Local Path Planning And Tracking Of Intelligent Vehicle In Complex Dynamic Environment

In recent years,the global automobile ownership is increasing day by day,environmental pollution and energy shortage are becoming more and more serious.People put forward higher requirements for environmental protection,energy consumption and occupant safety.Autonomous vehicles have become the research hotspot of automobile enterprises and research institutes all over the world.Local path planning and path tracking are two key technologies in unmanned aerial vehicle research.Aiming at the problem that the existing path planning and tracking technology can not meet the requirements of the complex and changeable environment,which leads to the failure of path planning and tracking,this paper proposes a planning control algorithm which can realize path planning and tracking in complex and dynamic environment.The main research work of this paper is as follows:Aiming at the problem of local path planning in complex dynamic environment,an intelligent vehicle local path planning algorithm based on discrete optimization method is proposed in this paper.Firstly,based on the global path and sensor information,a curved road model including Lane line,static obstacle and dynamic vehicle is established.Secondly,based on the initial position and heading angle of the target vehicle,a set of candidate paths are generated in the curvilinear coordinate system.Finally,a new cost function considering static security,comfort,multi-obstacle dynamic security,target lane and road occupancy rate is designed to evaluate the risk of each path,so as to select the optimal path.The simulation under several typical working conditions verifies the validity and real-time of the path planning algorithm in complex dynamic environment.Aiming at the lateral control problem of intelligent vehicle path tracking,a path tracking controller based on fractional order PID control algorithm is designed.The algorithm is based on preview theory,in which the deviation between the expected heading angle and the actual heading angle is used as the input of the controller.In order to minimize the tracking error,particle swarm optimization(PSO)algorithm is used to tune the parameters of fractional order PID controller.The effect of path tracking under different road structure,driving speed and slip rate is studied,and the effectiveness and robustness of the path tracking algorithm are verified.To verify the effectiveness of path planning algorithm with tracking deviation,a joint simulation platform for path planning and path tracking is built based on Simulink and Carsim.Typical simulation conditions are designed to verify the effectiveness of path planning and path tracking algorithm.The simulation results show that in complex dynamic environment,the path planning and path tracking algorithm can effectively guide and control the vehicle to achieve automatic driving.