Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles
This addresses security and safety issues for CAV networks, but it appears incremental as it builds on existing trust-based methods for resilience.
The paper tackles the problem of adversarial attacks and uncooperative vehicles in networks of Connected and Automated Vehicles (CAVs) by proposing a decentralized resilient control and coordination scheme using a trust framework, which guarantees safe collision-free coordination and mitigates traffic jams as validated by simulation results.
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.