Tight-coupling of Vision, Radar, and Carrier-phase Differential GNSS for Robust All-weather Positioning

Advanced driver assistance systems (ADAS) are a key technology for improving road safety. But both current and proposed ADAS are limited in important ways. Vision- and lidar-based ADAS performs poorly in heavy rain, snow, or fog. Lack of vehicle situational awareness due to these sensing limitations will unfortunately be the cause of many accidents, including fatalities, for connected and automated vehicles in the years to come. The goal of this research is to develop and test a sensing strategy with robust perception: No blind spots, applicable to all driveable environments, and available in all weather conditions. The project team believes there are three key requirements for collaborative all-weather sensing: (1) Precise vehicle positioning within a common reference frame (2) Decimeter-accurate vision and radar mapping; and (3) A means of quantifying the benefits of collaborative sensing.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Department of Transportation

    Intelligent Transportation Systems Joint Program Office
    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Project Managers:

    Bhat, Chandra

  • Performing Organizations:

    Data-Supported Transportation Operations and Planning Center

    University of Texas at Austin
    Austin, TX  United States  78701
  • Principal Investigators:

    Humphreys, Todd

  • Start Date: 20180901
  • Expected Completion Date: 20200831
  • Actual Completion Date: 0
  • Source Data: 154

Subject/Index Terms

Filing Info

  • Accession Number: 01670182
  • Record Type: Research project
  • Source Agency: Data-Supported Transportation Operations and Planning Center
  • Contract Numbers: DTRT13-G-UTC58
  • Files: UTC, RIP
  • Created Date: May 23 2018 4:35PM