Research On Local Trajectory Planning Method And Tracking Control Of Smart Car Under Typical Working Conditions

Intelligent vehicles are the development direction of the automobile industry in the new era.They will play a vital role in solving traffic accidents and alleviating traffic congestion.Autonomous driving is an advanced stage in the development of intelligent vehicles,and local trajectory planning and tracking control issues,as the key technologies of automatic driving,are important links to improve the level of intelligence.The trajectory includes the driving path and the driving speed.Solving the trajectory directly has problems such as high dimensionality and difficulty.Therefore,this article proposes a strategy for solving the path and speed to generate the trajectory separately for the trajectory planning problem of autonomous vehicles,and then design the horizontal and vertical Controller,verify the feasibility of the planned trajectory,and finally build a joint simulation platform to verify the algorithm.The main research content of this paper is the following parts:First,in an environment with static obstacles,the sampling-based RRT algorithm is improved to address the shortcomings of the sampling-based RRT algorithm.A biased sampling strategy and a node expansion strategy based on corner constraints are proposed to improve the convergence speed of the basic RRT algorithm and the smoothness of the path.The numerical optimization method optimizes the initial path to obtain a smoother and safer path.At the same time,a scene was built in Matlab to verify the performance of the improved algorithm.Then in an environment with moving obstacles,the ST state space is used to convert the speed planning problem into a path search problem,and a path search strategy based on dynamic planning is proposed to obtain the discrete optimal path.At the same time,a fifth-order polynomial is used to simulate discrete points.Together,the continuous optimal solution is obtained by establishing the objective function and constraint conditions to solve the fifth-order polynomial coefficients.Set up a scene in Matlab to verify the performance of the speed planning algorithm.Secondly,to verify the feasibility of the planned trajectory,an LMPC controller was built based on the model prediction theory to control the lateral position of the vehicle,and to constrain the tire slip angle and the front wheel angle to meet the linearization conditions.Based on PID control theory,a PID controller is built to control the longitudinal speed of the vehicle,and at the same time,the switching logic of driving and braking is formulated.Finally,a joint simulation platform based on matlab/simulink and carsim was built,and typical working conditions with static and moving obstacles were set under the structured road to verify the performance of the trajectory planning algorithm and the control algorithm.