Cooperative Control Research on Emergency Collision Avoidance of Human–Machine Cooperative Driving Vehicles

When faced with an emergency, drivers of human-machine shared driving are prone to unconsciously generate excessive control, collision avoidance and stability maintenance are two critical issues. To avoid collision when the driver is stressed to produce an unreasonable handwheel steering input, this paper proposes a cooperative control strategy of emergency collision avoidance for human-machine shared driving. The improved circular arc docking collision avoidance path is adopted in the collision avoidance path planning layer based on the relative motion state and position relationship between the vehicle and the obstacle, and its geometric discontinuities are smoothed considering vehicle size and common driver steering perception. A nonlinear dynamics model of the vehicle is established in the tracking control layer, and a multi-constraints Model Predictive Control (MPC) method is utilized to calculate the additional yaw moment to correct for driver's excessive stress handwheel input. A brake wheel preference and torque distribution strategy are used to ensure vehicle stability. The co-simulation results show that the cooperative control algorithm efficiently ensures the safety and stability of human-machine shared driving vehicles in emergency collision avoidance at high speeds and low road adhesion coefficients.