Abstract: Aiming at the limited improvement of vehicle path tracking performance only with steering control, a coordinated control strategy for intelligent vehicle path tracking based on steering/yaw Nash game is proposed. Firstly, the cubature Kalman filter algorithm is utilized to estimate the tire lateral force in real time to realize the tire cornering stiffness self-correction. Then, based on the 2-DOF vehicle dynamics model, the Nash game theory is adopted for system modelling to describe the interaction of steering and yaw moment simultaneously applied to the vehicle, and the tracking accuracy and lateral stability are given as the separate control objective; by establishing prediction model, setting cost functions and solving Nash equilibrium, the optimal control variables of front wheel angle and yaw moment are obtained. Next, in order to reasonably meet different driving conditions, the vehicle stability envelope boundary considering the influence of longitudinal velocity and road adhesion coefficient is obtained based on β-ω phase plane, and the stability margin index is defined to classify the vehicle stability category for designing different control modes. The control modes switching and control variables’ values adjustment are realized by the adaptive adjustment of the control weight R, and the yaw moment is completed by differential braking strategy of single wheel. Finally, simulations and hardware in loop experiments are carried out, and the results show that Nash game has better control performance than model predictive control in path tracking coordination, the consideration of stability discrimination in control strategy improves the intervention accuracy of differential braking, and the weight adaptive adjustment enhances the control output’s adaptability to the change of driving conditions.

Key words: path tracking, tire cornering stiffness correction, stability judgment, Nash game, coordinated control