4.7 Article

A digital twin in transportation: Real-time synergy of traffic data streams and simulation for virtualizing motorway dynamics

期刊

ADVANCED ENGINEERING INFORMATICS
卷 55, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.aei.2022.101858

关键词

Digital twin; Microscopic traffic simulation; Real-time Big Data analytics; Calibration; Traffic sensors; Smart roads

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The introduction of digital twins is expected to fundamentally change transportation technology by monitoring the entire lifecycle of the transport system. This article focuses on microscopic motorway simulation with real-time data integration, proposing a paradigm shift in motorway traffic modeling. The simulation results provide a basis for future real-time analysis and predictive analytics in traffic management.
The introduction of digital twins is expected to fundamentally change the technology in transportation systems, as they appear to be a compelling concept for monitoring the entire life cycle of the transport system. The advent of widespread information technology, particularly the availability of real-time traffic data, provides the foun-dation for supplementing predominated (offline) microscopic simulation approaches with actual data to create a detailed real-time digital representation of the physical traffic. However, the use of actual traffic data in real-time motorway analysis has not yet been explored. The reason is that there are no supporting models and the applicability of real-time data in the context of microscopic simulations has yet to be recognized. Thus, this article focuses on microscopic motorway simulation with real-time data integration during system run-time. As a result, we propose a novel paradigm in motorway traffic modeling and demonstrate it using the continuously synchronized digital twin model of the Geneva motorway (DT-GM). We analyze the application of the micro-scopic simulator SUMO in modeling and simulating on-the-fly synchronized digital replicas of real traffic by leveraging fine-grained actual traffic data streams from motorway traffic counters as input to DT-GM. Thus, the detailed methodological process of developing DT-GM is presented, highlighting the calibration features of SUMO that enable (dynamic) continuous calibration of running simulation scenarios. By doing so, the actual traffic data are directly fused into the running DT-GM every minute so that DT-GM is continuously calibrated as the physical equivalent changes. Accordingly, DT-GM raises a technology dimension in motorway traffic simu-lation to the next level by enabling simulation-based control optimization during system run-time that was previously unattainable. It, thus, forms the foundation for further evolution of real-time predictive analytics as support for safety-critical decisions in traffic management. Simulation results provide a solid basis for the future real-time analysis of an extended Swiss motorway network.

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