Addressing Safety and Security Challenges in ML-based AV Software Stack - Remote Operation Support and Balancing Trade-offs

In this work, the research team proposes a framework that enables safe and secure human remote operation when AV systems require support due to the inherent limitations of ML models used. The team develops an approach that can effectively detect and mitigate potentially malicious remote human operators, and satisfy the real-time requirements of remote operation despite possibly variable network conditions impacting the communication channel between the AV system and the remote operator. The solution will be demonstrated on the Mcity 2.0 testbed as a means to validate the proposed design in realistic settings.

• Record URL:
  https://ccat.umtri.umich.edu/research/u-m/addressing-safety-and-security-challenges-in-ml-based-av-software-stack-remote-operation-support-and-balancing-trade-offs/

Language

• English

Project

• Status: Active
• Funding: $280000
• Contract Numbers:

  69A3552348305

• 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:

  University of Michigan Transportation Research Institute

  2901 Baxter Road
  Ann Arbor, Michigan  United States  48109
• Project Managers:

  Stearns, Amy

  Bezzina, Debra

• Performing Organizations:

  University of Michigan, Ann Arbor Electrical Engineering and Comuter Science

  1301 Beal Avenue
  Ann Arbor, MI  United States  48109

  Purdue University, West Lafayette

  School of Civil Engineering
  West Lafayette, IN  United States  47907-1284
• Principal Investigators:

  Mao, Morley

  Feng, Yiheng

• Start Date: 20240901
• Expected Completion Date: 20250831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Computer security; Machine learning; Remote control; Vehicle operations; Vehicle safety
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Security and Emergencies; Vehicles and Equipment;

Filing Info

• Accession Number: 01929521
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3552348305
• Files: UTC, RIP
• Created Date: Sep 4 2024 5:18PM