A Terminal Sliding Mode-based Individualized Trajectory Tracking Control Strategy via Haptic Assistance

To improve the human-vehicle cooperation and vehicle yaw stability in trajectory tracking, a terminal sliding mode-based individualized trajectory tracking control strategy via haptic assistance is presented in this paper. The driver-vehicle system model, including the vehicle dynamics model, the active front steering (AFS) model, and driver's arm dynamics model, is built for further controller design. A nonsingular fast terminal sliding mode (NFTSM)-based haptic assistance controller is presented to generate individualized haptic assistance torque to the driver. Then, an on-line sequence extreme learning machine (OS-ELM)-based estimator is introduced to approximate the equivalent control of the NFTSM controller for reducing the dependence of NFTSM performance on the modeling accuracy of system dynamics. Meanwhile, the fast integral terminal sliding mode control (FITSM) is applied to track the desired yaw rate to ensure vehicle stability during the trajectory tracking task. Driver-in-the-loop experiments in both general overtaking and emergency collision avoidance scenarios are conducted. Experimental results demonstrate that the proposed individualized trajectory tracking control strategy can enhance trajectory tracking performance by providing personalized driving assistance while improving vehicle yaw stability.