LANE DETECTION USING YOLOV8 FOR AUTONOMOUS DRIVING APPLICATIONS

Lane detection is a critical component of autonomous driving systems and Advanced Driver Assistance Systems (ADAS).This paper presents a real-time lane detection approach using the YOLOv8 deep learning model integrated with computer vision techniques.A rear-view car driving video dataset collected from online sources was used for training and testing the system.The proposed method detects lane boundaries accurately and performs efficiently under various road and lighting conditions.Experimental results show an accuracy of 98.8%, demonstrating the effectiveness of the YOLOv8-based approach for intelligent transportation systems.