Robust Lateral Shared Control of Autonomous Vehicle Considering Driver NMS Characteristics

In view that the shared lateral control strategy of autonomous vehicles has no consideration of the neuromuscular（NMS）characteristics of the driver, the driver's maneuver cannot be adjusted adaptively according to the driver's state after taking-over. A vehicle steering system and a 2-DOF model are established respectively. The driver's maneuver is designated as interference input and the H∞ controller is designed with the steering wheel angle and yaw rate as state variables. Accordingly, the vehicle can track the anticipated steering wheel angle accurately. Aiming for the complex traffic conditions when automation's failure occurred and the driver required to take over immediately, a driver's arm dynamic model based on neuromuscular characteristics is proposed in this paper. For the influence of NMS parameter perturbation of the driver, a guaranteed cost robust controller is demonstrated with the anticipated steering wheel angle as input. So that, the driver can apply the ideal steering angle in order to tra