This paper presents a driver behavior analysis using microscopic video data measures including vehicle speed, lane-changing ratio, and time to collision. An analytical framework was developed to evaluate the effect of...This paper presents a driver behavior analysis using microscopic video data measures including vehicle speed, lane-changing ratio, and time to collision. An analytical framework was developed to evaluate the effect of adverse winter weather conditions on highway driving behavior based on automated （computer） and manual methods. The research was conducted through two case studies. The first case study was conducted to evaluate the feasibility of applying an au- tomated approach to extracting driver behavior data based on 15 video recordings obtained in the winter 2013 at three dif- ferent locations on the Don Valley Parkway in Toronto, Canada. A comparison was made between the automated approach and manual approach, and issues in collecting data using the automated approach under winter conditions were identified. The second case study was based on high quality data collected in the winter 2014, at a location on Highway 25 in Montreal, Canada. The results demonstrate the effectiveness of the automated analytical framework in analyzing driver behavior, as well as evaluating the impact of adverse winter weather conditions on driver behavior. This approach could be applied to evaluate winter maintenance strategies and crash risk on highways during adverse winter weather conditions.展开更多
In this paper a cellular automaton model is proposed to describe driver behavior at a single-lane urban roundabout. Driver behavior has been considered as heterogeneous and inconsistent. Most traffic papers in the lit...In this paper a cellular automaton model is proposed to describe driver behavior at a single-lane urban roundabout. Driver behavior has been considered as heterogeneous and inconsistent. Most traffic papers in the literature just discussed heterogeneous driver behavior, to our best knowledge. Two truncated Caussian distributions are used to model heterogeneous and inconsistent driver behavior, respectively. The physical meanings of two truncated distributions are indicated. This method may help enhance a better understanding of driver behavior at roundabout traffic, and even possibly provide references for roundabout design and management.展开更多
This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are us...This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are used for the purpose of training and researching driver behavior and characteristics;3) the article addresses driver experience by involving new virtual reality technologies. A simulator has been used to assist novice drivers to learn how to drive in a very safe environment, and researching and collecting data for researchers has become easier due to this secure and user-friendly environment. The theoretical framework of this driving simulation has been designed by using the Unity3D game engine (5.4.f3 version) and was programmed with the C# programming language. To make the driving environment more realistic we, in addition, utilized the HTC Vive Virtual reality headset which is powered by Steamvr. We used Unity Game Engine to design our scenarios and maps because by doing this we are able to be more flexible with designing. In this study, we asked 10 people ranging from ages 19 - 37 to participate in this experiment. Four Japanese divers and six non-Japanese drivers engaged in this study, some of which do not have a driver’s license in Japan. A few Japanese drivers have a license and car, while others have a license but no car. In order to analyze the results of this experiment we are used MatlabR2016b to analyze the gathered data. The result of this research indicates that individual’s behavior and characteristics such as controlling the speed, remaining calm and relaxed when driving, driving at appropriate speeds depending on changes in road structures and etc. can affect their driving performance.展开更多
The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. The present study aims to research driver pattern and classification feature. Driver behavior self-reported inve...The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. The present study aims to research driver pattern and classification feature. Driver behavior self-reported investigation was conducted with standardized driver behavior questionnaire (DBQ) by 225 nonprofessional drivers on the internet in Beijing. Questionnaire’s reliability was verified by statistics analysis. Confirmatory factor analysis (CFA) was used to analyze the underlying factor structure. Speed advantage, space occupation, the contend right of way and the contend space advantage were extracted from the ques-tionnaire results to quantify driver characteristics. Based on fuzzy C-means (FCM) algorithm and taking the four factors as pattern features, the number of driver classification distribution was discussed. Then the number of driver classification was determined by statistical indices. The comparison of classification results with the survey finding on whether the driver occurred in traffic accidents within five years shows that the classification result is the same as the actual driving conditions. Finally, correlation between the demographic and types of driving behavior has been analyzed. Female were more likely than male to careful driving, and the older the driver and the less driving experience, the more careful and moderate driving behavior is.展开更多
Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lan...Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lane departure warning (LDW), blind spot warning (BSW), over speed warning (OSW), forward collision warning (FCW), lane keep assist (LKA), adaptive cruise control (ACC), cooperative ACC (CACC), and automated emergency braking (AEB) are designed to assist with, or in some cases take over, certain driving maneuvers. They can be broadly categorized into advanced driver assistance system (ADAS) and automated features. Each of these advanced features focuses on addressing a particular task of driving, thereby, aiding the driver, influencing their behavior, and enhancing safety. Many vehicles with these advanced features are penetrating into the market, yet the total reported number of crashes has increased in recent years. This paper presents a systematic review of these advanced features on driver behavior and safety. The review is categorized into 1) survey and mathematical methods to assess driver behavior, 2) field test methods to assess driver behavior, 3) microsimulation methods to assess driver behavior, 4) driving simulator methods to assess driver behavior, and 5) driver understanding and the effectiveness of advanced features. It is followed by conclusions, knowledge gaps, and need for further research.展开更多
Amassive market penetration of electric vehicles(EVs)associated with nonnegligible energy consumption and environmental issues has imposed a big challenge on evaluating electrical power distribution and related transp...Amassive market penetration of electric vehicles(EVs)associated with nonnegligible energy consumption and environmental issues has imposed a big challenge on evaluating electrical power distribution and related transportation facilities improvement in response to the largescale EV charging service need.Strategical deployment of EV charging stations including location and determination ofnumber of slowcharging stations and fast charging stationshas become an emerging concern and one of the most pressing needs in planning.This paper conducts a comprehensive survey of EV charging demand and distribution models with consideration of realistic driver behaviors impacts.This is currently a shortage in academic literature,but indeed has drawn practical attention in the strategic planning process.To address the need,this paper presents an in-depth literature review of relevant studies that have identified different types of EV charging facilities,needs or concerns that are considered into EV charging demand and distribution modeling,alongside critical impacting factor identification,mathematical relationshipsof the contributing factorsandEVchargingdemand and distribution modeling.Key findings from the current literature are summarized with strategies for optimized plan of charging station deployments(i.e.,location and related number of charging station),in an attempt to provide a valuable reference for interested readers.展开更多
In order to achieve the lateral control of the intelligent vehicle, use the bi-cognitive model based on cloud model and cloud reasoning, solve the decision problem of the qualitative and quantitative of the lateral co...In order to achieve the lateral control of the intelligent vehicle, use the bi-cognitive model based on cloud model and cloud reasoning, solve the decision problem of the qualitative and quantitative of the lateral control of the intelligent vehicle. Obtaining a number of experiment data by driving a vehicle, classify the data according to the concept of data and fix the input and output variables of the cloud controller, design the control rules of the cloud controller of intelligent vehicle, and clouded and fix the parameter of cloud controller： expectation, entropy and hyper entropy. In order to verify the effectiveness of the cloud controller, joint simulation platform based on Matlab/Simulink/CarSim is established. Experimental analysis shows that： driver＇s lateral controller based on cloud model is able to achieve tracking of the desired angle, and achieve good control effect, it also verifies that a series of mental activities such as feeling, cognition, calculation, decision and so on are fuzzy and uncertain.展开更多
To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm,based on the driver-behavior-based transferable motion primitives(MPs), a general motion-planning framew...To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm,based on the driver-behavior-based transferable motion primitives(MPs), a general motion-planning framework for offline generation and online selection of MPs is proposed. Optimal control theory is applied to solve the boundary value problems in the process of generating MPs, where the driver behaviors and the vehicle motion characteristics are integrated into the optimization in the form of constraints. Moreover, a layered, unequal-weighted MP selection framework is proposed that utilizes a combination of environmental constraints, nonholonomic vehicle constraints,trajectory smoothness, and collision risk as the single-step extension evaluation index. The library of MPs generated offline demonstrates that the proposed generation method realizes the effective expansion of MP types and achieves diverse generation of MPs with various velocity attributes and platform types. We also present how the MP selection algorithm utilizes a unique MP library to achieve online extension of MP sequences. The results show that the proposed motion-planning framework can not only improve the efficiency and rationality of the algorithm based on driving experience but can also transfer between heterogeneous vehicle platforms and highlight the unique motion characteristics of the platform.展开更多
