Multi-objective Planning And Tracking Control Of High-speed Lane Changing Trajectory For Intelligent Connected Vehicles

As the development of future automotive technology,automatic driving can effectively reduce safety accidents and improve traffic efficiency,thus comprehensively improving travel experience.Automatic lane changing in high-speed environment is an indispensable link to realize automatic driving.Based on the advantages of intelligent connected vehicles in environmental perception,this paper makes reasonable trajectory planning and accurate tracking for lane changing process,which is of great significance for realizing automatic driving in high-speed environment.Through the analysis of lane changing behavior,the lane changing is divided into three processes: intent generation,condition judgment,operation implementation,and this article selects free lane changing in two scenarios of straight road and curve road as the main research content.In order to avoid collision,a safe distance model under straight road and curve road is established by considering the movement status of surrounding traffic vehicles and self-vehicle during the lane changing process based on V2 V mode.Regarding the safety,comfort and efficiency requirements of lane changing,a priority-based lane changing rules are proposed,which makes a reasonable decision on the automatic lane changing process.In straight lane changing,the boundary conditions are obtained according to the law of longitudinal and lateral motion,and the polynomial functions of different orders are selected to describe the longitudinal and lateral motion respectively,so as to obtain the trajectory equation of lane changing.According to the law of lateral motion in straight lane changing and circular motion,the lane changing trajectory under curved road is established by coordinate transformation.In order to realize the optimal trajectory planning in different environments,a multi-objective function that balances comfort and efficiency is proposed.The V2 V method is used to reasonably evaluate the lane changing space to determine the weight coefficient.Find the extreme point of the objective function in the constraint interval with the golden section method,so as to obtain the optimal trajectory in different traffic environments.Limit the trajectory under two adhesion factors of dry and wet to prevent dangerous conditions such as side slip during the lane changing process.The simulation is compared with the lane changing model in a non-V2 V mode,and the results show that the optimal trajectory through multi-objective planning can adapt to different traffic environments.To realize the tracking control of the lane changing trajectory,the model predictive control method is used to control the vehicle steering to achieve automatic lane changing.First,a threedegree-of-freedom vehicle model and a magic formula tire model are established,and the state space expression of the control system is obtained according to the nonlinear dynamic model.According to the basic principles of model predictive control,the optimal control amount of the system is obtained,and the design of the trajectory tracking controller is completed through the predictive equations and the optimization solution process.The co-simulation environment of Car Sim and Simulink was built.The simulation results showed that the controller could realize the accurate and smooth lane changing process in both the straight road and the curve road scenarios.