Innovating Urban Mobility with Digital Twins: Data-Driven Traffic Visualization and Testing

This paper proposes an urban and mobility-based Digital Twin that provides the representation of an urban scenario with both real and simulated mobility data of vehicles, 2-wheelers and people. The platform integrates real-time data from the Aveiro Tech City Living Lab (ATCLL) with 2D and 3D visualizations using SUMO and CARLA, respectively, enabling detailed traffic analysis and management. Key functionalities include the synchronization of real-world sensor data with simulated environments, providing accurate and dynamic traffic visualizations. The platform also supports the change and blocking of intersections, roundabouts and lanes, being able to test scenarios when the road conditions change, anticipating the impact of those changes in the urban mobility. The platform results show that they can help decision makers to optimize the traffic flow and anticipate changes in the roads, providing information on the travel times, CO2 emissions and congestion in the roads.

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Publication Details

Published
2025-03-24
DOI
https://doi.org/10.1109/wcnc61545.2025.10978641
Citations
1
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
1.01
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Innovating Urban Mobility with Digital Twins: Data-Driven Traffic Visualization and Testing

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Traffic Prediction and Management Techniques
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article

Innovating Urban Mobility with Digital Twins: Data-Driven Traffic Visualization and Testing

Susana Sargento, Pedro Rito, J. Mendes, Filipe Cabral Pinto, Rafaela Dias, Duarte Raposo, Mariana Perna, Bernardo Pinto, Filipe Obrist
article en
1 citations

Abstract

This paper proposes an urban and mobility-based Digital Twin that provides the representation of an urban scenario with both real and simulated mobility data of vehicles, 2-wheelers and people. The platform integrates real-time data from the Aveiro Tech City Living Lab (ATCLL) with 2D and 3D visualizations using SUMO and CARLA, respectively, enabling detailed traffic analysis and management. Key functionalities include the synchronization of real-world sensor data with simulated environments, providing accurate and dynamic traffic visualizations. The platform also supports the change and blocking of intersections, roundabouts and lanes, being able to test scenarios when the road conditions change, anticipating the impact of those changes in the urban mobility. The platform results show that they can help decision makers to optimize the traffic flow and anticipate changes in the roads, providing information on the travel times, CO2 emissions and congestion in the roads.

Instituto de Telecomunicações (PT), University of Aveiro (PT), Altice Portugal (Portugal) (PT)
Sustainable cities and communities
Openalex Percentile: Top 25%
Traffic Prediction and Management Techniques
1.01
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