Access Journals (Sweden)

    Cen Zhaohui

    2016-01-01

    Full Text Available As a basic component in electrical and electronic devices, capacitors are very popular in electrical circuits. Conventional capacitors such as electrotype capacitors are easy to degradation, aging and fatigue due to long‐time running and outer damages such as mechanical and electrical stresses. In this paper, a novel online capacitance measurement/estimation approach is proposed. Firstly, an Adaptive Model Observer (AMO is designed based on the capacitor's circuit equations. Secondly, the AMO’s stability and convergence are analysed and discussed. Finally, Capacitors with different capacitance and different initial voltages in a buck converter topology are tested and validated. Simulation results demonstrate the effectiveness and superiority of our proposed approach.

  4. Adaptive learning compressive tracking based on Markov location prediction

    Science.gov (United States)

    Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

    2017-03-01

    Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

  5. Adaptive Neuro-Fuzzy Inference System based DVR Controller Design

    Directory of Open Access Journals (Sweden)

    Brahim FERDI

    2011-06-01

    Full Text Available PI controller is very common in the control of DVRs. However, one disadvantage of this conventional controller is its inability to still working well under a wider range of operating conditions. So, as a solution fuzzy controller is proposed in literature. But, the main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy Inference System (ANFIS based controller design is proposed. The resulted controller is composed of Sugeno fuzzy controller with two inputs and one output. According to the error and error rate of the control system and the output data, ANFIS generates the appropriate fuzzy controller. The simulation results have proved that the proposed design method gives reliable powerful fuzzy controller with a minimum number of membership functions.

  6. Thermotropic and Thermochromic Polymer Based Materials for Adaptive Solar Control

    Directory of Open Access Journals (Sweden)

    Olaf Mühling

    2010-12-01

    Full Text Available The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from ordinary shadow systems to intrinsic solar energy reflection materials based on phase transition components and a first remark about their realization is reported. Own current results concerning extruded films and high thermally stable casting resins with thermotropic properties make a significant contribution to this field.

  7. Wavefront sensorless adaptive optics temporal focusing-based multiphoton microscopy.

    Science.gov (United States)

    Chang, Chia-Yuan; Cheng, Li-Chung; Su, Hung-Wei; Hu, Yvonne Yuling; Cho, Keng-Chi; Yen, Wei-Chung; Xu, Chris; Dong, Chen Yuan; Chen, Shean-Jen

    2014-06-01

    Temporal profile distortions reduce excitation efficiency and image quality in temporal focusing-based multiphoton microscopy. In order to compensate the distortions, a wavefront sensorless adaptive optics system (AOS) was integrated into the microscope. The feedback control signal of the AOS was acquired from local image intensity maximization via a hill-climbing algorithm. The control signal was then utilized to drive a deformable mirror in such a way as to eliminate the distortions. With the AOS correction, not only is the axial excitation symmetrically refocused, but the axial resolution with full two-photon excited fluorescence (TPEF) intensity is also maintained. Hence, the contrast of the TPEF image of a R6G-doped PMMA thin film is enhanced along with a 3.7-fold increase in intensity. Furthermore, the TPEF image quality of 1μm fluorescent beads sealed in agarose gel at different depths is improved.

  8. An evaluation of speed management measures in Bangladesh based upon alternative accident recording, speed measurements, and DOCTOR traffic conflict observations

    NARCIS (Netherlands)

    Horst, A.R.A. van der; Thierry, M.C.; Vet, J.M.; Fazlur Rahman, A.K.M.

    2017-01-01

    With 21,000 people annually killed in road traffic (estimated figure by World Health Organization), Bangladesh has one of the highest fatality rates in the world. Vulnerable road users (VRUs) account for over 50% of road traffic casualties, and 70% of casualties occur in rural areas. As in many Low

  9. An evaluation of speed management measures in Bangladesh based upon alternative accident recording, speed measurements, and DOCTOR traffic conflict observations

    NARCIS (Netherlands)

    Horst, A.R.A. van der; Thierry, M.C.; Vet, J.M.; Rahman, A.F

    2016-01-01

    With 21,000 people annually killed in road traffic (estimated figure by World Health Organization), Bangladesh has one of the highest fatality rates in the world. Vulnerable road users (VRUs) account for over 50% of road traffic casualties, and 70% of casualties occur in rural areas. As in many Low

  10. Local and regional sources of fine and coarse particulate matter based on traffic and background monitoring

    Science.gov (United States)

