Research On Trajectory Planning And Tracking Control Of Campus Unmanned Logistics Vehicle Obstacle Avoidance

With the rapid development of courier business,unmanned logistics vehicles are emerging in more and more campuses,but the complex driving environment on campus has brought great challenges to the efficient and safe driving of unmanned logistics vehicles.In this paper,the trajectory planning algorithm and tracking control algorithm of campus unmanned logistics vehicles are studied to solve the problems of conservative obstacle avoidance strategy and poor dynamic obstacle avoidance effect,and to improve the delivery efficiency and safety of campus unmanned vehicles.Considering the driving environment of campus unmanned logistics vehicles,three typical traffic conflict scenarios are selected and modeled in Prescan as the environment model to verify the effectiveness of the algorithm;three vehicle models are established and compared as the model basis for the later planning and control algorithm.By comparing different global path planning algorithms through simulation analysis,the JPS(Jump Point Search)algorithm with higher computational efficiency is selected as the global path planning algorithm for unmanned logistics vehicles,and the JPS algorithm is improved for the problem that the paths planed by JPS algorithm are too close to obstacles,and the JPS algorithm based on the jump point improvement strategy is proposed.The improved JPS algorithm search speed is 3.97 seconds,which is 17 seconds faster than A* algorithm,and can keep a safe distance from obstacles when turning;Through simulation analysis and comparison,MPC(Model Predict Control,MPC)algorithm is selected as the local trajectory planning algorithm,and for the problems such as poor dynamic obstacle avoidance ability of MPC trajectory planning algorithm,MPC-VO trajectory planning algorithm is proposed based on VO(Velocity Obstacle,VO)algorithm,which considers the unmanned logistics vehicle operation process of moving The algorithm considers the driving state of obstacles during the operation of unmanned logistics vehicle,modifies the objective function of traditional MPC trajectory planning algorithm,and the simulation results show that the trajectory planned by MPC-VO algorithm can avoid dynamic obstacles better and keep the distance from obstacles compared with the trajectory planned by traditional MPC algorithm.The MPC trajectory tracking controller is built based on the kinematic model,and the trajectory tracking problem of the unmanned vehicle is transformed into a quadratic programming problem.The problem is solved to obtain the control results;The MPC trajectory tracking control module and the controlled vehicle model are built based on the joint simulation environment of Carsim and Simulink,and the tracking control simulation is verified for the double-shift trajectory and S-curve trajectory at different speeds.The results show that the controller can ensure the vehicle driving stability and has good control accuracy.Based on the joint simulation environment of Carsim,Simulink and Prescan,a conflict scenario model is built and the simulation of the obstacle avoidance algorithm proposed in this paper is verified.The results show that the controlled vehicle can successfully avoid dynamic obstacles and maintain driving stability.In this paper,we built an obstacle avoidance control verification platform based on d SPACE SCALEXIO and Carsim,wrote the DBC file,built the CAN communication module and the planning and control module.The algorithm is validated in a conflict scenario established in Carsim,and the results show that the proposed algorithm works well for obstacle avoidance.