A Machine Vision Approach for Estimating Motion Discomfort in Simulators and in Self-Driving Vehicles

Motion discomfort represents a persistent problem in driving simulators and is expected to be as problematic in highly automated vehicles. This problem can compromise data collection and research validity in simulators, and very likely discourage people from riding in automated vehicles; undermining their potential safety benefits. Monitoring motion sickness can help mitigate its negative effects. However, most of the existing research focuses on physiological research and subjective reporting to quantify motion sickness, which is impractical and does not allow for online monitoring; respectively. Some studies have linked motion sickness to increased yawning. Yet, there is no system to monitor motion sickness in real-time. This project will develop a machine vision algorithm that monitors facial features of drivers and detect any signs of motion discomfort in real-time. The research team will use data collected from 36 drivers who participated in an automated simulator driving study that is expected to induce motion sickness.

Project

  • Status: Inactive
  • Funding: $75000
  • Contract Numbers:

    69A3551747131

  • 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:

    University of Iowa, Iowa City

    National Advanced Driving Simulator, 2401 Oakdale Blvd
    Iowa City, IA  United States  52242-5003
  • Performing Organizations:

    University of Wisconsin-Madison

    1415 Engineering Drive
    Madison, Wisconsin  United States  53706
  • Principal Investigators:

    Lee, John

  • Start Date: 20180501
  • Expected Completion Date: 20190901
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01664245
  • Record Type: Research project
  • Source Agency: Safety Research Using Simulation University Transportation Center (SaferSim)
  • Contract Numbers: 69A3551747131
  • Files: UTC, RiP
  • Created Date: Mar 26 2018 11:24AM