Research On Lane-changing Obstacle Avoidance Dynamic Path Planning And Tracking Control For Driverless Vehicles

With the improvement of science and technology and economy year by year,vehicles have been all over the streets.Although vehicles have brought great convenience to daily life,the increasing number of vehicles in successive years leads to more frequent traffic safety problems and environmental pollution problems.Drivers will be affected by various factors in the process of driving,and many traffic safety problems are related to the driver’s state fluctuation.Driverless vehicles are designed to dilute the role of the driver in driving.Path planning and tracking control are important modules in driverless vehicles,whose accuracy directly affects the smooth operation of driverless vehicles.Therefore,the path planning and tracking control of driverless vehicles are studied,including the following aspects:A path planning method based on improved artificial potential field method is proposed for driverless vehicles under the condition of lane change and obstacle avoidance.In order to solve the problem of unreachable target and local optimum of traditional artificial potential field method,the repulsive potential field function of obstacle is changed.In order to keep the controlled vehicle in the lane after lane change,a new road potential field is established.In order to meet the conditions of lateral driving,B-spline curve is used to generate path cluster,and the optimal path is screened.Under different obstacle conditions,the path planning algorithm is verified by simulation experiment,and the simulation results show that the planned path has good smoothness and safety.Based on the idea of hierarchical control,a longitudinal velocity tracking controller is established.The upper controller uses the MPC control algorithm to calculate the expected acceleration of the vehicle.Based on reasonable braking/drive switching rules,the lower controller obtains specific throttle opening and braking pressure signals through the longitudinal inverse dynamics model and the expected acceleration output of the upper controller.Under the conditions of different speed changes,simulation experiments are carried out.The simulation results show that the speed tracking controller has good accuracy,and can ensure the stability and safety of the vehicle when driving.Based on LQR control algorithm,a lateral path tracking controller is established.Based on the vehicle dynamics model,a lateral path tracking model with lateral error and its rate of change,course error and its rate of change as system state variables is constructed,and a discrete LQR controller with front wheel angle compensation module is constructed..The simulation experiments are carried out under different speeds with double line shifting as the test condition.The simulation results show that the path tracking controller has good accuracy and stability.Finally,a horizontal and vertical integrated tracking control model is built,which is used to track and control the path planned by the improved artificial potential field method.Simulation experiments are carried out by Car Sim/Simulink.The simulation results showed that the horizontal and vertical integrated tracking control could stably follow the planned path,and the errors are all within a reasonable range.The path planning algorithm and tracking control model have good robustness.