Intelligent Vehicle Trajectory Planning And Motion Control Based On Vehicle Information Interaction

As a new technology under the background of scientific and technological revolution,intelligent vehicle is recognized by the world as the direction of technology development and industrialization that can lead to trillions of markets.As a new industry,the market potential and research value of the internet of vehicles are immeasurable.In China,the internet of vehicles has great research value and the potential of market development.The driver's handling characteristics and the information that cannot be detected by traditional intelligent vehicles are of great significance for enriching the control information and realizing safe driving of intelligent vehicles.First,the intelligent vehicle direction control strategy based on the driver model and model predictive control algorithm(Model Predictive Control,MPC)is designed.The model predictive control model,which includes driver's handling characteristics,is established by using the driver's characteristic model and the vehicle kinematics model.At the same time,the driver's characteristic is taken as the state of the controller,and the target function and constraints are designed.The direction control is realized by controlling the front wheel steering angle of the intelligent vehicle.The effectiveness of the algorithm is verified by the simulation test.Then,the linear three degree of freedom vehicle dynamics model is used as the basic vehicle dynamics model.The vehicle information interaction module is used to realize the information interaction between vehicles.The interactive information of the two vehicles is taken as the state of the controller,and a prediction model is established.According to the control target,the objective function and constraints of the controller are designed.The intelligent vehicle direction controller based on vehicle communication is designed to solve the dynamic change of the intelligent vehicle reference trajectory.In view of the dynamic changes of the driving environment and the delay of information interaction,the trajectory prediction model of the mobile obstacle is proposed.The trajectory of the obstacle is predicted and the dynamic solution of the reference trajectory is realized.The effectiveness and robustness of the algorithm are verified by simulation tests under different speed and road adhesion coefficient.Finally,a trajectory replanning motion controller is designed for the lane changing scene of the same lane moving intelligent vehicle with overlapping trajectories.The penalty function is added to the controller,and the local trajectory replanning controller is designed.Using the method of curve fitting,the reference trajectory parameterized output of local reprogramming is realized.The direction control of intelligent vehicle is realized by MPC direction controller.The fuzzy PI method is used to design the longitudinal speed controller of the intelligent vehicle.The integrated direction speed control framework of intelligent vehicle is constructed to realize the integrated control of intelligent vehicle movement.The effectiveness of the algorithm is verified by the simulation test.