Visual Path Tracking Control for Park Scene

TL;DR

This paper presents a visual path tracking control method for autonomous parking scenes using a single webcam, combining fuzzy logic and PID control to enhance robustness and accuracy in path following.

Contribution

It introduces a novel visual lateral control approach for park scenes that integrates fuzzy logic with PID control, improving stability and accuracy over traditional methods.

Findings

Accurately follows paths in virtual and real scenes.

Robust performance even at night.

Achieves precise 5-meter turning accuracy.

Abstract

Autonomous driving application is developing towards specific scenes. Park scene has features such as low speed, fixed routes, short connection, less complex traffic, and hence is suitable for bringing autonomous driving technology into reality. This paper targets park scene, and proposes a visual path tracking lateral control method using only one webcam. First, we calculate error of distance and error of angle from camera images, and then use fuzzy logic to fuzzify them into a combined error degree. The PID control algorithm takes it as input, and outputs steering wheel angle control command. Fuzzification could tolerate the error brought by image transformation and lane detection, making PID control more stably. Our experiments in both virtual and real scene show that our method can accurately and robustly follow the path, even at night. Compared with pure pursuit, our method can make 5 meters turning.