Development of a Connected Corridor Real-Time Data-Driven Traffic Digital Twin Simulation Model

Abhilasha J. Saroj; Somdut Roy; Angshuman Guin; Michael Hunter

doi:10.1061/JTEPBS.0000599

Development of a Connected Corridor Real-Time Data-Driven Traffic Digital Twin Simulation Model

Abhilasha J. Saroj, Somdut Roy, Angshuman Guin, Michael Hunter

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

Smart cities - being equipped with connected infrastructure - receive significant real-time traffic data. In this paper, a data-driven connected corridor traffic simulation model, i.e., a digital twin, is developed that leverages real-time data streams to model the current traffic state and provide dynamic feedback on traffic and environmental performance measures, e.g., travel time, speed, energy consumption, and vehicular emissions. The developed digital twin model architecture uses real-time 6-min volume aggregate data and 0.1 Hz to 10 Hz signal indication data as input to simulate the connected corridor using a traffic modeling software microscopic simulation. Dynamic data retrieval and transfer from the simulation model are enabled using the software's COM feature and a Flask web server. The robustness and feasibility of the digital twin architecture and the generated performance measure reasonableness are demonstrated on a smart corridor test bed. Such a model can be used to monitor and provide insights on the impacts of intelligent transportation system technologies on connected corridor traffic and environmental performance.

Original language	English
Article number	04021096
Journal	Journal of Transportation Engineering Part A: Systems
Volume	147
Issue number	12
DOIs	https://doi.org/10.1061/JTEPBS.0000599
State	Published - Dec 1 2021
Externally published	Yes

Funding

The information, data, or work presented herein was funded in part by the City of Atlanta (CoA) and in part by the National Center for Sustainable Transportation (NCST) Dissertation Grant. The authors thank CoA for support of this research under Research Project FC-9930 Smart Cities Traffic Congestion Mitigation Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors. This paper does not constitute a standard, specification, or regulation.

Funders	Funder number
City of Atlanta
National Center for Sustainable Transportation	FC-9930

Keywords

Connected corridors
Digital twin
Intelligent transportation system (ITS)
Real-time simulation
Smart city
Traffic simulation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1061/JTEPBS.0000599

Cite this

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title = "Development of a Connected Corridor Real-Time Data-Driven Traffic Digital Twin Simulation Model",

abstract = "Smart cities - being equipped with connected infrastructure - receive significant real-time traffic data. In this paper, a data-driven connected corridor traffic simulation model, i.e., a digital twin, is developed that leverages real-time data streams to model the current traffic state and provide dynamic feedback on traffic and environmental performance measures, e.g., travel time, speed, energy consumption, and vehicular emissions. The developed digital twin model architecture uses real-time 6-min volume aggregate data and 0.1 Hz to 10 Hz signal indication data as input to simulate the connected corridor using a traffic modeling software microscopic simulation. Dynamic data retrieval and transfer from the simulation model are enabled using the software's COM feature and a Flask web server. The robustness and feasibility of the digital twin architecture and the generated performance measure reasonableness are demonstrated on a smart corridor test bed. Such a model can be used to monitor and provide insights on the impacts of intelligent transportation system technologies on connected corridor traffic and environmental performance.",

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Development of a Connected Corridor Real-Time Data-Driven Traffic Digital Twin Simulation Model

Abstract

Funding

Keywords

UN SDGs

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