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Lateral control of autonomous vehicles based on learning driver behavior via cloud model

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The Journal of China Universities of Posts and Telecommunications 2017年第2期24卷 10-17页

作者： Gao Hongbo Xie Guotao Liu Hongzhe Zhang Xinyu Li Deyi State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing Key Laboratory of Information Service Engineering Beijing Union University Information Technology Center Tsinghua University The 61th Institute of Electronic System Engineering

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.

关键词： cloud model driver behavior autonomous vehicles lateral control

Using microscopic video data measures for driver behavior analysis during adverse winter weather:opportunities and challenges

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Journal of Modern Transportation 2015年第2期23卷 81-92页

作者： Ting Fu Sohail Zangenehpour Paul St-Aubin Liping Fu Luis F.Miranda-Moreno Department of Civil Engineering and Applied Mechanics McGill University Department of Civil Geological and Mining Engineeringcole Polytechnique de MontréalC.P.6079succ.Centre-VilleMontrealQC H3C 3A7Canada Department of Civil and Environmental Engineering University of Waterloo School of Transportation and Logistics Southwest Jiaotong University

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.

关键词： Winter Video data collection Issues driver behavior Time to collision Winter roadmaintenance

The verbiage in variable message signs and traffic diversion during crash incidents

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Journal of Intelligent and Connected Vehicles

Journal of Intelligent and Connected Vehicles 2022年第3期5卷 333-344页

作者： Sailesh Acharya Michelle Mekker Department of Civil and Environmental Engineering Utah State UniversityLoganUtahUSA

Purpose–WIth limited research on the effects of variable message sign(VMS)message content and verbiage on revealed driver behavior,this study aims to investigate how different verbiage of crash-related messages are related to the diversion rate.Design/methodology/approach–Using ordered logit models,the associations of message verbiage with diversion rates during crash incidents were assessed using five years of VMS message history within a section of I-15 in the state of Utah.Findings–A significant impact of message verbiage on the diversion rate was observed.Based on the analysis results,the crash message verbiage with the highest diversion was found to be miles to crash 1“prepare to stop,”followed by crash location 1 delay information,miles to crash 1“use caution”1 lane of the crash,etc.In addition,the diversion rate was found to be correlated to some roadway characteristics(e.***.occupancy in mainline,weather condition and light condition)along with the temporal variations.Research limitations/implications–These findings could be used by transportation agencies(e.***.state department of transportation[DOTs])to make informed decisions about choosing the message verbiage during future crash incidents.This study also revealed that higher diversion rates are associated with a shorter distance between the crash location and VMS device location,recommending increasing the number of VMS devices,particularly in crash-prone areas.

关键词： Variable message sign Verbiage message content diversion rate Crash driver behavior Congestion

A Survey of driver behavior Perception Methods for Human-Computer Hybrid Enhancement of Intelligent Driving

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A Survey of Driver Behavior Perception Methods for Human-Com...

Analyzing variations in spatial critical gaps at two-way stop controlled intersections using parametric and non-parametric techniques

2021中国汽车工程学会年会暨展览会

作者： Yi Jiwei Du Aimin Zhu Zhongpan Ding Hongjun School of Automotive Studies Tongji University School of Electronic and Information Engineering Tongji University

The subjective uncertainty of human-in-the-loop is a core issue for hybrid enhancement of human-computer shared driving that is the research hotspot of intelligent vehicle studies.Precise perception of driver behavior is a prerequisite and a significant method to break through the problem of human-in-the-loop uncertainties.Through literature comparison and analysis,we find that the objective evaluation method based on contact and non-contact sensors has received more attention from scholars in comparison with the subjective evaluation of driver behavior.However,there is no literature that addresses the new challenges of driver behavior perception under the condition of human-computer shared driving.Therefore the methods of driver behavior perception for hybrid enhancement of human-computer shared driving are summarized in this paper and the driver behavior perception based on visual and tactile multi-sensor fusion has been pointed out as the future research direction.

关键词： driver behavior human-computer shared driving perception neural network

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Journal of Traffic and Transportation Engineering(English Edition) 2021年第1期8卷 129-138页

作者： Digvijay S.Pawar Gopal R.Patil Department of Civil Engineering Indian Institute of Technology HyderabadKandi 502285India Department of Civil Engineering Indian Institute of Technology BombayPowai 400076India

At two-way stop controlled(TWSC)intersections drivers on minor stream are generally at risk because of the difficulty in judging safe gap between major stream vehicles.Any misjudgment by the driver while choosing gap may result in a collision with major stream vehicle.This paper provides important insights for determining and analyzing spatial critical gaps of drivers at high speed and medium speed TWSC intersections.The critical gap line(CGL)fitted for the accepted and rejected gaps using parametric(binary logit model-BLM)and non-parametric(support vector machines-SVM)techniques gives critical gap values at 15 th,50 th and 85 th percentile speeds.The evaluation of spatial critical gap with respect to major road vehicle(conflicting vehicle)speed makes it easier to understand the impact of variation in speed on spatial gaps accepted by the drivers on the minor road.The logit models developed revealed that the probability of accepting gap decreases with increase in the speed of the conflicting vehicle and it increases with increase in the distance of conflicting vehicle.The spatial critical gaps estimated using support vector machines were found in close approximation with those estimated using binary logit model.The study results showed that SVMs have very good potential to be an alternative tool for the estimation of driver's critical gap.The spatial critical gaps corresponding to 15 th,50 th and 85 th percentile speeds for medium speed intersections were 32 m,38 m and 46 m respectively and for high speed intersections these values were 64 m,76 m and 104 m respectively.The increase in the magnitude of gap value with respect to the percentile speed clearly states the effect of speed on spatial gaps.The insights from the study can be used to suggest various measures to improve the safety of crossing drivers at uncontrolled intersections.

