Trajectory Tracking Control of Driverless Racing Car Under Extreme Conditions

Aiming at the problem that it is difficult to ensure trajectory tracking accuracy and driving stability of driverless racing car under extreme conditions high-speed turning with different road adhesion coefficients, a control strategy proposed. Firstly, coefficient estimated using extended Kalman filter algorithm. Draw phase plane diagram vehicle’s centroid sideslip angle-centroid angular velocity. Use two-line method determine area obtain expected limit vehicle speed coefficients front wheel steering angle. Tracking desired travel achieved through drive brake control. Secondly, predictive algorithm based on adaptive prediction horizon model designed as lateral motion improve accuracy. Finally, MATLAB/Simulink CarSim co-simulation, results show proposed can conditions.