Modeling Driver Behavior and Driver Aggressiveness Using Biobehavioral Methods – Phase III
项目名称: Modeling Driver Behavior and Driver Aggressiveness Using Biobehavioral Methods – Phase III
摘要: It is well known that driver inattention and human error are the primary causes of traffic accidents. In addition, existing driver behavioral modeling algorithms (e.g., car-following, lane changing) assume that driver variability is expressed through various distributions and random number generators. What constitutes aggressive driving, and which are the actions of aggressive drivers that negatively affect safety and traffic instability, are some of the topics that have not been studied thoroughly. At the same time, significant work has been done in the field of cognitive science and psychology, with emphasis in understanding, modeling, and predicting drivers’ intended actions. During the first two years of this project (Modeling Driver Behavior and Driver Aggressiveness Using Biobehavioral Methods – PART I and Part II), the research team conducted an extended driving simulator experiment and collected a multitude of measures of driver performance (speeds, accelerations, car-following), cognition (workload, situational awareness, level of activation), psychophysiological measures (brain activation, heart monitoring), and characteristics (demographics, personality, moral). Several scenarios with varying difficulty and presence of distraction were used. The data obtained through this experiment, will be used here to fulfill two major objectives: (1) calibrate a well-known car-following model (Intelligent Driver Model (IDM)) such that it captures driver heterogeneity as well as the impact of driving task on driver performance, and (2) develop a driver assessment tool that evaluates driver capability and performance.
状态: Active
资金: 148878
资助组织: Office of the Assistant Secretary for Research and Technology
项目负责人: Stearns, Amy
执行机构: University of Kansas, Lawrence
开始时间: 20200624
预计完成日期: 20210630
主题领域: Highways;Operations and Traffic Management;Safety and Human Factors
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