Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles
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Abstract (arXiv)
We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area. Adversarial attacks such as Sybil attacks can cause safety violations resulting in collisions and traffic jams. In addition, uncooperative (but not necessarily adversarial) CAVs can also induce similar adversarial effects on the traffic network. We propose a decentralized resilient control and coordination scheme that mitigates the effects of adversarial attacks and uncooperative CAVs by utilizing a trust framework. Our trust-aware scheme can guarantee safe collision free coordination and mitigate traffic jams. Simulation results validate the theoretical guarantee of our proposed scheme, and demonstrate that it can effectively mitigate adversarial effects across different traffic scenarios.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 35 references that are in the map. First posted on arXiv 26 May 2023.
Builds on
9 of 35 references.
References · 9
- 2019Control Barrier Functions for Systems with High Relative Degreecited by 30
- 2020A Survey on Security Attacks and Defense Techniques for Connected and Autonomous Vehiclescited by 10
- 2020Bridging the Gap between Optimal Trajectory Planning and Safety-Critical Control with Applications to Autonomous Vehiclescited by 6
- 2020Impact Evaluation of Falsified Data Attacks on Connected Vehicle Based Traffic Signal Controlcited by 3
- 2021Resilient Cooperative Adaptive Cruise Control for Autonomous Vehicles Using Machine Learningcited by 3
- 2021Evaluating Cybersecurity Risks of Cooperative Ramp Merging in Mixed Traffic Environmentscited by 2
- 2022Trust-based Rate-Tunable Control Barrier Functions for Non-Cooperative Multi-Agent Systemscited by 2
- 2020On the Security of Networked Control Systems in Smart Vehicle and its Adaptive Cruise Controlcited by 1
- 2021Trust-aware Control for Intelligent Transportation Systemscited by 1
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.