The Research Of Local Path Planning And Path Tracking Method For Intelligent Vehicle

With the development of society,the number of vehicles is increasing rapidly.Traffic congestion,traffic accidents and air pollution caused by vehicles have seriously affected people’s life.Because intelligent vehicles with unmanned functions can solve these problems from many aspects,intelligent vehicles have gradually become the focus of attention and research.The driverless vehicle system of intelligent vehicle can be divided into five parts: environmental perception,navigation and location,path planning,path tracking and bottom control according to functional modules.In this paper,the local path planning and path tracking of intelligent car are studied in detail.The specific contents are as follows.Firstly,the system structure of the intelligent vehicle BJUT-IV is described in general,and the design scheme of the steering control system and the longitudinal control system in the bottom control system of the BJUT-IV intelligent vehicle is carefully explained,which lays the foundation for the later research.Secondly,aiming at the problem of the current local path planning method,such as poor quality of local path planning and inconsistent planning results,this paper proposes a temporal consistent intelligent vehicle local path planning method.The method is based on the motion differential constraint of the vehicle,and the motion constraint of the vehicle is added to the process of path generation.In view of the problem that the local path obtained by the independent periodic planning does not have the time consistency,the method puts forward the plan of "strong planning + weak planning".The strong planning part guarantees the obstacle avoidance ability of the algorithm,and the weak planning part ensures the consistency of the planning results obtained by the two adjacent planning cycles.Thirdly,aiming at the problem of low tracking accuracy and poor vehicle parameter constraint based on traditional geometry based intelligent vehicle path tracking,a path tracking method based on model predictive control is proposed.The simplified vehicle dynamics model is used as a prediction model,which not only guarantees the ability of vehicle dynamic parameter constraint,but also reduces the computational complexity of the algorithm.In order to ensure the safety of the intelligent vehicle,the method adds the side-slip-angle constraint of the tire,and improves the safety and path tracking ability of the vehicle.Fourth,a co-simulation platform based on CarSim and Matlab/Simulink is designed in this paper.The local path planning method with time consistency and path tracking method based on model predictive control are simulated and verified in this paper.The simulation results show that the proposed local path planning method can avoid obstacles effectively,and the planning results have time consistency,which improves the smoothness of vehicle running.For the proposed path tracking method,the simulation results show that this method has good constraint performance on vehicle side slip angle,and improves the safety of vehicle driving.Finally,the intelligent vehicle control software based on QT is designed to realize the planning and control ability of vehicle movement.A series of real vehicle experiments are carried out by using the control software,and the experimental results verify the effectiveness of the proposed methods.