Transportation plays a vital role both in urban economy and usuallives, which is recognized as one of the major functions of a city, along with dwelling, work, and recreation. As an organic system, urban traffic has a...Transportation plays a vital role both in urban economy and usuallives, which is recognized as one of the major functions of a city, along with dwelling, work, and recreation. As an organic system, urban traffic has attracted increased attention during recent years. However, the majority of studies focused on roadways and vehicular technologies, and limited research has been conducted to address the driver characteristics and their impact. A major possible reason is the scarcity of reliable data. In fact, traditional traffic data obtained from cross-sectional detectors as well as video capture devices are not sufficient to fully capture driver behavior. Only in the recent years, with the availability of transportation-related ＂big data＂ and particu- larly the overwhelming information onboard and from road- side facilities, the impacts of driver behavior may be investigated in more detail. In general, driver behavior in microscopic level may include car-following, lane-changing, and gap acceptance models, which are believed largely to affect roadway capacity. Furthermore, safety concerns especially when drivingin an urban environment due to the interaction of different modes, also increase the complexity of quantifying the quality of service of various transportation facilities. These potential complexities in driver behavior challenge academia to develop supporting models and methods of analysis.展开更多
Road traffic accidents are a major cause of casualties and costly implications to all the stakeholders. Research focusing on the driver as one of the causal agent of accidents has been studied for centuries and with t...Road traffic accidents are a major cause of casualties and costly implications to all the stakeholders. Research focusing on the driver as one of the causal agent of accidents has been studied for centuries and with the advent of modernized driver assistance technologies. This paper sought to evaluate response of a driver using active-driving performance indicators like reaction time and physiological signal response (surface electromyogram), to understand hazard response behavior. Simulation of driving scenes was done using Unity3D engine and VR Head mounted display. The driver was presented with stimulus (collision objects) of different size and distance. From the results, an event scene that the driver considered hazardous was marked with increased electromyography response distinct from non-event scenes. From the results, we noted an increase in pedal misapplication during hazard response. The proposed approach is applicable in a real time driving analysis for on-road risk level classification.展开更多
125 automobile drivers, including 85 drivers with accidents (Accident Group, AG) and 40 drivers without accidents (Nonaccident Group, NAG), and 51 controls (Control Group. CG )were tested with WHO Neurobehavioral Core...125 automobile drivers, including 85 drivers with accidents (Accident Group, AG) and 40 drivers without accidents (Nonaccident Group, NAG), and 51 controls (Control Group. CG )were tested with WHO Neurobehavioral Core Test Battery (WHO NCTB). The results showed that there were obvious negative mood states such as tension-anxiety and fatigue in AG and drivers with accidents had more poor neurobehavioral performances, especially attention, response speed and perceptual-motor speed than drivers without accidents and controls. We also found that automobile drivers' neurobehavioral functions got weakened with the increase of their age and got strengthened with the elevation of their educational level. And the functions were inversely correlative to the accidents they cuased. The results of our study suggest that WHO NCTB can be an index of researches on driving accidents that automobile drivers caused and can be used in occupational selection and training of drivers.展开更多
文摘This paper presents a driver behavior analysis using microscopic video data measures including vehicle speed, lane-changing ratio, and time to collision. An analytical framework was developed to evaluate the effect of adverse winter weather conditions on highway driving behavior based on automated （computer） and manual methods. The research was conducted through two case studies. The first case study was conducted to evaluate the feasibility of applying an au- tomated approach to extracting driver behavior data based on 15 video recordings obtained in the winter 2013 at three dif- ferent locations on the Don Valley Parkway in Toronto, Canada. A comparison was made between the automated approach and manual approach, and issues in collecting data using the automated approach under winter conditions were identified. The second case study was based on high quality data collected in the winter 2014, at a location on Highway 25 in Montreal, Canada. The results demonstrate the effectiveness of the automated analytical framework in analyzing driver behavior, as well as evaluating the impact of adverse winter weather conditions on driver behavior. This approach could be applied to evaluate winter maintenance strategies and crash risk on highways during adverse winter weather conditions.
基金Supported by Science and Technology Support Plan of Sichuan Province under Grant No.2012GZX0088Foundation of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection under Grant No.2011Z006Talent Program of Chengdu University of Technology under Grant No.HG0092
文摘In this paper a cellular automaton model is proposed to describe driver behavior at a single-lane urban roundabout. Driver behavior has been considered as heterogeneous and inconsistent. Most traffic papers in the literature just discussed heterogeneous driver behavior, to our best knowledge. Two truncated Caussian distributions are used to model heterogeneous and inconsistent driver behavior, respectively. The physical meanings of two truncated distributions are indicated. This method may help enhance a better understanding of driver behavior at roundabout traffic, and even possibly provide references for roundabout design and management.
