Improvement Of Self-Driving Tourist Vehicle Bottom Control System And Research Of Path Tracking Algorithms

Self-driving technology is one of the hot technologies in the current society.The application of self-driving vehicles can solve two major social problems,environmental pollution and traffic congestion.Among all the technologies of self-driving vehicles,the bottom control technology and path tracking technology are the basic technologies of self-driving vehicles.Self-driving vehicles in specific scenarios such as self-driving express vehicles and self-driving sightseeing vehicles will enter the market earlier than passenger cars because of their relatively simple driving environment and huge market demand.Therefore,the content of this paper is based on an electric sightseeing vehicle platform,under the premise of good design of data fusion system and path planning system,to research and develop vehicle bottom control technology and path tracking technology.Firstly,we need to reform the bottom hardware structure of the electric vehicle,further design the corresponding control algorithm and path tracking algorithm,and then design an autonomous vehicle.The tracking performance of the unmanned sightseeing vehicle is simulated and verified by real vehicle.The main research contents are as follows:(1)Starting from the relevant modification of the bottom control system of the sightseeing car,the lateral control system and the longitudinal control system of the sightseeing car are reformed,including the modification of the acceleration,deceleration and steering system,and the design of the relevant modules of the bottom control system;furthermore,the lateral and vertical motion control of the vehicle is studied,and the specific bottom control algorithm of the sightseeing car is designed.(2)Secondly,this paper analyses and compares two commonly used path tracking control algorithms.The first one is pure tracking control algorithm.The second one is path tracking algorithm based on course prediction.Further,a joint simulation platform is built by using MATLAB/Simulink and Carsim.The simulation results of the two tracking algorithms in low-speed and high-speed scenarios are validated.Compared with the tracking effect of the two algorithms at low speed and high speed,it is preliminarily concluded that the control algorithm based on heading prediction is better than the pure tracking control algorithm.(3)Finally,two kinds of common road conditions in domestic scenic spots are selected,and the self-driving sightseeing vehicle is tested.The tracking results of the two kinds of path tracking algorithms are compared in the experiment,and the third kind of vehicle tracking algorithm based on course prediction with better overall tracking effect is tested,and the tracking effect is also good.Through a series of experiments,the validity and stability of the self-driving sightseeing vehicle system and its control algorithm designed in this paper are verified.