Research On Path Planning And Tracking Control Of Unmanned Based On Chassis By Wire

With the increasing number of cars in China,traffic safety and traffic efficiency have become urgent problems to be solved,and unmanned vehicles can improve road traffic safety and alleviate traffic congestion,which has become a research hotspot in the field of automobiles.Environmental awareness technology is the premise of unmanned driving,and stable and reliable path planning and tracking control methods are the core and necessary conditions to realize unmanned driving.Therefore,this paper makes an in-depth study on path planning and tracking control methods of unmanned vehicles,and the specific research contents are as follows:Firstly,aiming at the defects that a single global path planning algorithm lacks the ability of dynamic obstacle avoidance and a single local path planning algorithm lacks the ability of global information guidance,a path planning algorithm combining dynamic and static is proposed.The environmental point cloud information collected by the lidar sensor is used to build a global map,and after the positioning function is complete,the optimal global static path is obtained by the dynamic programming method.Then,the global static path is sampled locally,and the optimal local dynamic path is obtained by predicting the behavior of obstacles and evaluating the cost of the planned path.Finally,the path is smoothed by the conjugate gradient method,which improves the smoothness of the path and lays a good foundation for the follow-up tracking control.Secondly,aiming at the problem that the tracking effect of the traditional pure tracking algorithm is greatly affected by the forward-looking distance,a fuzzy controller is designed to adjust the forward-looking distance adaptively,and the lateral error and heading error are taken as the inputs of the fuzzy controller to output the dynamically changing forward-looking distance.Aiming at the shortcoming of a traditional pure tracking algorithm that only has lateral tracking control,a longitudinal speed tracking controller is designed,which adjusts the longitudinal speed based on curvature and tracks the speed based on proportional differential control.The simulation results show that the proposed comprehensive control strategy for vertical and horizontal tracking greatly improves the tracking effect and stability compared with the traditional pure tracking algorithm.Finally,to verify the effectiveness of the proposed path planning and tracking control method,a test platform is built based on the wire-controlled chassis,and ROS and Autoware unmanned platforms are deployed..After the sensor completes the sensing and positioning function,a real vehicle test is carried out,aiming at the path planning and tracking control effect.The experimental results show that the proposed planning algorithm can complete the global planning function and realize the autonomous real-time obstacle avoidance function along the locally optimal path.Compared with the traditional pure tracking algorithm,the tracking control accuracy and stability of the proposed control strategy are improved,the lateral trajectory tracking error is reduced by 69.8%,and the steering angle change is reduced by 45.1%.