Research on Emergency Collision Avoidance System of Man-Machine Cooperative Driving Vehicles Based on Additional Yaw Moment Control

Abstract

Drivers of man-machine cooperative driving intelligent vehicles are affected by driving skills, physiological reactions, and other factors. Under emergency conditions, they often subconsciously forcefully take over control rights and produce unreasonable stress steering, which brings new accident risks to vehicles. To avoid collisions, this paper proposes an emergency collision avoidance control strategy for man-machine cooperative driving vehicles. In the collision avoidance path planning layer, considering the obstacle distance, road adhesion coefficient, vehicle speed, steering wheel stress angle, and driver’s linear steering cognition, a circular arc lane-change path is designed. The curvature mutation is smoothed using the third-order Bezier function. In the tracking control layer, a method of additional yaw moment control is designed by using the model predictive control (MPC) algorithm to track the path. The accuracy and safety of vehicle tracking are guaranteed only by adjusting the braking torque of each wheel of the vehicle, to correct the unreasonable input when the driver forces to take over. The co-simulation results show that the collision avoidance control system can effectively correct the unreasonable input during forced take-over, and ensure the safety of stress steering.