Behavioral Indicators of Drowsy Driving: Active Search Mirror Checks

Driver impairment, due to drowsiness or fatigue, has a significant impact on the safety of all road users. Assessing an impairment such as driver drowsiness, through the use of vehicle-based technology, continues to be an area of interest. Both the initial detection, as well as continued monitoring, of driver drowsiness have been the emphasis of vehicle-based Driver Monitoring Systems (DMS). Particularly, in-vehicle eye-tracking systems have been implemented, as a way of determining driver state. Specifically, when hands-free driving assistance features are engaged, measures such as the driver’s percentage of eye closure (PERCLOS) are being used to determine driver drowsiness. However, one challenge of such a metric is its reliability; particularly with regard to false alarms (when a DMS indicates the driver is drowsy, but in fact is not). Therefore, the use of more gross-level driver behavioral-based measures may serve as a way of crosschecking the assessments of a DMS. This work aims to mine an available dataset in order to examine driver search behavior, with the goal of identifying relationships between driver vigilance and drowsy driving. The hypothesis is that driver search behavior (e.g. mirror checks) degrades with increasing levels of drowsiness. If a reliable relationship is found between driver vigilance and state of drowsiness, the practical applications may be to incorporate this measure of driver search behavior into the “toolbox” of metrics for estimating driver drowsiness.

Language

  • English

Project

  • Status: Active
  • Funding: $354000
  • 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:

    Meyers, Jason

  • Start Date: 20201001
  • Expected Completion Date: 20220501
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01754158
  • Record Type: Research project
  • Source Agency: Safety through Disruption University Transportation Center
  • Contract Numbers: 69A3551747115
  • Files: UTC, RiP
  • Created Date: Oct 3 2020 1:00PM