Experimental Results in Cyber-Physical Transportation Systems: A Case Study in Cybersecurity

Details

• Creators:
  Ha, Won Yong ; Chakraborty, Sayan ; Ozbay, Kaan ; Jiang, Zhong-Ping
• Corporate Creators:
  New York University
• Corporate Contributors:
  Connected Communities for Smart Mobility Toward Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER) Tier-1 University Transportation Center (UTC) ; 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:
  Autonomous Vehicles Congestion Management Systems Connected Vehicles Learning-based Control Machine Learning Perception-in-the-loop Resilient Reinforcement Learning Trajectory Control Vehicle Mix
• Resource Type:
  Manuscript
• Right Statement:
  Public Domain
• Geographical Coverage:
  United States
• Corporate Publisher:
  Connected Communities for Smart Mobility Toward Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER) Tier-1 University Transportation Center (UTC)
• Abstract:
  This paper presents experimental results from a learning-based control framework for cyber-physical transportation systems. Building on theoretical guarantees that establish an upper bound on denial-of-service (DoS) attack durations to maintain closed-loop stability, we deploy a resilient learning-based lane-changing control algorithm on a remote-controlled (RC) autonomous vehicle equipped with GPS, IMU, and camera sensors, interfaced with an Nvidia Jetson AGX Xavier board. The algorithm leverages real-time sensor data to make suboptimal yet robust lane-change decisions while enduring intermittent DoS attacks that disrupt communication. Our experiments confirm the resilience of this learning-based approach, demonstrating safe and efficient maneuvers under adversarial conditions in obstacle-rich driving scenarios. By highlighting these experimental findings, this work underscores the importance of cybersecurity in next-generation vehicle control algorithms for autonomous transportation applications.
• Content Notes:
  Public Domain, except where noted in the document. Ha, Won Yong, Sayan Chakraborty, Kaan Ozbay, and Zhong-Ping Jiang. Experimental Results in Cyber-Physical Transportation Systems: A Case Study in Cybersecurity.
• Format:
  PDF
• Funding:
  69A3552348326
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:beef7fbb64487699d5e8c79f46262876760c7fa0cb2fc8f1f17ed1636ca0bfa5cbaac13d9ea36ce9bbc6b8584257143b8108ecf631b221b5b89aacaa6c80556e
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/86346/dot_86346_DS1.pdf
• File Type:
  [PDF - 4.34 MB ]