Research On Local Motion Planning Method Of Intelligent Vehicle Based On Model Predictive Control

With the improvement of artificial intelligence,communication technology,big data and other technologies,intelligent networked vehicles have become the inevitable trend of the development of the future automobile industry.As an important part of intelligent vehicles,the research on the motion planning technology of intelligent vehicles is of great significance.For autonomous vehicles,the trajectory planned by the trajectory planning module needs to satisfy the environmental constraints,comfort constraints and safety constraints of the trajectory.This requires that the planning system can handle these constraints in a simple way;In addition,selecting complex models can better consider vehicle dynamics characteristics and improve the accuracy of model predictive control algorithms,but the complexity of the problem also increases,How to simplify the optimization problem is also very important.Gauss pseudospectral method is a method that uses numerical method to solve the optimal control problem.First,the optimization problem is converted into a nonlinear programming problem,and then the solution of the optimization problem can be quickly obtained through the iterative solution of the interior point method.In this paper,the model predictive control algorithm is used to build the trajectory planning problem,and the Gauss pseudospectral method is used to solve the optimization problem of each small step;Then the PID and LQR controller is used to track the reference track of the vehicle.The main contents of this paper are as follows:1,This paper introduces and analyzes the different coordinate systems used by the local trajectory planning method,and predicts the vehicle trajectory based on the model-based trajectory prediction method.Firstly,the discrete points of the road reference line are fitted with Bezier curve,and the coordinates of the road point and the track point are transformed according to the fitted road reference line;Under the condition that the operation intention of the vehicle in the future is known,two methods are used to predict the trajectory.The predicted trajectory is used for obstacle avoidance in the trajectory planning module.2,The local motion planning method based on model predictive control is introduced and analyzed.Firstly,the prediction model used in this chapter is introduced.The trajectory planning module takes the time optimization as the objective function,takes the vehicle dynamics constraints,tire force constraints,future vehicle trajectory and the road information constraints to establish the model predictive control problem,in which the geometric model of the vehicle is the elliptical model.When establishing this optimization problem,we transform the optimization problem in the time domain into the optimization problem in the distance domain to directly reflect the surrounding information and road information in the control problem.The Gauss pseudo-spectral method is used to solve the optimization problem in each step.In order to interpolate the state trajectory,the configuration point is selected as the zero point of Legendre polynomial,and the objective function and constraint are also converted to the distance domain.Finally,the optimal control problem of each step is converted into a nonlinear programming problem.By iterating the decision variables of the problem,we can obtain the sequence of trajectory points in a distance domain in the future.3,The track tracking method is introduced and analyzed.First,the tracking control problem is decoupled into the control problem in the horizontal and vertical directions.In the vertical direction,we use the position PID controller and the speed PID controller.LQR controller is used for lateral control,and the vehicle model used by the controller is the vehicle lateral error model.At the same time,in order to eliminate the steadystate error caused by trajectory curvature,we introduce feedforward control.In order to verify the effect of the controller,we designed two trajectory tracking simulation experiments.The final simulation results show that the trajectory tracking controller we designed has good tracking accuracy.4,Based on MATLAB/Simulink-Carsim,three different simulation experiments were designed to verify the correctness and progressiveness of the local motion planning system designed in this paper,which shows that the local motion planning system can meet the requirements of safe and comfortable driving of vehicles.