Research On Intelligent Vehicle Obstacle Avoidance Trajectory Planning And Tracking Control

With the development of economy and the improvement of scientific and technological level,the vehicle industry tends to be automated and intelligent,and autonomous driving technology has become a research hotspot nowadays.As two core modules of the auto drive system,trajectory planning and tracking control determine the comfort and stability of the autopilot vehicle in the driving process.Although there are many trajectory planning algorithms,it is still difficult to generate a good obstacle avoidance trajectory in real time in a dynamic environment.Aiming at the safety of trajectory planning and robustness of tracking control for intelligent vehicles facing obstacles in structured road scenes,this paper studies trajectory planning and tracking control algorithms,and establishes a joint simulation platform to verify the effectiveness of the algorithm.The specific research content of this article is as follows:(1)The obstacle avoidance path planning algorithm is optimized based on the artificial potential field.At present,the difficulty of trajectory planning is that the planning algorithm for intelligent vehicles in complex scenes needs to ensure real-time performance.In this paper,the vehicle motion is decoupled into lateral motion and longitudinal motion in the Frenet coordinates,and a polynomial curve is used to plan the vehicle’s travel path.Aiming at the phenomenon of unreasonable sampling points and wasted computational power in the conventional method of uniform sampling along the reference line,a path planning algorithm for optimizing sampling points using the artificial potential field method is proposed based on comprehensive consideration of obstacle information and road information,which improves the real-time performance of the algorithm and makes the planned path safer.(2)Dynamic obstacles are considered for speed planning,and further optimization is achieved through quadratic planning.This paper considers the dynamic movement of vehicles for speed planning.Firstly,projection the predicted vehicle travel trajectory onto the path planned in the previous chapter,draw an S-T diagram,search for a rough speed curve that can be avoided through dynamic planning algorithms,and then set constraints to optimize the speed curve twice,planning a speed curve that meets safety and comfort.(3)Track tracking control and comprehensive simulation verification.In order to verify the effectiveness of the trajectory planning algorithm in this paper,a vehicle trajectory tracking control algorithm is designed,which uses a lateral and longitudinal decoupling method to control the vehicle’s heading angle and vehicle speed respectively.Based on the Prescan-Carsim-Simulink joint simulation platform,a comprehensive simulation scenario including static obstacle avoidance,overtaking,and following was built.The simulation results show that the trajectory planning algorithm for vehicle obstacle avoidance scenarios in this paper can generate the optimal trajectory with both safety and comfort,and the tracking control part can ensure good stability and high tracking accuracy.