Countermeasures to Detect and Combat Inattention While Driving Partially Automated Systems

This project will investigate and develop countermeasures for problems that can arise when human drivers are required to recognize a fault and assume manual control of a vehicle which is partially-automated. Researchers at Texas A&M University (TAMU) and Texas A&M Transportation Institute will collaborate with those at Virginia Tech Transportation Institute (VTTI) to complete and integrate two research thrusts. The VTTI group will develop and refine a Driver Monitoring System (DMS) for automated vehicles which will estimate the level of attentiveness the driver gives to driving tasks that may require human input and/or taking over from automation control. The TAMU team will first perform an extensive literature review to define a set of failure scenarios in which human action (or inaction) following automation faults could contribute substantially to driving performance and/or safety. These scenarios will be developed in a driving simulator at TAMU, which will be used to conduct a human subjects study to evaluate driving performance with and without various types of multisensory cues (visual, auditory, tactile, and combinations) designed to guide attention to relevant displays and controls. This study will identify the most promising cuing system for guiding attention to these areas of interest, and for easing the transition into manual control for the required task. Finally, researchers at both institutions will combine the products of their research to implement and test the cuing system in a partially-automated vehicle on a controlled test track at VTTI. A short qualitative pilot study will be conducted to validate the usefulness of the cuing system in more realistic driving contexts designed to encourage inattentiveness, and possibly using a Wizard-of-Oz style triggering of cues based on similar logic being developed for the DMS. This effort will also serve as a partial proof-of-concept to springboard future development in this research toward an integrated system that combines DMS attentiveness assessment and cuing to mitigate driver inattentiveness.

• Record URL:
  http://www.vtti.vt.edu/utc/safe-d/index.php/projects/countermeasures-to-detect-and-combat-inattention-while-driving-partially-automated-systems/

Language

• English

Project

• Status: Active
• Funding: $178162
• 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 (Safe-D)

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

  Harwood, Leslie

• Performing Organizations:

  Texas A&M Transportation Institute

  Texas A&M University System
  3135 TAMU
  College Station, TX  United States  77843-3135

  Virginia Tech Transportation Institute

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

  Ferris, Thomas

• Start Date: 20170525
• Expected Completion Date: 20200430
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Attention lapses; Countermeasures; Distraction; Driver monitoring; Human factors engineering; Intelligent vehicles; Traffic safety
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01632140
• Record Type: Research project
• Source Agency: Safety through Disruption University Transportation Center (Safe-D)
• Contract Numbers: 69A3551747115
• Files: UTC, RIP
• Created Date: Apr 4 2017 12:17PM