Lane Topology

Lane topology, the arrangement and connectivity of lanes in a road network, is crucial for autonomous driving and intelligent transportation systems. Current research focuses on accurately reconstructing lane topology from various data sources (e.g., aerial imagery, onboard cameras) using deep learning models, often employing graph neural networks, transformers, or multi-layer perceptrons to represent and reason about lane connectivity and relationships with traffic elements. These advancements aim to improve the robustness and reliability of autonomous navigation systems by providing a comprehensive understanding of the drivable environment. The resulting high-fidelity lane topology maps are valuable for applications ranging from route planning and traffic simulation to infrastructure management and safety analysis.