High-speed Overtaking Path Planning And Tracking Control Of Autonomous Vehicles

Automatic driving technology is considered to be an important measure to improve traffic safety,but there are still many key technical bottlenecks to be solved.Automatic overtaking involves the longitudinal motion and lateral motion control of vehicles,especially when driving at high speed.It is easy to encounter collision accidents and lateral instability.How to improve the tracking accuracy of high-speed automatic overtaking control and ensure the safety and comfort of the vehicle is the key technology of the automatic driving technology.In this thesis,a new path planning method and tracking control strategy are proposed for the control of high speed overtaking of autonomous vehicles,including:(1)The thesis proposes a method to determine the safe distance of lane change based on different driving styles.Analyzing the driving style by using kmeans clustering algorithm.According to whether the track of different driving styles changes continuously,the starting and ending points of lane change are determined,and the change time is analyzed statistically.According to the time of lane change,the thesis proposes the safe distance of lane change based on different driving styles by using risk factors.(2)A method of overtaking path planning based on the limit safety distance is proposed.The overtaking process is simplified into five stages of lane change and straight-line driving.In the transverse direction,the mixed function model is established and the target function of the lane change is established to optimize the lane change curve.In longitudinal direction,the driving time and longitudinal acceleration of each stage are planned by using the safety distance and speed,so as to ensure that the overtaking vehicles do not collide with the surrounding vehicles in each stage,and at the same time,ensure a certain safe distance.(3)The multi-objective extension cooperative adaptive trajectory tracking model predictive control is proposed.The expected yaw rate is calculated by using the curvature of the path,the time of changing the track and the longitudinal speed.In order to minimize the lateral position deviation,yaw rate tracking error and control increment as the optimization objective,a multi-objective model predictive extension coordination control strategy for automatic vehicle tracking is established by dynamically assigning the trajectory tracking accuracy and the weight coefficient of lateral stability through the extension set correlation function.Finally,a joint simulation platform is built for overtaking path planning based on the limit safety distance and multi-objective extension cooperative adaptive model predictive control,and then the control strategy is simulated and verified.The simulation results show that the proposed path planning strategy and track tracking control strategy can not only ensure the safety of vehicle overtaking on low attachment Road,but also improve the lateral stability and ride comfort of the vehicle,and the comprehensive performance under different working conditions can be better.