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This case study demonstrates a digital twin pipeline for public transport, highlighting its potential for improving urban mobility.
Digital Twins (DTs) offer a wide range of functionalities including retrospective analyses of past conditions, real-time monitoring and control, as well as the evaluation of future scenarios. These capabilities make DTs a valuable tool in the Public Transport (PT) domain. To enable the functionalities demanded by traffic planners and operators, DTs rely on the integration of aggregated and disaggregated data from real-world sources and simulations. Informative visualizations of these data sources within the street network, combined with 3D representations of the built environment, provide the necessary contextualization to facilitate decision-making. However, since DTs integrate this large set of different components, their development is typically time- and resource-intensive which represents a barrier for their adoption. To make DTs more widely accessible and promote their use in the PT field, we propose and implement a DT development pipeline that integrates real-world data collection and processing, simulation, and 3D visualization in a unified framework. The pipeline is based on open data and open source software to enable the implementation of PT DTs with low barriers while allowing for extensibility to other urban-related applications. We demonstrate the DT’s functionalities with a prototypical implementation for the region of Kista in Stockholm, and discuss the potential as well as the limitations of PT DTs for practical use cases from a conceptual perspective.
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Jostmann et al. (2026) studied this question.
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