Smart Mobility in the Cloud: Enabling Real-Time Situational Awareness and Cyber-Physical Control Through a Digital Twin for Traffic

Haowen Xu, Andy Berres, Srikanth B. Yoginath, Harry Sorensen, Phil J. Nugent, Joseph Severino, Sarah A. Tennille, Alex Moore, Wesley Jones, Jibonananda Sanyal

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

This article presents the design, implementation, and use cases of the Chattanooga Digital Twin (CTwin) towards the vision for next-generation smart city applications for urban mobility management. CTwin is an end-to-end web-based platform that incorporates various aspects of the decision-making process for optimizing urban transportation systems in Chattanooga, Tennessee, to reduce traffic congestion, incidents, and vehicle fuel consumption. The platform serves as a cyberinfrastructure to collect and integrate multi-domain urban mobility data from various online repositories and Internet of Things (IoT) sensors, covering multiple urban aspects (e.g., traffic, natural hazards, weather, and safety) that are relevant to urban mobility management. The platform enables advanced capabilities for: (a) real-time situational awareness on traffic and infrastructure conditions on highways and urban roads, (b) cyber-physical control for optimizing traffic signal timing, and (c) interactive visual analytics on big urban mobility data and various metrics for traffic prediction and transportation performance evaluation. The platform is designed using a multi-level componentization paradigm and is implemented using modular and adaptive architecture, rendering it as a generalizable and extendable prototype for other urban management applications. We present several use cases to demonstrate CTwin's core capabilities for supporting decision-making in smart urban mobility management.

Original languageEnglish
Pages (from-to)3145-3156
Number of pages12
JournalIEEE Transactions on Intelligent Transportation Systems
Volume24
Issue number3
DOIs
StatePublished - Mar 1 2023

Funding

This work was supported in part by the United States Department of Energy (U.S. DOE) through UT-Battelle, LLC., under Contract DE-AC05-00OR22725 and in part by the U.S. DOE, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office.

FundersFunder number
U.S. Department of Energy
Wind Energy Technologies Office
UT-BattelleDE-AC05-00OR22725

    Keywords

    • Traffic flow visualization
    • level of detail
    • situational awareness
    • traffic monitoring
    • traffic sensor network
    • urban mobility

    Fingerprint

    Dive into the research topics of 'Smart Mobility in the Cloud: Enabling Real-Time Situational Awareness and Cyber-Physical Control Through a Digital Twin for Traffic'. Together they form a unique fingerprint.

    Cite this