Research on Human-machine Lateral Cooperative Control of Co-driving Vehicle Considering Driver Fatigue Characteristics

In the cooperative closed-loop system of intelligent vehicle, driver behavior will directly affect the vehicle's motion state, and fatigue driving constitutes a significant contributing factor to the incidence of road traffic accidents. Therefore, this paper proposes a human-machine shared cooperative lateral torque control method that takes into account driver fatigue characteristics. An advanced driving state detection model is built by fusing eye features with Deep-learning using Smart Eye Pro visual tracking system, and maps human-machine gain control factors for different states to achieve dynamic allocation of driving control. On this basis, a time-varying driver-intelligent driving system dual-loop T-S fuzzy road tracking control system is constructed using vehicle longitudinal speed and gain control factors. Furthermore, a human-machine collaborative shared lateral torque controller is designed. Ultimately, the effectiveness of the proposed control strategy in adapting to various fatigue characteristics of driving behaviors is verified through Hardware-in-the-Loop (HIL) experimental validation.