Combined Control Of Intelligent Vehicle Lateral And Longitudinal Motion

As an important part of intelligent transportation system,intelligent vehicles provide a new way to solve the road traffic problems.The motion control of intelligent vehicle is the premise and foundation of intelligent behavior.Therefore,it is of great significance and application value to study the motion control strategy of intelligent vehicle.In this paper,the intelligent vehicle motion control method is studied,and the lateral and longitudinal motion integrated control system is established.According to the analysis of the control scheme,the decomposition motion control mode is adopted in this paper.The lateral and longitudinal control systems are designed respectively,and coordinating them to construct the combined control framework.Therefore,the vehicle dynamics models for the lateral and longitudinal control systems need to be established respectively.Firstly,the vehicle monorail dynamic model is established,and the "Magic Formula" tire model is used to analyze the tire dynamic characteristics.In order to facilitate the design of the lateral control system,the vehicle dynamics model is simplified based on the small angle assumption and further simplified to get the point mass model.Then,the longitudinal dynamic system is modeled,including vehicle longitudinal dynamic model and power transmission system model.The lateral controller is designed based on model predictive control(MPC)algorithm.According to the vehicle dynamics model,the linear time-varying prediction equation is derived and the predictive control model is established.Particle swarm optimization(PSO)is used to optimize the predictive time domain and control time domain of MPC.The performance of controller is verified under different working conditions through the joint simulation platform of CarSim and Simulink.The simulation results show that the controller has high tracking accuracy,strong robustness and good real-time performance.In order to ensure the safe driving of vehicles in the obstacle environment,the hierarchical control structure is adopted.The upper model predictive path planning controller is designed,and combines with the lower path tracking controller to realize vehicle obstacle avoidance control.The effectiveness of the control system is verified by simulation in the environment with static and dynamic obstacles.The longitudinal control system adopts the hierarchical control structure.According to the multi-objective performance requirements of the vehicle,the speed tracking control method is designed based on the model predictive control.The upper controller calculates the desired acceleration according to the desired speed,and the lower controller coordinates the throttle/brake to achieve the desired acceleration according to the switching logic.Particle swarm optimization is used to optimize the parameters of model predictive controller.The performance of controller is verified by the joint simulation platform under different working conditions.The result indicates show that it is robust and real-time,and can track the desired speed accurately and stably.The longitudinal speed planning module is designed to plan the vehicle reference speed according to the path information and dynamic constraints,and the longitudinal speed is taken as the coupling point to coordinate the lateral and longitudinal control systems to form a comprehensive control framework.Simulation results show that the integrated control system can realize path and speed tracking control simultaneously and meet the requirements of intelligent vehicle motion control.