Cybersecurity of Next-Generation Traffic Signal Control With CAVs

Details

• Creators:
  Stern, Raphael ; Kiani, Amirhossein
• Corporate Creators:
  Center for Connected and Automated Transportation (CCAT) ; University of Minnesota. Center for Transportation Studies
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Traffic signal timing
  • Connected vehicles
  • Automated vehicle control
  • Transportation
  • Computer security
  • Traffic actuated controllers
  • Cyberattacks
  • Data analysis
  • Risk assessment
• Publication/ Report Number:
  CTS 26-06
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (September 2023 - December 2025)
• Corporate Publisher:
  University of Michigan. Center for Connected and Automated Transportation
• Abstract:
  This report explores cyber vulnerabilities that exist in new approaches for actuated traffic flow management where individual connected and automated vehicles share information about their arrival to a reinforcement learning based traffic signal. Using this approach, potential cyberattacks include false data injection attacks, where vehicles report false data. We find that new signal techniques are vulnerable to such attacks, deteriorating intersection level of service, and also present approaches to overcome this vulnerability through federation.
• Format:
  PDF
• Funding:
  69A3552348305
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/89920/dot_89920_DS1.pdf
• File Type:
  [PDF - 5.36 MB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; University Transportation Centers
• Main Document Checksum:
  urn:sha-512:54ec957d47c9e6deb871790e5c366afd0be32ca8ce16de2bdcd826c846ca4323dd4f6582232ab47f18f8a06da2550a8935efd07be77702ba90793902b501d1ea