Shared control with a novel dynamic authority allocation strategy based on game theory and driving safety field

Abstract

Abstract This paper proposes a novel dynamic control authority allocation strategy based on the elliptic driving safety field for the game-based shared control, which aims to deal with human-automation conflicts during obstacle avoidance. The noncooperative game theory is used for modeling the interaction between a human driver and the trajectory-following controller, where the Nash equilibrium solution is derived by distributed model predictive control (DMPC) approach. In addition, the elliptic driving safety field is introduced to evaluate the driving risk by considering the driver-vehicle-road interactions under different driving contexts. The authority allocation ratio, denoting the ratio between the lateral position error weight of the human driver’s cost function and the trajectory-following controller’s, is determined by the shared dynamic authority allocation strategy designed based on the evaluated driving risk. More importantly, two case studies are provided to verify the elliptic driving safety field and the proposed dynamic authority allocation strategy on a straight or curve road. The results show that the proposed strategy can help the vehicle obtain great performance for obstacles avoidance, and the control authority is dynamically shifted between a human driver and the trajectory-following controller according to the evaluated driving risk of current driving condition.