Intelligent Vehicle Platoon Lane-Changing Trajectory Planning And Tracking Control Method

The development of intelligent driving technology facilitates people’s lives,but it also brings new problems such as traffic safety,energy consumption,and environmental pollution.Intelligent vehicle platoon provides solutions to these problems.In view of the problems in the three directions of intelligent vehicle platoon model construction,trajectory planning and tracking control in lane changing scenarios,this paper proposes solutions respectively.The main contents are as follows:(1)Aiming at the interference caused by the parameters in the environment that are difficult to calibrate in advance to the intelligent vehicle platoon,an intelligent vehicle platoon model construction method based on the online sequential extreme learning machine is proposed.Due to the difficulty of pre-calibrating the air resistance coefficient and rolling friction coefficient in the environment of intelligent vehicle platooning,an intelligent vehicle dynamics model based on uncertain parameters is constructed,and the environmental parameters are identified by the online sequential extreme learning machine algorithm,which improves the adaptability of the vehicle model to the environment.Give that the lanechanging driving scenario,the intelligent vehicle dynamics model is converted into the Frenet coordinate system,and the intelligent vehicle platoon error model is constructed.The experimental results show that the proposed intelligent vehicle platoon model has high accuracy.(2)Aiming at the problem of insufficient flexibility of the centralized vehicle platoon trajectory planning method,a lane-changing trajectory planning method for intelligent vehicle platoon based on the improved artificial hummingbird algorithm is designed.According to the motion state and trajectory of the preceding vehicle,the planning termination point of the following vehicle is constrained,the quintic polynomial model is used to generate the trajectory cluster.The multi-objective optimization function is constructed based on the state of the vehicle,the initialization operation of the artificial hummingbird algorithm is improved by the Monte Carlo method,and use the improved artificial hummingbird algorithm to select the optimal trajectory of the vehicle.The simulation results show that the proposed trajectory planning method can solve the trajectory planning problem in synchronous and distributed lane changing scenarios,the planned trajectory has high smoothness,and the calculation time will not increase with the platoon size.(3)Aiming at the problem that the traditional control method cannot guarantee the rapid convergence of the lateral and longitudinal errors of the platoon,an intelligent vehicle platoon lane-changing trajectory tracking control method based on adaptive sliding mode is designed.Based on the intelligent vehicle platoon model and expected motion trajectory,a platoon distributed finite-time adaptive sliding mode tracking control framework is designed.Considering the finite time convergence of the system sliding mode,the integral terminal sliding mode surface is designed,and an adaptive power integral reaching law is proposed for the finite time reachability of the system reaching mode.Then a distributed finite-time adaptive sliding mode tracking controller for the vehicle platoon is designed,and a Lyapunov function is constructed to analyze the finite-time stability and string stability of the system.The simulation experiment based on Carsim/Simulink is carried out,and it is proved that the proposed control method can ensure the stable driving of the intelligent vehicle platoon and the errors of platoon can converge quickly during the driving process.