In the context of urban transportation systems, digital twins can facilitate real-time data analysis and predictive modeling, allowing city planners and transportation authorities to make informed decisions. By integrating data from various sources—such as traffic sensors, public transit usage, and environmental monitoring—cities can gain a comprehensive understanding of their transportation networks.

Digital twins can also contribute significantly to sustainability efforts: By modeling and analyzing energy consumption patterns and air quality metrics, cities can develop strategies aimed at reducing their carbon footprints. These simulations can identify opportunities for integrating greener transportation options of public transport and micro mobility, into the urban context.

A new study by Eurac Research recently published on the scientific Journal logistics, proposes an innovative approach for creating urban mobility digital twins, focusing on process standardization through a formal language (Specification and Description Language - SDL). This study addresses the conceptual validation phase, which is part of a broader continuous validation process typical of digital twins. This enables the development of digital twins that can be continuously improved through real-time data and used to optimize sustainable mobility scenarios.

Through a collaboration between Eurac Research and Universitat Politècnica de Catalunya (UPC), the researchers developed the conceptual framework of the digital twin and applied it to the city of Bolzano. While UPC provided the methodology for continuous validation and conceptualization through Specification and Description Language, Eurac Research focused on designing the conceptual framework for optimizing urban mobility scenarios, incorporating factors such as traffic congestion, emissions, and energy consumption.

“The primary innovation is the use of Specification and Description Language to formalize the digital twin creation process, establishing a tool- and language-independent framework. This formalization not only allows for adaptation across different urban contexts but also improves communication with stakeholders by providing an accessible, standardized structure that supports easy validation and collaboration, even for non-experts” explains Andrea Grotto first author of this study.

“Since many years we are executing multi objective optimization in the energy modelling field. We do this to identify the technology combination that allows to reach a defined CO2 emission reduction of the energy system at lowest possible system. The present study establishes the framework which should allow in future to transfer this approach in the field of urban mobility: Establish a digital twin of the actual situation and model hundreds of different scenarios that allow to satisfy the actual mobility needs in a more energy efficient and environmentally friendly way with less congestions” explains Wolfram Sparber, Head of the Institute for Renewable Energy and co-author of the study.

In conclusion, the implementation of digital twins in urban transportation systems can represent a transformative shift towards smarter planning processes. By leveraging technology to monitor, simulate, and optimize, city officials can address current urban challenges while laying the groundwork for sustainable city development and a better quality of life for its residents.

Link to the original article

This study was funded by the European Union—NextGenerationEU, in the framework of the consortium iNEST—Interconnected Nord-Est Innovation Ecosystem (PNRR, Missione 4 Componente 2, Investimento 1.5 D.D. 1058 23/06/2022, ECS00000043—Spoke1, RT3, CUP I43C22000250006). The authors thank the Department of Innovation, Research University and Museums of the Autonomous Province of Bozen/Bolzano for covering the Open Access publication costs.