文摘This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are used for the purpose of training and researching driver behavior and characteristics;3) the article addresses driver experience by involving new virtual reality technologies. A simulator has been used to assist novice drivers to learn how to drive in a very safe environment, and researching and collecting data for researchers has become easier due to this secure and user-friendly environment. The theoretical framework of this driving simulation has been designed by using the Unity3D game engine (5.4.f3 version) and was programmed with the C# programming language. To make the driving environment more realistic we, in addition, utilized the HTC Vive Virtual reality headset which is powered by Steamvr. We used Unity Game Engine to design our scenarios and maps because by doing this we are able to be more flexible with designing. In this study, we asked 10 people ranging from ages 19 - 37 to participate in this experiment. Four Japanese divers and six non-Japanese drivers engaged in this study, some of which do not have a driver’s license in Japan. A few Japanese drivers have a license and car, while others have a license but no car. In order to analyze the results of this experiment we are used MatlabR2016b to analyze the gathered data. The result of this research indicates that individual’s behavior and characteristics such as controlling the speed, remaining calm and relaxed when driving, driving at appropriate speeds depending on changes in road structures and etc. can affect their driving performance.
文摘The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. The present study aims to research driver pattern and classification feature. Driver behavior self-reported investigation was conducted with standardized driver behavior questionnaire (DBQ) by 225 nonprofessional drivers on the internet in Beijing. Questionnaire’s reliability was verified by statistics analysis. Confirmatory factor analysis (CFA) was used to analyze the underlying factor structure. Speed advantage, space occupation, the contend right of way and the contend space advantage were extracted from the ques-tionnaire results to quantify driver characteristics. Based on fuzzy C-means (FCM) algorithm and taking the four factors as pattern features, the number of driver classification distribution was discussed. Then the number of driver classification was determined by statistical indices. The comparison of classification results with the survey finding on whether the driver occurred in traffic accidents within five years shows that the classification result is the same as the actual driving conditions. Finally, correlation between the demographic and types of driving behavior has been analyzed. Female were more likely than male to careful driving, and the older the driver and the less driving experience, the more careful and moderate driving behavior is.
文摘Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lane departure warning (LDW), blind spot warning (BSW), over speed warning (OSW), forward collision warning (FCW), lane keep assist (LKA), adaptive cruise control (ACC), cooperative ACC (CACC), and automated emergency braking (AEB) are designed to assist with, or in some cases take over, certain driving maneuvers. They can be broadly categorized into advanced driver assistance system (ADAS) and automated features. Each of these advanced features focuses on addressing a particular task of driving, thereby, aiding the driver, influencing their behavior, and enhancing safety. Many vehicles with these advanced features are penetrating into the market, yet the total reported number of crashes has increased in recent years. This paper presents a systematic review of these advanced features on driver behavior and safety. The review is categorized into 1) survey and mathematical methods to assess driver behavior, 2) field test methods to assess driver behavior, 3) microsimulation methods to assess driver behavior, 4) driving simulator methods to assess driver behavior, and 5) driver understanding and the effectiveness of advanced features. It is followed by conclusions, knowledge gaps, and need for further research.
文摘Amassive market penetration of electric vehicles(EVs)associated with nonnegligible energy consumption and environmental issues has imposed a big challenge on evaluating electrical power distribution and related transportation facilities improvement in response to the largescale EV charging service need.Strategical deployment of EV charging stations including location and determination ofnumber of slowcharging stations and fast charging stationshas become an emerging concern and one of the most pressing needs in planning.This paper conducts a comprehensive survey of EV charging demand and distribution models with consideration of realistic driver behaviors impacts.This is currently a shortage in academic literature,but indeed has drawn practical attention in the strategic planning process.To address the need,this paper presents an in-depth literature review of relevant studies that have identified different types of EV charging facilities,needs or concerns that are considered into EV charging demand and distribution modeling,alongside critical impacting factor identification,mathematical relationshipsof the contributing factorsandEVchargingdemand and distribution modeling.Key findings from the current literature are summarized with strategies for optimized plan of charging station deployments(i.e.,location and related number of charging station),in an attempt to provide a valuable reference for interested readers.
