Lane Change Hazard Analysis Using Radar Traces to Identify Conflicts and Time-To-Collision Measures

This project will mine an existing set of radar data surrounding real-world lane change events executed by drivers relying on both conventional mirror and camera-based systems. The data set provides valuable opportunities to develop computer-based algorithms for dealing with and managing radar traces to identify normative lane change signatures as well as conflict-based events (inappropriate lane changes, or lane changes executed with small-time gaps). This research is expected to greatly contribute to the development of automated and partially automated driving systems by 1) Developing and validating algorithms using radar trace data to classify “safe” and “unsafe” lane change situations which may be used to guide the implementation and management of automated lane change systems, 2) Helping to develop automated lane change systems that naturally mimic a good driver’s performance thereby increasing driver acceptance and comfort, and 3) Development of warnings to drivers operating with partially automated systems under situations where drivers need to assume control and guarding against inadvisable lane changes. Understanding how drivers manage lane changes under manual driving situations (e.g., time-to-collision judgments, conflicts, etc.) can therefore greatly enhance and aid in the development and implementation of automated lane change and driver warning systems.

Language

  • English

Project

  • Status: Active
  • Funding: $ 364,000
  • Contract Numbers:

    69A3551747115

  • 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:

    Safety through Disruption University Transportation Center

    Virginia Tech Transportation Institute
    Blacksburg, VA  United States  24060
  • Project Managers:

    Glenn, Eric

  • Performing Organizations:

    Virginia Tech Transportation Institute

    3500 Transportation Research Plaza
    Blacksburg, Virginia  United States  24061
  • Principal Investigators:

    McLaughlin, Shane

  • Start Date: 20201101
  • Expected Completion Date: 20220731
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

  • Geographic Terms: risk assesment
  • Subject Areas: Safety and Human Factors;

Filing Info

  • Accession Number: 01754698
  • Record Type: Research project
  • Source Agency: Safety through Disruption University Transportation Center
  • Contract Numbers: 69A3551747115
  • Files: UTC, RiP
  • Created Date: Oct 15 2020 12:20AM