Mandatory lane-changing decision and control method based on game theory - Zhe Wang; Xinyi Zhang; Haoze Ren; Liu Yang (PLoS ONE, 2026)
This paper proposes a lane-changing decision and control framework for mandatory lane-changing scenarios based on stage game decision-making. The lane-changing process is discretized, and payoff functions are constructed for the autonomous vehicle and the following vehicles in the target lane, enabling adaptive adjustment of driving strategies and planned trajectories according to surrounding vehicle interactions. The optimal lane-changing decision is dynamically updated by incorporating environmental information and interactive feedback from surrounding vehicles. For trajectory tracking, a composite error combining lateral displacement and heading angle deviations is defined and constrained using a preset performance boundary. The constrained error is transformed into an equivalent unconstrained form, and a sliding mode controller is designed to ensure robust tracking performance. A joint simulation platform integrating traffic simulation and driver-in-the-loop experiments is established to evaluate the proposed framework. A preliminary study involving three human drivers with different driving tendencies is conducted to analyze interaction behaviors in mandatory lane-changing scenarios. The experimental results provide initial insights into the effectiveness of the proposed approach under representative conditions.