    Dimitriou, Konstantinos; Kassomenos, Pavlos

    2014-05-01

    The aim of this study was to identify local and exogenous sources affecting particulate matter (PM) levels in five major cities of Northern Europe namely: London, Paris, Hamburg, Copenhagen and Stockholm. Besides local emissions, PM profile at urban and suburban areas of the European Union (EU) is also influenced by regional PM sources due to atmospheric transport, thus geographical city distribution is of a great importance. At each city, PM10, PM2.5, NO2, SO2, CO and O3 air pollution data from two air pollution monitoring stations of the EU network were used. Different background characteristics of the selected two sampling sites at each city facilitated comparisons, providing a more exact analysis of PM sources. Four source apportionment methods: Pearson correlations among the levels of particulates and gaseous pollutants, characterisation of primal component analysis components, long-range transport analysis and extrapolation of PM size distribution ratios were applied. In general, fine (PM2.5) and coarse (PM10) particles were highly correlated, thus common sources are suggested. Combustion-originated gaseous pollutants (CO, NO2, SO2) were strongly associated to PM10 and PM2.5, primarily at areas severely affected by traffic. On the contrary, at background stations neighbouring important natural sources of particles or situated in suburban areas with rural background, natural emissions of aerosols were indicated. Series of daily PM2.5/PM10 ratios showed that minimum fraction values were detected during warm periods, due to higher volumes of airborne biogenic PM coarse, mainly at stations with important natural sources of particles in their vicinity. Hybrid single-particle Lagrangian integrated trajectory model was used, in order to extract 4-day backward air mass trajectories that arrived in the five cities which are under study during days with recorded PM10 exceedances. At all five cities, a significantly large fraction of those trajectories were classified

  11. Model of pulmonary fluid traffic homeostasis based on respiratory cycle pressure, bidirectional bronchiolo-pulmonar shunting and water evaporation.

    Science.gov (United States)

    Kurbel, Sven; Kurbel, Beatrica; Gulam, Danijela; Spajić, Borislav

    2010-06-01

    The main puzzle of the pulmonary circulation is how the alveolar spaces remain dry over a wide range of pulmonary vascular pressures and blood flows. Although normal hydrostatic pressure in pulmonary capillaries is probably always below 10 mmHg, well bellow plasma colloid pressure of 25 mmHg, most textbooks state that some fluid filtration through capillary walls does occur, while the increased lymph drainage prevents alveolar fluid accumulation. The lack of a measurable pressure drop along pulmonary capillaries makes the classic description of Starling forces unsuitable to the low pressure, low resistance pulmonary circulation. Here presented model of pulmonary fluid traffic describes lungs as a matrix of small vascular units, each consisting of alveoli whose capillaries are anastomotically linked to the bronchiolar capillaries perfused by a single bronchiolar arteriole. It proposes that filtration and absorption in pulmonary and in bronchiolar capillaries happen as alternating periods of low and of increased perfusion pressures. The model is based on three levels of filtration control: short filtration phases due to respiratory cycle of the whole lung are modulated by bidirectional bronchiolo-pulmonar shunting independently in each small vascular unit, while fluid evaporation from alveolar groups further tunes local filtration. These mechanisms are used to describe a self-sustaining regulator that allows optimal fluid traffic in different settings. The proposed concept is used to describe development of pulmonary edema in several clinical entities (exercise in wet or dry climate, left heart failure, people who rapidly move to high altitudes, acute cyanide and carbon monoxide poisoning, large pulmonary embolisms). .

  12. Development of a model performance-based sign sheeting specification based on the evaluation of nighttime traffic signs using legibility and eye-tracker data.

    Science.gov (United States)

    2010-09-01

    This project focused on the evaluation of traffic sign sheeting performance in terms of meeting the nighttime : driver needs. The goal was to develop a nighttime driver needs specification for traffic signs. The : researchers used nighttime sign legi...

  13. Efficient community-based control strategies in adaptive networks

    International Nuclear Information System (INIS)

    Yang Hui; Tang Ming; Zhang Haifeng

    2012-01-01

    Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible–infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible–infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans. (paper)

  14. Development of quantum-based adaptive neuro-fuzzy networks.

    Science.gov (United States)

    Kim, Sung-Suk; Kwak, Keun-Chang

    2010-02-01

    In this study, we are concerned with a method for constructing quantum-based adaptive neuro-fuzzy networks (QANFNs) with a Takagi-Sugeno-Kang (TSK) fuzzy type based on the fuzzy granulation from a given input-output data set. For this purpose, we developed a systematic approach in producing automatic fuzzy rules based on fuzzy subtractive quantum clustering. This clustering technique is not only an extension of ideas inherent to scale-space and support-vector clustering but also represents an effective prototype that exhibits certain characteristics of the target system to be modeled from the fuzzy subtractive method. Furthermore, we developed linear-regression QANFN (LR-QANFN) as an incremental model to deal with localized nonlinearities of the system, so that all modeling discrepancies can be compensated. After adopting the construction of the linear regression as the first global model, we refined it through a series of local fuzzy if-then rules in order to capture the remaining localized characteristics. The experimental results revealed that the proposed QANFN and LR-QANFN yielded a better performance in comparison with radial basis function networks and the linguistic model obtained in previous literature for an automobile mile-per-gallon prediction, Boston Housing data, and a coagulant dosing process in a water purification plant.

