Research On Path Planning And Tracking Control Of Driverless Vehicle For Dynamic Obstacles

With the continuous development of computer and automatic control technology,driverless vehicle is the inevitable trend of future vehicle development.As an important function of driverless vehicle technology,obstacle avoidance control will directly affect the working performance of driverless vehicle,which is an important part of realizing the safe driving of driverless vehicle.The path planning and track tracking technology is one of the main methods to avoid obstacles for driverless vehicles.Therefore,the research on path planning and track tracking control technology has important theoretical significance and application value for the realization of driverless vehicle safe driving.Firstly,this paper studies the A* algorithm for global planning,analyzes the heuristic function and algorithm flow for searching path.Aiming at the problem that the search path of A* algorithm does not consider the influence of road slope on the shortest path and the influence of road rolling resistance coefficient on vehicle energy loss,a comprehensive heuristic function based on road slope and rolling resistance coefficient is proposed.A* bidirectional search algorithm is used to improve the search efficiency.Finally,cubic spline interpolation method is used to smooth the planned trajectory.Secondly,the APF algorithm for local obstacle avoidance is analyzed and studied.Aiming at the influence of speed and volume of obstacles on vehicle obstacle avoidance,the dynamic vector repulsion potential field function and the volume and speed repulsion potential field function are proposed.Aiming at the problem that the distance between the target point and the vehicle is different,which leads to the different attraction of the target point to the vehicle,and indirectly causes the safety distance between the vehicle and the obstacle to be too small,a predictive control strategy for obstacle avoidance is proposed.Finally,the APF algorithm of local obstacle avoidance is integrated into the A*algorithm of global planning.The MPC-APF control system,which is the core part of the algorithm,is studied.The model predictive controller for trajectory tracking is studied.The objective function is designed and the vehicle kinematic model and system constraints are established.The sub objective point selection method of APF algorithm is determined in three scenarios.Based on the research and theoretical analysis of the above algorithm,simulation examples are designed to verify the improvement of each part.The simulation results show that the A* bi-directional search algorithm based on the comprehensive heuristic function designed in this paper is more efficient than the traditional algorithm and more accurate in searching the optimal path;the improved APF algorithm is more secure in dynamic obstacle avoidance;the A* algorithm combined with the APF algorithm can not only avoid the local obstacles in unknown environment,but also avoid the obstacles twice after the global path planning,further improving the unmanned path Vehicle driving safety.