Research On Intelligent Vehicle Obstacle Avoidance Path Planning And Tracking Control Based On MPC

The development of intelligent vehicle industrialization provides an effective solution to solve urban traffic congestion and reduce traffic accidents.Research on intelligent vehicles can not only optimize the traffic environment,but also promote the development of other industries,which has become a research hotspot in recent years.At present,path planning and tracking control,as its core technology,have been studied a lot.However,the dynamic planning effect of obstacle avoidance path in obstacle environment is poor.At the same time,in the face of complex working conditions and large curvature road conditions,the effect of tracking control is still not ideal.Therefore,this paper takes intelligent vehicles as the research object,and studies the dynamic planning of obstacle avoidance path and path tracking control.Aiming at the problem of dynamic planning of obstacle avoidance path,the improved APF is used for path planning,and the elliptic obstacle repulsive potential field is used instead of the original repulsive potential field.The collision risk coefficient is introduced to establish the road boundary constraint and the lane gravitational constraint,and the velocity repulsive potential field is added.Through simulation experiments,it is proved that the improved APF can reasonably plan a safe obstacle avoidance path in a dynamic and static obstacle environment.In order to consider the dynamic characteristics of the vehicle,the potential field model function established by APF is introduced into the objective function and constraint of MPC,and the dynamic planner of obstacle avoidance path based on MPC and improved APF is designed.The optimal path is solved at each moment to realize the update of path planning in the whole prediction time domain.Aiming at the problem of path tracking control,a vehicle lateral path tracking controller based on MPC is established.The simulation experiments at 30 km/h,60 km/h and 90 km/h speeds are carried out respectively.It is found that the weight coefficient in the objective function has an impact on the tracking performance.Through the simulation analysis of different weight coefficients.The vehicle lateral path tracking controller based on fuzzy MPC is established,and the simulation test is carried out under the same speed condition as MPC,and the control effect of MPC and fuzzy MPC path tracking controller is analyzed and compared.The maximum lateral deviations corresponding to the three speed conditions are 0.217 m,0.283 m and 0.759 m,respectively.The results show that both of them can track the reference path more accurately under different speed conditions,but the fuzzy MPC path tracking controller has better control effect.Finally,the longitudinal PID speed tracking controller is established by hierarchical structure,and the simulation analysis is carried out under constant speed and variable speed conditions.The results show that the longitudinal PID speed tracking controller can track the desired speed well.Aiming at the problem of auxiliary driving system with following and obstacle avoidance mode,an intelligent vehicle autonomous following and obstacle avoidance system with following and obstacle avoidance mode is designed.The hierarchical structure control is adopted.The upper controller judges and switches the two modes according to the motion state information of the front vehicle perceived by the sensor,and calculates the expected acceleration in the corresponding mode.The lower controller determines the required throttle opening or braking pressure according to the expected acceleration and speed.At the same time,the obstacle avoidance path planner and the tracking controller perform path planning and tracking according to the motion state information of the controlled vehicle.Finally,all the information is sent to the vehicle model for control,and two typical driving scenarios are simulated.In the obstacle avoidance mode,the maximum yaw angle,yaw rate and lateral acceleration are 1.24 deg,0.437 deg/s and 0.189 m/s~2.The results show that the designed autonomous following and obstacle avoidance system can effectively follow and avoid obstacles,and plan a reasonable safe obstacle avoidance path.At the same time,the vehicle also has good stability and tracking.In order to verify the effectiveness and stability of the designed obstacle avoidance path dynamic planning and tracking control strategy.Based on the joint simulation test of MATLAB/Simulink and Carsim software,the joint simulation model of obstacle avoidance path planning and tracking control is established,and the simulation verification is carried out at different speeds of static obstacles,dynamic obstacles and dynamic obstacles.The results show that the planned path can avoid obstacles safely,and the vehicle has good tracking and stability during obstacle avoidance.Select the real vehicle test of obstacle path dynamic planning and tracking control under linear conditions;the maximum lateral distance of the planned path is greater than 2.5 m,indicating that the planned obstacle avoidance path can safely and effectively avoid obstacles.At the same time,the maximum steering wheel angle,yaw rate and sideslip angle of the vehicle during the tracking process are 159.8 deg,0.249 deg/s and 0.847 deg,respectively.The results show that the designed obstacle avoidance path dynamic planner and tracking controller have good tracking and stability.