AI RESEARCH
Metropolis-Scale Road Network Datasets for Fine-Grained Urban Traffic Modeling
arXiv CS.LG
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ArXi:2510.02278v2 Announce Type: replace Modeling traffic dynamics is a critical challenge for urban computing, with applications from real-time traffic management to infrastructure planning. However, progress in this area is fundamentally constrained by a lack of large-scale public datasets that capture the subtle properties of real city road networks. Existing benchmarks are often limited by their small scale, reliance on sparse highway traffic sensors, absence of true road connectivity information, and lack of information about road properties. To address this issue, we