基金supported by the National Natural Science Foundation of China (61035004,61273213,61300006,61305055,90920305,61203366,91420202,61571045,61372148)the National Hi-Tech Research and Development Program of China (2015AA015401)+2 种基金the National Basic Research Program of China (2016YFB0100906,2016YFB100903)the Junior Fellowships for Advanced Innovation Think-Tank Program of China Association for Science and Technology (DXB-ZKQN-2017-035)the Beijing Municipal Science and Technology Commission Special Major (D171100005017002)
文摘In order to achieve the lateral control of the intelligent vehicle, use the bi-cognitive model based on cloud model and cloud reasoning, solve the decision problem of the qualitative and quantitative of the lateral control of the intelligent vehicle. Obtaining a number of experiment data by driving a vehicle, classify the data according to the concept of data and fix the input and output variables of the cloud controller, design the control rules of the cloud controller of intelligent vehicle, and clouded and fix the parameter of cloud controller： expectation, entropy and hyper entropy. In order to verify the effectiveness of the cloud controller, joint simulation platform based on Matlab/Simulink/CarSim is established. Experimental analysis shows that： driver＇s lateral controller based on cloud model is able to achieve tracking of the desired angle, and achieve good control effect, it also verifies that a series of mental activities such as feeling, cognition, calculation, decision and so on are fuzzy and uncertain.
基金Supported by National Natural Science Foundation of China (Grant Nos. 91420203 and 61703041)。
文摘To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm,based on the driver-behavior-based transferable motion primitives(MPs), a general motion-planning framework for offline generation and online selection of MPs is proposed. Optimal control theory is applied to solve the boundary value problems in the process of generating MPs, where the driver behaviors and the vehicle motion characteristics are integrated into the optimization in the form of constraints. Moreover, a layered, unequal-weighted MP selection framework is proposed that utilizes a combination of environmental constraints, nonholonomic vehicle constraints,trajectory smoothness, and collision risk as the single-step extension evaluation index. The library of MPs generated offline demonstrates that the proposed generation method realizes the effective expansion of MP types and achieves diverse generation of MPs with various velocity attributes and platform types. We also present how the MP selection algorithm utilizes a unique MP library to achieve online extension of MP sequences. The results show that the proposed motion-planning framework can not only improve the efficiency and rationality of the algorithm based on driving experience but can also transfer between heterogeneous vehicle platforms and highlight the unique motion characteristics of the platform.
文摘Transportation plays a vital role both in urban economy and usuallives, which is recognized as one of the major functions of a city, along with dwelling, work, and recreation. As an organic system, urban traffic has attracted increased attention during recent years. However, the majority of studies focused on roadways and vehicular technologies, and limited research has been conducted to address the driver characteristics and their impact. A major possible reason is the scarcity of reliable data. In fact, traditional traffic data obtained from cross-sectional detectors as well as video capture devices are not sufficient to fully capture driver behavior. Only in the recent years, with the availability of transportation-related ＂big data＂ and particu- larly the overwhelming information onboard and from road- side facilities, the impacts of driver behavior may be investigated in more detail. In general, driver behavior in microscopic level may include car-following, lane-changing, and gap acceptance models, which are believed largely to affect roadway capacity. Furthermore, safety concerns especially when drivingin an urban environment due to the interaction of different modes, also increase the complexity of quantifying the quality of service of various transportation facilities. These potential complexities in driver behavior challenge academia to develop supporting models and methods of analysis.
文摘Road traffic accidents are a major cause of casualties and costly implications to all the stakeholders. Research focusing on the driver as one of the causal agent of accidents has been studied for centuries and with the advent of modernized driver assistance technologies. This paper sought to evaluate response of a driver using active-driving performance indicators like reaction time and physiological signal response (surface electromyogram), to understand hazard response behavior. Simulation of driving scenes was done using Unity3D engine and VR Head mounted display. The driver was presented with stimulus (collision objects) of different size and distance. From the results, an event scene that the driver considered hazardous was marked with increased electromyography response distinct from non-event scenes. From the results, we noted an increase in pedal misapplication during hazard response. The proposed approach is applicable in a real time driving analysis for on-road risk level classification.
文摘125 automobile drivers, including 85 drivers with accidents (Accident Group, AG) and 40 drivers without accidents (Nonaccident Group, NAG), and 51 controls (Control Group. CG )were tested with WHO Neurobehavioral Core Test Battery (WHO NCTB). The results showed that there were obvious negative mood states such as tension-anxiety and fatigue in AG and drivers with accidents had more poor neurobehavioral performances, especially attention, response speed and perceptual-motor speed than drivers without accidents and controls. We also found that automobile drivers' neurobehavioral functions got weakened with the increase of their age and got strengthened with the elevation of their educational level. And the functions were inversely correlative to the accidents they cuased. The results of our study suggest that WHO NCTB can be an index of researches on driving accidents that automobile drivers caused and can be used in occupational selection and training of drivers.
