Simulating Urban Futures: A Digital Twin Framework for Proactive Mobility Management Based on Hybrid Spatio-Temporal Graph Neural Network
The integration of transportation and urban planning is a key challenge for contemporary megacities. A significant problem is the absence of tools capable of quantitatively assessing the future impact of urban development on mobility patterns. For proactive urban mobility management, a framework of a comprehensive Digital Twin (DT) structure is proposed, based on the methodology of a multilayered, dynamic digital representation of the city's public transport system, relying exclusively on open data sources such as GTFS, OpenStreetMap, and OpenWeather. To this end, a