Obstacle Avoidance Trajectory Planning And Tracking Control For Autonomous Driving Vehicles

Autonomous driving technology is an important stage in the development of the automotive industry.Improving driving safety has always been the primary goal pursued by autonomous vehicles.Obstacle avoidance system,as the core link to reflect the driving safety of the automatic driving system,is an important guarantee to achieve the basic requirements of driving safety.When autonomous vehicles detects an obstacle,it will select the best obstacle avoidance method based on the detected information,and plan an optimal trajectory in combination with the traffic environment to avoid obstacles.According to the planned trajectory,the motion control system generates operations such as braking and steering to flexibly control vehicle behavior and achieve the safety goal of obstacle avoidance.So trajectory planning and vehicle motion control are the important realization modules of the obstacle avoidance function of the automatic driving system.This paper focuses on the obstacle avoidance control problem of autonomous vehicles,studies the obstacle avoidance trajectory planning and tracking control.The performance of the algorithm is verified and analyzed by simulation experiments.The trajectory planning and motion control of autonomous vehicles need to be achieved through the control of vehicle kinematics and dynamics system.Aiming at the obstacle avoidance control problem studied in this paper,vehicle kinematics and dynamics modeling are established.Kinematics is the study of the laws of motion of objects from a geometric point of view.Applying kinematics model in the trajectory planning algorithm can make the planned trajectory feasible and satisfy the geometric constraints of kinematics.In order to further consider the dynamics problems of vehicle stability control in the vertical and horizontal directions,a vehicle dynamics model with three degrees of freedom including longitudinal,lateral and yaw was established.The mathematical formula is used to describe the model to facilitate the theoretical research and systematic analysis of the model,which lays a foundation for the follow-up planning and tracking research.The obstacle avoidance problem of autonomous vehicles can be summarized as a continuous optimal control problem that satisfies a series of constraints while optimizing a certain performance index.Gauss pseudospectral method uses a series of numerical approximation techniques to transform the continuous optimal control problem into a discrete nonlinear programming problem.Through the numerical solution of the nonlinear programming problem,the state variable trajectory that satisfies various constraints and makes the performance index optimal is obtained.Considering that the tracking control needs to meet the multi-objective and multi-constraint in the driving process of the vehicle,the trajectory tracking controller is designed based on model predictive control in this paper.Based on the established three-degree-of-freedom nonlinear vehicle dynamics model,a trajectory tracking controller is designed to track the planned longitudinal speed and lateral displacement.Simulation experiment of Matlab/Simulink and Car Sim is performed to verify the effectiveness of controller.In this paper,aiming at the control problem of automatic obstacle avoidance,trajectory planning and tracking control are studied.A method for numerical solution of optimization problems with complex constraints is proposed,the optimal state in the obstacle avoidance process can be obtained through the solution,and the controller is designed to realize the tracking control of the desired state:(1)The planned trajectory is safe and feasible,and can achieve the goal of avoiding obstacles.(2)It can accurately and quickly realize the tracking control of vehicle speed and displacement.The research in this paper has a positive theoretical significance and value for the development of obstacle avoidance control of future autonomous driving vehicles.