Path Tracking Control Algorithm for Unmanned Vehicles based on Improved RRT Algorithm

Abstract

Unmanned vehicles are a very popular research direction now. Based on the improved RRT algorithm, the application of the path tracking control algorithm of unmanned vehicles in real life is discussed in depth, which can be widely used in specific experiments. This paper improves the traditional RRT algorithm and uses the target point as a random point to expand the random tree, which can realize the tracking control technology for the path of the unmanned vehicle, and has certain feasibility for the steering constraint of the unmanned vehicle. This experiment is based on the path tracking control algorithm of unmanned vehicles, and an improved RRT algorithm is proposed for this technology. For the research on path tracking control trajectories of unmanned vehicles, the actual unmanned vehicles can be built according to this algorithm. A model of path deviation. The experimental results show that the trajectory planning of the driverless vehicle path tracking control algorithm is different under the improved RRT algorithm. Compared with the traditional RRT algorithm, the lateral position deviation coefficient increases from the initial fixed gain of 80 to 90 after the experiment. Left and right, and then adjusted between 80 and 100, there was a significant improvement in the quality and speed of path planning for self-driving cars.