Safe-D: Safety through Disruption

Behavioral Indicators of Drowsy Driving: Active Search Mirror Checks

Abstract

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.

Project Highlights

  • Coming Soon

Final Report

Coming Soon

EWD & T2 Products

Coming Soon

Presentations/Publications

Coming Soon

Final Dataset

Coming Soon

Research Investigators (PI*)

Jason Meyer (VT/VTTI)*
Eddy Llaneras (VT/VTTI)*

Project Information

Start Date: 2020-01-11
End Date: 2022-05-01
Status: Active
Grant Number: 69A3551747115
Total Funding: $354,000
Source Organization: Safe-D National UTC
Project Number: 05-084

Safe-D Theme Areas

Big Data Analytics

Automated Vehicles

Safe-D Application Areas

Vehicle Technology
Driver Factors and Interfaces
Performance Measures
Planning for Safety

More Information

RiP URL
UTC Project Information Form

Sponsor Organization

Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States

Performing Organization

Virginia Polytechnic Institute and State University
Virginia Tech Transportation Institute
3500 Transportation Research Plaza
Blacksburg, Virginia 24061
USA