  15. Wireless traffic steering for green cellular networks

    CERN Document Server

    Zhang, Shan; Zhou, Sheng; Niu, Zhisheng; Shen, Xuemin (Sherman)

    2016-01-01

    This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consum...

  16. Model for traffic emissions estimation

    Science.gov (United States)

    Alexopoulos, A.; Assimacopoulos, D.; Mitsoulis, E.

    A model is developed for the spatial and temporal evaluation of traffic emissions in metropolitan areas based on sparse measurements. All traffic data available are fully employed and the pollutant emissions are determined with the highest precision possible. The main roads are regarded as line sources of constant traffic parameters in the time interval considered. The method is flexible and allows for the estimation of distributed small traffic sources (non-line/area sources). The emissions from the latter are assumed to be proportional to the local population density as well as to the traffic density leading to local main arteries. The contribution of moving vehicles to air pollution in the Greater Athens Area for the period 1986-1988 is analyzed using the proposed model. Emissions and other related parameters are evaluated. Emissions from area sources were found to have a noticeable share of the overall air pollution.

  17. Flatness-based adaptive fuzzy control of chaotic finance dynamics

    Science.gov (United States)

    Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

    2017-11-01

    A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use neurofuzzy approximators. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the non-measurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.

  18. Adaptive optics in digital micromirror based confocal microscopy

    OpenAIRE

    Pozzi, P.; Wilding, D.; Soloviev, O.A.; Vdovine, Gleb; Verhaegen, M.H.G.; Bifano, Thomas G.; Kubby, Joel; Gigan, Sylvain

    2016-01-01

    This proceeding reports early results in the development of a new technique for adaptive optics in confocal microscopy. The term adaptive optics refers to the branch of optics in which an active element in the optical system is used to correct inhomogeneities in the media through which light propagates. In its most classical form, mostly used in astronomical imaging, adaptive optics is achieved through a closed loop in which the actuators of a deformable mirror are driven by a wavefront senso...

  19. An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction

    Science.gov (United States)

    Zhang, Yan; Tang, Baoping; Liu, Ziran; Chen, Rengxiang

    2016-02-01

    Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements. Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wavelet filter whose parameters (i.e. center frequency and bandwidth) are selected in separate steps. An alternative and efficient method of determining the center frequency is proposed that utilizes the statistical information contained in the production functions (PFs). The bandwidth parameter is optimized using a local ‘greedy’ scheme along with Shannon wavelet entropy criterion. Then, to further reduce the residual in-band noise in the filtered signal, a spectral subtraction procedure is elaborated after wavelet filtering. Instead of resorting to a reference signal as in the majority of papers in the literature, the new method estimates the power spectral density of the in-band noise from the associated PF. The effectiveness of the proposed method is validated using simulated data, test rig data, and vibration data recorded from the transmission system of a helicopter. The experimental results and comparisons with other methods indicate that the proposed method is an effective approach to detecting the fault-related impulses

  20. An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction

    International Nuclear Information System (INIS)

    Zhang, Yan; Tang, Baoping; Chen, Rengxiang; Liu, Ziran

    2016-01-01

    Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements. Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wavelet filter whose parameters (i.e. center frequency and bandwidth) are selected in separate steps. An alternative and efficient method of determining the center frequency is proposed that utilizes the statistical information contained in the production functions (PFs). The bandwidth parameter is optimized using a local ‘greedy’ scheme along with Shannon wavelet entropy criterion. Then, to further reduce the residual in-band noise in the filtered signal, a spectral subtraction procedure is elaborated after wavelet filtering. Instead of resorting to a reference signal as in the majority of papers in the literature, the new method estimates the power spectral density of the in-band noise from the associated PF. The effectiveness of the proposed method is validated using simulated data, test rig data, and vibration data recorded from the transmission system of a helicopter. The experimental results and comparisons with other methods indicate that the proposed method is an effective approach to detecting the fault-related impulses