Research On Trajectory Planning And Control Of Intelligent Connected Vehicles Under Urban Working Conditions

The intelligent connected vehicle can choose the best scheme according to its decision system and control the safe driving of the vehicle under the complex and changeable scene.In this paper,the trajectory planning and control methods of intelligent connected vehicles under urban working conditions are studied.The purpose is to improve trajectory tracking accuracy and save people’s travel time.The specific research content of this paper is as follows:(1)In this paper,the intelligent connected environment and intelligent vehicle system are built from the perspective of intelligent connected vehicle trajectory planning and decision control.Firstly,various environmental models of roads,traffic lights,trees and vehicles are built in Pre Scan.V2 X sensors are added to the controlled vehicles and transportation infrastructure.Then,the vehicle dynamics model and tire model are built in Simulink.Finally,the intelligent vehicle simulation model is built in Car Sim.(2)This paper presents an intelligent connected vehicle trajectory planning method based on improved A* algorithm.Firstly,the efficiency of the algorithm is improved by improving the heuristic function.Then,the constraint list and trajectory optimization strategy of A* algorithm are designed to complete the global trajectory planning in the intelligent network environment.Finally,the improved A* algorithm is compared with other A* algorithms in the intelligent network environment.The simulation results show that the improved A* algorithm proposed in this paper can carry out global trajectory planning in intelligent network environment,with higher planning efficiency and smoother trajectory.It is conducive to the driving of intelligent connected vehicle.(3)This paper designs three kinds of decision and control systems of intelligent connected vehicles under urban working conditions.Firstly,based on the status of traffic lights,the duration of the status and the location information of target vehicles,the speed prediction system is designed.Secondly,based on V2 X and TIS sensors,an intelligent connected overtaking system is designed.Then,according to the obstacle information of different states,the intelligent networkd vehicle dynamic obstacle avoidance system is designed.Finally,simulation experiments and hardware-in-the-loop tests are carried out respectively for the above decision systems.The results show that the decision control system designed in this paper is effective and can be applied to intelligent driving platform.(4)Based on the intelligent vehicle model,an intelligent connected vehicle trajectory tracking controller based on the improved terminal sliding mode controller is designed in this paper.Firstly,the controlled system of terminal sliding mode controller is built according to the lateral error and heading error of intelligent connected vehicle trajectory tracking.Then,the sliding mode surface,reaching law and control law are designed based on the control system model.The stability of the control system is proved by Lyapunov function.Finally,hardware in-loop tests with different control methods are carried out under different working conditions.The test results show that the terminal sliding mode controller designed in this paper has higher trajectory tracking accuracy and better stability than the MPC controller.