Modeling Driver Responses During Automated Vehicle Failures

Automated and connected vehicle technologies, like truck platoons, offer tremendous promise for driving safety, efficiency, and productivity. Some projections even go as far to suggest that these technologies will eliminate all traffic fatalities. However, the benefits of these technologies will only be realized if they are designed for the human beings that interact with them. This interaction is particularly significant in cases where automation fails or hits an operational limit, where drivers may unexpectedly be asked to resume control of the vehicle often with little time to re-engage and react before a crash. One method of alleviating these problematic transitions is to integrate models of human behavior directly into the design process. The models can be used to predict human reactions and differentiate between scenarios where the driver can recover safely, and those where a crash is likely to occur. In this project we develop a model of human behavior during automation failures that may be integrated into current and future design processes for automated vehicles. We will use this model to generate a set of design guidelines for future automated vehicle following technologies that will promote safety and reduce automated driving crashes.

• Record URL:
  https://www.vtti.vt.edu/utc/safe-d/index.php/projects/modeling-driver-responses-during-automated-vehicle-failures/

Language

• English

Project

• Status: Active
• Funding: $353915
• 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:

  McDonald, Tony

• Start Date: 20180101
• Expected Completion Date: 20201231
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Automated vehicle control; Driver monitoring
• Subject Areas: Design; Research; Safety and Human Factors; Transportation (General); Vehicles and Equipment;

Filing Info

• Accession Number: 01658895
• Record Type: Research project
• Source Agency: Safety through Disruption University Transportation Center (Safe-D)
• Contract Numbers: 69A3551747115
• Files: UTC, RIP
• Created Date: Feb 2 2018 5:19PM