Systematic and Provably Safe Design Methodology for Connected and Autonomous Vehicles

Today’s sensor technologies are not at the level of emulating human eyes with 100% accuracy. Recent accidents with autonomous vehicles where sensors failed to correctly identify the threat suggests that sensor possible inaccuracies or inability to identify upcoming obstacles due to environmental conditions, road geometry, unpredictable vehicle maneuvers and traffic conditions need to be taken into account in a more systematic way. The safety-critical nature of autonomous vehicles calls for systematic analysis and design procedure to ensure safety of the passengers, pedestrians, and other actors on the road by taking into account sensor uncertainties, road geometry, weather, traffic conditions, traffic rules etc. The purpose of this project is to investigate a systematic control design methodology for provably safe autonomous vehicle operations for wide range of driving conditions using dynamic safe sets. The dynamic safe sets expressed in terms of control barrier functions (CBFs) are continuously updated based on the health of sensors, road geometry, traffic rules, weather conditions, emergency situations etc by taking into account possible uncertainties. The vehicle controller is updated using quadratic programming optimization to keep the states of the vehicle inside the safe sets. The safe set is defined in such a way that its forward-invariance would guarantee the safety of passengers, neighboring vehicles, pedestrians, obstacles as well as compliance to traffic rules. The project team proposes to establish a methodology for developing dynamic safe sets that are continuously updated specifying where the states of the vehicles should be in order to guarantee safe operations. The project team then develops a control design methodology that guarantees that the vehicle states are always inside the dynamic safe sets while maintaining mobility. Such systematic and provable safe guaranteed control design methodology that exploits the dynamics of the vehicle and surrounding road and traffic environment and accounts for sensor inaccuracies and other external effects is very fundamental to the success of deploying autonomous vehicles.


    • English


    • Status: Completed
    • Funding: $100000
    • Contract Numbers:


    • Sponsor Organizations:

      Department of Transportation

      Federal Motor Carrier Safety Administration
      1200 New Jersey Avenue, SE
      Washington, DC    20590

      Department of Transportation

      Office of the Assistant Secretary for Research and Technology
      1200 New Jersey Avenue, SE
      Washington, DC  United States  20590
    • Managing Organizations:

      METRANS Transportation Center

      University of Southern California
      Los Angeles, CA  United States  90089-0626
    • Performing Organizations:

      University of Southern California, Los Angeles

      University Park Campus
      Los Angeles, CA  United States  90089
    • Principal Investigators:

      Ioannou, Petros

    • Start Date: 20220815
    • Expected Completion Date: 20230814
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers

    Subject/Index Terms

    Filing Info

    • Accession Number: 01854744
    • Record Type: Research project
    • Source Agency: National Center for Metropolitan Transportation Research
    • Contract Numbers: 69A3551747109
    • Files: UTC, RIP
    • Created Date: Aug 16 2022 6:47PM