A Cyberattack Detection-Isolation Scheme For CAV Under Changing Driving Environment
Under a changing driving environment, a Connected Autonomous Vehicle (CAV) platoon relies strongly on the acquisition of accurate traffic information from neighboring vehicles as well as reliable commands from a centralized supervisory controller through the communication network. Even though such modalities are imperative to ensure the safe and efficient driving performance of CAVs, they led to multiple security challenges. Thus, a cyberattack on this network can corrupt vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication, which can lead to unsafe or undesired driving scenarios. Hence, in this paper, we propose a unified V2V and V2I cyberattack detection scheme along with a V2I isolation scheme for CAVs under changing driving conditions. The proposed scheme is constructed using a bank of residual generators with Lyapunov function-based performance guarantees, such as disturbance-to-state stability, robustness, and sensitivity. Finally, we showcase the efficacy of our proposed algorithm through two simulation studies, namely under highway driving and urban driving. The results show that the proposed scheme can enhance the cybersecurity of CAVs by detecting and isolating cyberattacks on CAV platoons.