Research On Path Planning And Tracking Control Method For Active Collision Avoidance Of Intelligent Vehicles

In recent years,with the improvement of world productivity,the car ownership in various countries has maintained a high level and continued to grow,with the emergence of traffic congestion,traffic accidents and other worldwide problems.Every year,the number of people killed and injured by traffic accidents all over the world remains high.The technology of automatic driving vehicle arises at the historic moment.Vehicle collision avoidance technology is an important part of it.This paper mainly studies the collision avoidance technology of intelligent vehicle active steering,that is,the technology of trajectory re-planning and trajectory tracking when the vehicle runs normally on the original road and encounters obstacles.Firstly,the research background,significance and the development status of the intelligent vehicle collision avoidance technology are discussed.The related methods of current intelligent vehicle path planning and trajectory tracking control technology,as well as the advantages and disadvantages of these methods are introduced in detail.This paper combines the advantages of the two control algorithms of PID control and fuzzy control,and determines that the fuzzy adaptive PID trajectory tracking controller is used as the trajectory tracking layer of collision avoidance model to overcome the disadvantage of single PID controller parameter can not be adjusted online.In order to avoid the problem of poor tracking under limit conditions,the application of MPC control algorithm in trajectory tracking layer is determined.In order to solve the trajectory planning problem of intelligent vehicles in dynamic environment,the model predictive trajectory re-planning algorithm is selected as the trajectory planning layer.Secondly,the vehicle coordinate system and two-degree-of-freedom vehicle dynamics model are established for the intelligent vehicle with wheel steering.In the course of studying the trajectory tracking problem,the establishment process of the fuzzy PID trajectory tracking controller and the MPC trajectory tracking controller is introduced in detail,and the tracking effect is simulated in the environment of MATLAB/Simulink.The results show that when the vehicle speed is 18 km/h,36 km/h and 72 km/h,they have ideal tracking effect for different tracking trajectories(straight line and double line shifting).Then,the application of model prediction theory in trajectory reprogramming in dynamic environment is introduced in detail,and the trajectory planner of intelligent vehicle collision avoidance model is established.In order to meet the needs of real-time and robustness,the point-mass vehicle model with less computation is adopted in the trajectory planning layer of this paper.Finally,the paper uses the fuzzy PID and MPC controllers as the trajectory tracking layer,and the model predictive dynamic trajectory planner as the trajectory planning layer,and builds the trajectory planning + trajectory tracking double-layer controller as the intelligent vehicle steering collision avoidance model.Finally,the collision avoidance effect is simulated in Matlab/Simulink environment.The results show that when the vehicle speed is 18 km/h and 36 km/h,the model has better collision avoidance effect and can track the original trajectory in time after collision avoidance.But when the vehicle speed is 72 km/h,because of the high speed,the early addition of obstacle information will lead to the early trajectory re-planning and deviation of the intelligent vehicle.The original trajectory,but on the whole,the collision avoidance model has achieved the design goal of collision avoidance.The trajectory planning and tracking algorithm selected in this paper can meet the requirements of the intelligent vehicle active collision avoidance technology.