Design And Experiment Of Trajectory Tracking Control Method For Self-driving Vehicles Based On Multi-Platform Simulation Vehicles

Autonomous driving technology is a current research hotspot in the automotive industry.In-depth research on autonomous driving technology can not only reduce the waste of oil resources,but also effectively improve the traffic environment and reduce the probability of traffic accidents caused by human factors.Therefore,this thesis conducts research on local obstacle avoidance planning and tracking control,which are key technologies for autonomous driving.The main research contents are as follows:(1)Establishing vehicle model and joint simulation platform.Based on the MATLAB/Simulink software platform,a 6-degree-of-freedom vehicle dynamics model and a magic formula tire model are constructed and simulated to obtain the linear regions of the longitudinal and lateral forces of the tires.The whole vehicle is modeled based on Car Sim simulation software,and a joint simulation model is built with MATLAB/Simulink.(2)The trajectory tracking controller is designed based on linear time-varying model predictive control.Firstly,the simplified nonlinear dynamics model of the vehicle is transformed into a linear time-varying system.Then the controller constraints and objective function are designed to construct the model prediction optimization problem and transform it into a quadratic programming problem for optimal solution.Finally,the performance of the trajectory tracking controller is verified by selecting the working conditions of 0.4 and 0.7 for the road adhesion coefficient and 15m/s,20m/s and 25m/s for the vehicle speed,and the results show that the controlled vehicle can track the reference trajectory accurately and stably with strong robustness under the above working conditions.(3)To address the problem of obstacles in the tracking reference trajectory,a hierarchical control system with an obstacle avoidance planning layer is designed.Firstly,the controlled vehicle in the planning layer adopts the point mass model,and the method of fusing target information points is selected to select the reference trajectory points and inflate the obstacles.Then the obstacle avoidance function and objective function are designed based on the model predictive control,and the layered controller is built with the trajectory tracking layer.Finally,we set the vehicle speed to 15m/s,20m/s and 25m/s for the simulation verification of straight line and double shift line.The results show that the obstacle avoidance hierarchical controller designed in this thesis can avoid the obstacles smoothly under both conditions,and all parameters of the vehicle are within the constraint range,with high lateral stability.(4)Build the whole vehicle hardware-in-the-loop test rig based on Speedgoat simulation platform.Prescan software is selected to establish the campus road test conditions and static obstacles,and the control system is built in MATLAB/Simulink,then the software and hardware are connected through the Speedgoat simulation platform,and finally different obstacle conditions are designed to verify the performance of the control system.The test results show that the real-time performance of the obstacle avoidance and tracking controller designed in this thesis is good,which can make the controlled vehicle achieve stable obstacle avoidance on the basis of meeting the vehicle safety driving conditions,and the tracking effect after obstacle avoidance has high accuracy and stability.