Modeling Driver Behavior and Driver Aggressiveness Using Biobehavioral Methods – Phase III

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.

    Language

    • English

    Project

    • Status: Completed
    • Funding: $148878
    • Contract Numbers:

      69A3551747107

    • Sponsor Organizations:

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Managing Organizations:

      Mid-America Transportation Center

      University of Nebraska-Lincoln
      2200 Vine Street, PO Box 830851
      Lincoln, NE  United States  68583-0851
    • Project Managers:

      Stearns, Amy

    • Performing Organizations:

      University of Kansas, Lawrence

      Department of Civil Engineering, 2006 Learned Hall
      Lawrence, KS  United States  66045-2225
    • Principal Investigators:

      Kondyli, Alexandra

    • Start Date: 20200624
    • Expected Completion Date: 20210630
    • Actual Completion Date: 20211231
    • USDOT Program: University Transportation Centers Program
    • Source Data: RiP Project 91994-66

    Subject/Index Terms

    Filing Info

    • Accession Number: 01752957
    • Record Type: Research project
    • Source Agency: Mid-America Transportation Center
    • Contract Numbers: 69A3551747107
    • Files: UTC, RIP
    • Created Date: Sep 25 2020 2:09PM