Research On Trajectory Planning Optimization Algorithm For Autonomous Vehicles

Automatic driving technology can reduce the occurrence of traffic accidents and improve the traffic efficiency of road vehicles.Over the years,it has been vigorously developed.As an important part of autonomous driving technology,trajectory planning can directly reflect the level of autonomous driving.This paper studies the trajectory planning and tracking control of vehicles in the traffic environment under the interference of dynamic obstacles.The coordinate system commonly used in automatic driving is analyzed,the importance of Frenet coordinate system in trajectory planning is expounded,and the mapping relationship between Cartesian coordinate system and Frenet coordinate system is derived.The quadratic programming problem of the discrete position points of the reference path is constructed,and the original reference path is smoothed.The code writing and experiment are completed by Matlab.The detailed analysis of the reference path before and after smoothing verifies that the method is of great help to the reference path smoothing.Considering the scene of multiple dynamic obstacles,a geometric obstacle avoidance model that can describe the relationship between the vehicle itself and the obstacle motion is proposed.By analyzing the relationship between the vehicle and the obstacle in terms of spatial distance and speed,and using the three related elements to characterize the threat of obstacles to the safety of the vehicle.Based on the principle of model predictive control(MPC),the discrete kinematics model of the vehicle is used as the prediction model,and the Frenet coordinate system is used to comprehensively consider the road boundary,the mechanical structure of the vehicle itself,the safety and comfort of the vehicle.The objective function and constraints are constructed,and the nonlinear programming problem is finally established and solved.The simulation results show that the method can realize the trajectory planning of vehicle path and speed coupling in the environment with dynamic obstacles,and preliminarily meet the real-time performance.In the control,the lateral and longitudinal decoupling of the vehicle is completed,and the overall trajectory tracking is completed by combining path tracking and speed tracking.On the path tracking controller,a two-degree-of-freedom dynamic model of the vehicle is established.After linearization,it is used as a predictive model,constraints are introduced,and the objective function is transformed into a quadratic programming problem.A model predictive control tracking controller for dynamics is designed.In addition,the pure tracking method is improved,and the front wheel compensation angle is obtained based on the lateral deviation and heading angle,which improves the tracking accuracy.SERES SF5 is used as an experimental vehicle,and a hardware sensor is installed to build an automatic driving experimental platform.The trajectory planning and tracking algorithm is deployed on the ROS + Matlab / Simulink software platform,and the trajectory planning and tracking experiments are carried out respectively.The results show that the method can not only avoid obstacles smoothly,but also obtain reasonable and comfortable driving trajectory.