Lane Aware

Lane-aware systems aim to accurately detect and understand lane markings and their context for applications like autonomous driving and high-definition map creation. Current research focuses on developing robust 3D lane detection models using diverse data sources (images, LiDAR), employing architectures like transformers and graph neural networks to capture spatial and temporal relationships, and leveraging multi-modal fusion techniques to improve accuracy. These advancements are crucial for enhancing the safety and reliability of autonomous vehicles and improving the efficiency of infrastructure management through automated map generation and analysis.