Unknown Input Estimation and FDI Attack Detection for Autonomous Vehicles

For autonomous vehicles that contain both unknown inputs and attack signals, this paper focuses on addressing the challenges associated with estimating unknown factors and detecting potential attacks. First, a dynamic model of an autonomous vehicle is proposed and combined with a lane keeping model, a model of an autonomous vehicle containing both unknown input signals and attack signals is constructed. Then the autonomous vehicle state and unknown input signals are estimated by designing a proportional integral observer. Also, an attack detection method for autonomous driving vehicles is proposed. Moreover, the viability of the proposed approach is verified through a simulation analysis conducted on real autonomous vehicles.