A Novel Approach towards Vehicle Lane Tracing using Auto Vision Techniques

This article introduces a new method for tracking vehicle lanes using sophisticated visual recognition methods. The swift advancement of self-driving technology makes precise lane detection and tracking essential for secure and dependable vehicle navigation. The method suggested involves using different computer vision algorithms such as edge detection, color space transformation, and Hough Transform to precisely locate and follow lane markings under different road conditions. Furthermore, machine learning algorithms are incorporated to improve the system’s ability to manage obstacles like occlusions, changing lighting conditions, and complicated road structures. The system is intended for use in modern autonomous vehicles, operating in real-time. Thorough testing in various settings proves the efficiency of the method, indicating notable enhancements in both accuracy and processing speed when compared to traditional techniques. This research work helps advance safer and more dependable self-driving systems with a new approach for detecting lanes and guiding vehicles.