Reinforcement learning-based control for autonomous vehicle trajectory tracking under coupled physical-cyber disturbances
Simulation results demonstrate that the proposed method outperforms robust control and adaptive model predictive control in tracking accuracy under varying attack intensities, validating the effectiveness of the unified RL-based framework for AVs under coupled physical-cyber threats.