关键词： Traffic engineering Spatial critical gaps Uncontrolled intersections Logit model SVM driver behavior

A methodology for calibration of traffic micro-simulator for urban heterogeneous traffic operations

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Journal of Traffic and Transportation Engineering(English Edition) 2020年第4期7卷 507-519页

作者： Palak Maheshwary Kinjal Bhattacharyya Bhargab Maitra Manfred Boltze ARCADIS Bengaluru 560017India Department of Civil Engineering Indian Institute of Technology KharagpurKharagpur 721302India Department of Civil and Environmental Engineering Technische Universitat DarmstadtDarmstadt 64287Germany

Traffic micro-simulation is a widely accepted tool in many countries for the evaluation and assessment of alternative design schemes.However,for several developing countries,replicating heterogeneous,non-lane based traffic in a micro-simulation framework is gaining increased importance and still remains a challenge due to its complexity.The present study demonstrates a methodology to calibrate a traffic micro-simulation model giving due consideration to vehicle-class specific driver behavior in an urban Indian scenario for a midblock section and an intersection approach in Kolkata.The sensitive parameters affecting the driver behavior were identified for every vehicle type using Latin Hyper cube design,taking vehicle class specific travel time as a performance measure.Linear regression models were developed for each vehicle class considering the sensitive driving behavior parameters.The models highlight that the dependency of measure of effectiveness(MOE)of one vehicle type is not only limited to its own driver behavior but also on parameters of other vehicle classes.A genetic algorithm based optimization was adopted to obtain optimal parameter sets for different vehicle classes.The optimum values were found to vary significantly across all vehicle classes at a 95%confidence level.Single and multi-criteria calibration principles are also implemented to yield much more realistic results and subsequently minimizing weighted error for all vehicle classes.

关键词： Traffic operation Micro-simulation Heterogeneous traffic Vehicle-class driver behavior VISSIM

Evaluation of red-light camera enforcement using traffic violations

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Journal of Traffic and Transportation Engineering(English Edition) 2018年第1期5卷 66-72页

作者： Khaled Shaaban Anurag Pande Department of Civil and Architectural Engineering Qatar University Department of Civil and Environmental Engineering California Polytechnic State University

The State of O.atar started to use red-light cameras in 2007 at key signalized intersections and the rate of installation has subsequently increased. In 2017, 19.2% of signalized intersections are equipped with red-light cameras. In many cases, the cameras are not installed on all approaches to the intersections. The purpose of this study is to compare the red-light running violations on approaches with and without red-light running enforcement cameras at the same intersections. Actual field observations were used in this study. Different vari- ables were investigated, including the day of the week, time of day, traffic volume, the possibility of glare on an approach, and the lengths of the yellow and all-red times. A regression tree model was used to explain the characteristics associated with the violations. The results showed that the number of violations on low-volume approaches was five times higher than on high-volume approaches. The results also showed that the presence of the cameras significantly lowered red-light running violations. High-volume approaches without cameras had an approximately eight times higher rate of violations than high-vol- ume approaches with cameras. The analysis also showed that bringing the all-red interval closer to the values recommended by the Institute of Transportation Engineers formula may bring down the rates of violations for low-volume approaches. As with any observational data mining method, the study could benefit from a larger sample size. The method used in the study was effective and is easily transferable to other locations. The results of this study can be used in developing new strategies to improve safety at signalized intersections.

关键词： driver behavior Traffic signal Police enforcement Risky driving Automated enforcement Road policing

driver State Detection Based on Cardiovascular System and driver Reaction Information Using a Graphical Model

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Journal of Transportation Technologies 2021年第2期11卷 139-156页

作者： Thanh Tung Nguyen Hirofumi Aoki Anh Son Le Hirano Akio Kunimoto Aoki Makoto Inagami Tatsuya Suzuki Graduate School of Engineering Nagoya University Nagoya Japan Institute of Innovation for Future Society Nagoya University Nagoya Japan

Traffic accidents are mainly caused by human error. In an aging society, the number of accidents attributed to elderly drivers is increasing. One noteworthy reason for this is operation misapplication. Studies have been conducted on the use of human-machine interfaces (HMIs) to inform the driver when he or she makes an error and encourage appropriate actions. However, the driver state during the erroneous action has not been investigated. The purpose of this study is to clarify the difference in the driver’s state between normal and surprising situations in a misapplication scenario, utilizing multimodal information such as biometric information and driver operation. We found significant changes in the interaction of components between the normal and the surprised driving state. The results could provide basic knowledge for the future development of a driver assistance system and driver state estimation using data acquired from multiple sensors in the vehicle.

关键词： Human Engineering driver behavior Bio-Signal Safety

Yellow light dilemma zone researches: a review

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Journal of Traffic and Transportation Engineering(English Edition) 2014年第5期1卷 338-352页

作者： Yaping Zhang Chuanyun Fu Liwei Hu School of Transportation Science and Engineering Harbin Institute of Technology Faculty of Transportation Engineering Kunming University of Science and Technology

The yellow light dilemma zone is widely known as an area on the high-speed intersection ap- proach, where vehicles neither safely stop before the stop line nor proceed through the intersection dur- ing amber interval. Within such an area, a vehicle might be involved in a right-angle crash or rear-end collision. This issue has been extensively discussed over five decades in traffic engineering field, cov- eting from theory to practice. However, few comprehensive review literatures on the amber signal di- lemma zone problems can be found. The objective of this paper is to summarize the evolution of yellow light dilemma zone researches. Basic definition and boundary of dilemma zone followed by driver be- havior and dilemma zone hazard measurement are depicted. At last, the future directions of yellow light dilemma zone research are discussed.

关键词： yellow light dilemma zone driver behavior signalized intersection