Lane Marking

Lane marking analysis focuses on automatically detecting, tracking, and interpreting road markings from various data sources, primarily to improve autonomous vehicle navigation and infrastructure management. Current research emphasizes robust algorithms for detecting lane markings in challenging conditions (e.g., poor lighting, occlusion) using computer vision techniques, including instance segmentation networks and adaptations of the Iterative Closest Point (ICP) algorithm, and leveraging high-definition (HD) maps for improved generalization and localization. These advancements are crucial for enhancing the safety and reliability of autonomous driving systems and for efficient infrastructure monitoring, enabling timely maintenance and improved traffic management.