Machine Learning, Human Factors and Security Analysis for the Remote Command of Driving: An MCity Pilot

Both human drivers and autonomous vehicles are now able to drive relatively well in ‘typical’ (frequently- encountered) settings, but fail in exceptional cases. Worse, these exceptional cases often arise suddenly, leaving human drivers with a few seconds at best to react—exactly the setting that people perform worst in. This work proposes methods for leveraging groups of remote operators to provide assistance on- demand. Unlike prior work, we introduce collective workflows that enable groups of operators to significantly outperform any of the constituent individuals on control and correction tasks. We propose to develop a software platform for MCity that enables a group of remote operators to command the autonomous test vehicles at MCity. A pilot study will be conducted at the Mcity Test Facility.


  • English


  • Status: Completed
  • Funding: $178,371
  • Contract Numbers:


  • 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:

    Center for Connected and Automated Transportation

    University of Michigan Transportation Research Institute
    Ann Arbor, MI  United States  48109
  • Project Managers:

    Tucker-Thomas, Dawn

  • Performing Organizations:

    University of Michigan Transportation Research Institute

    2901 Baxter Road
    Ann Arbor, Michigan  United States  48109

    University of Michigan Computer Science and Engineering

    Ann Arbor, MI  United States 
  • Principal Investigators:

    Hampshire, Robert

    Lasecki, Walter

    Bao, Shan

  • Start Date: 20180901
  • Expected Completion Date: 20200831
  • Actual Completion Date: 20200831
  • USDOT Program: University Transportation Centers Program
  • Subprogram: Research

Subject/Index Terms

Filing Info

  • Accession Number: 01665948
  • Record Type: Research project
  • Source Agency: Center for Connected and Automated Transportation
  • Contract Numbers: 69A3551747105
  • Files: UTC, RIP
  • Created Date: Apr 12 2018 12:18PM