Learning Effective Road Network Representation with Hierarchical Graph Neural Networks
Ning Wu, Xin Zhao, Jingyuan Wang, Dayan Pan
Abstract
Road network is the core component of urban transportation, and it is widely useful in various traffic-related systems and applications. Due to its important role, it is essential to develop general, effective, and robust road network representation models. Although several efforts have been made in this direction, they cannot fully capture the complex characteristics of road networks.
Topics & Concepts
Computer scienceRepresentation (politics)Artificial neural networkComponent (thermodynamics)GraphArtificial intelligenceCore (optical fiber)Theoretical computer scienceDistributed computingMachine learningTelecommunicationsPolitical scienceLawPoliticsPhysicsThermodynamicsAutomated Road and Building ExtractionData Management and AlgorithmsTraffic Prediction and Management Techniques