Path Tracking Lateral And Longitudinal Control Research For Autonomous Vehicle

As an important module of autonomous vehicle decision planning,path tracking has high research value.Path tracking requires not only accurate tracking of the reference path,but also speed control in the tracking process.This paper mainly studies the path tracking longitudinal speed control algorithm and lateral angle control algorithm in autonomous vehicle decision planning.The main research contents are as follows:(1)Aiming at the problem of automatic adjustment of vehicle speed when driving,a speed planning controller based on fuzzy control theory is designed to realize the speed planning according to the factors such as road curvature,lateral tracking error and road adhesion coefficient according to the characteristics of many influencing factors and difficult to establish accurate mathematical model.In order to solve the problem of speed tracking,a hierarchical control method is adopted to design the speed tracking controller.The upper controller uses PID control to o btain the desired acceleration,and the lower controller uses the inverse longitudinal dynamic model to analyze and calculate the control amount of throttle and brake according to the expected acceleration.At the same time,the switching rules of throttle and brake control are designed to avoid frequent switching between the two during control Ensure comfort and stability when driving.The simulation results show that the speed planning and speed tracking controller designed in this paper can meet the requ irements of unmanned vehicle path tracking longitudinal control.(2)Based on model predictive control theory and pure pursuit control theory,a lateral path tracking controller is designed.The simulation results show that the pure pursuit control algorithm is suitable for the conditions of medium low speed and large initial deviation,while the model predictive control algorithm is suitable for the conditions of medium high speed and small initial deviation.This conclusion lays a theoretical foundation for the proposed switching control algorithm.(3)In order to solve the problem that a single control algorithm can not meet the control performance requirements under various working conditions,considering the advantages and disadvantages of the two control algorithms,a switching control strategy based on model predictive control algorithm and pure pursuit control algorithm is proposed.At the same time,in order to prevent the large step of the front wheel angle output when the control al gorithm is switched and affect the lateral stability of the system,a switching stability controller based on the fuzzy control theory is designed.The front wheel angle output values of the pure tracking controller and the model predictive controller are weighted respectively.The simulation results show that the proposed algorithm can track the target path accurately and stably,and control the appropriate change of vehicle speed,which can effectively improve the performance of path tracking control process.