Exploring Safety and Security Accident-Management Policies for CAVs
The adoption of self-driving Connected and Automated Vehicles (CAV) in combination with advanced vehicle technology (AVT) has been actively pursued to enhance road traffic safety and decrease the occurrence of accidents. However, despite these concerted efforts, collisions have not been eliminated. Despite in-depth exploration into the management of Accident-Management (AM-) Policies, it is evident that this exploration in isolation may not be adequate to guarantee the secure management of traffic. This inadequacy originates from the absence of a robust mechanism for enforcement. To overcome these shortcomings, this project introduces a distributed, multi-user, multi-vehicle framework for the specification, evaluation, and enforcement of AM-Policies in the context of CAVs. To this end, this project will explore user needs from the viewpoints of passengers and bystanders and define potential AM-Policies based on varying case scenarios including CAV configurations, incidents, accidents, etc. Also, the research team introduces a theoretical model for AM-Policies leveraging Attribute-based Access Control (ABAC) for policy specification, analysis, and conflict resolution. Second, the team leverage blockchain technology to establish a decentralized framework for policy management that does not necessitate dependence on a single entity within the system, utilizing smart contracts to efficiently implement autonomous and binding agreements modeling the proposed AM-Policies. Third, the team proposes a multi-modal deep model for informative and accurate decision-making, such that different types of sensor signals and visual inputs, which are needed for successfully evaluating and enforcing AM-Policies, can be effectively incorporated.
- Record URL:
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Supplemental Notes:
- This material is based on work supported by the U.S. Department of Transportation, OST-R, University Transportation Center Program, the USDOT Tier 1 UTC Transportation Cybersecurity Center for Advanced Research and Education (CYBER-CARE).
Language
- English
Project
- Status: Active
- Funding: $100,000.00
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Contract Numbers:
69A3552348332
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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:
Transportation Cybersecurity Center for Advanced Research and Education (CYBER-CARE)
University of Houston
Houston, TX United States -
Project Managers:
Zhang, Yunpeng
Kline, Robin
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Performing Organizations:
Texas A&M University - Corpus Christi
6300 Ocean Dr.
Corpus Christi, Texas United States 78412 -
Principal Investigators:
Rubio-Medrano, Carlos E
- Start Date: 20231001
- Expected Completion Date: 20260630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Blockchains; Connected vehicles; Decision making; Deep learning; Incident management; Information processing; Traffic safety
- Subject Areas: Data and Information Technology; Planning and Forecasting; Safety and Human Factors; Transportation (General); Vehicles and Equipment;
Filing Info
- Accession Number: 01953954
- Record Type: Research project
- Source Agency: Transportation Cybersecurity Center for Advanced Research and Education (CYBER-CARE)
- Contract Numbers: 69A3552348332
- Files: UTC, RIP, STATEDOT
- Created Date: Apr 30 2025 3:58PM