Line Crossing Detector System for Real-Time Over-Taking Vehicle Detection

Abstract

This study introduces a novel method for detecting overtaking vehicles by integrating Virtual Line Detection with the YOLOv8n algorithm. The objective is to enhance road safety by accurately identifying and tracking vehicles as they overtake, which is crucial for preventing. The research demonstrates the effectiveness of this approach, achieving a detection accuracy rate of 80.95% using line crossing detection techniques. This high level of accuracy underscores the potential of the system to reliably identify overtaking maneuvers in traffic conditions. Furthermore, this innovative method holds promising implications for enhancing safety riding by providing realtime alerts to drivers and preventing infrastructure loss resulting from traffic incidents. Our findings suggest that integrating advanced detection algorithms like YOLOv8n with virtual line detection can be a viable solution for modern traffic safety challenges.