Digital Twins for Urban Mobility

Abstract

Urban Digital Twins (DTs) can help tackle the challenges of planning, monitoring, and managing modern cities. Existing mobility systems are already inadequate, yet urbanization and population growth will increase mobility demand still further. For this reason, urban mobility planning can benefit from DTs producing new knowledge executing automatically complex functions based on real-time data. The paper describes two different DTs for urban mobility and their implementation. The first one is the Traffic and Air Quality DT (TAQ) which investigates the relationship between traffic flows and air quality conditions through a chain of simulation models. The second DT is a multi-layered Graph-Based Multi-Modal Mobility (GBMMM) DT to study the interaction between different transport modes.