Secure control design for cooperative adaptive cruise control with a time-varying input delays under false data injection attacks

Connected and Autonomous Vehicles (CAVs) are shaping the future of transportation systems; however, their future development requires consideration of the upcoming challenges with cyber-physical attacks. Cooperative Adaptive Cruise Control (CACC) is one of the features used in CAVs. Using CACC increases the vulnerability of such systems to False Data Injection (FDI) attacks. To address this, this paper proposes a novel mitigation approach to compensate for FDI attacks and noise in real-time. In addition to FDI attacks, the current CACC algorithm suffers from input delay and disturbance. Here, we develop a nonlinear controller and an FDI attacks estimation technique to mitigate the effects of FDI attacks, noise, input delay and additive disturbance. Lyapunov–Krasovskii functionals are used in the Lyapunov-based stability analysis to ensure semi-global uniformly ultimately bounded tracking. In order to demonstrate the performance of the proposed approach, we validate it through simulation analysis.