Smart Corridor+: A Testbed-As-A-Service for Intelligent Transportation Research

Urbanization over the next decade will present many complex challenges to cities. Transportation plays an important role in a city’s ability to address urbanization and create resilient, sustainable, inclusive, and safer cities for all. However, challenges introduced by urbanization will decrease the effectiveness of current transportation methodologies. By utilizing innovations in sensing, computing, and communication along with machine learning and real-time data, intelligent transportation systems (ITS) can advance transportation efficiency and effectiveness. Integrating these technologies into intelligent transportation systems can potentially reduce congestion, pollution, energy consumption, and traffic incidents. This integration is at the forefront of academic and industry research. Although testbeds have been developed for the development, testing, and validation of ITS solutions, existing testbeds focus on narrow aspects of the ITS domain and are unable to support large-scale experimentation and integrations. Additionally, access to resources and data is limited and not remotely accessible to potential researchers. In this paper, we propose a smart city and ITS Testbed-As-A-Service. The testbed is located in downtown Chattanooga, TN, and offers a unified platform for a wide range of ITS applications including connected and autonomous vehicles, wireless communication, cooperative transportation, internet-of-things (IoT), and edge-based AI.

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Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10826138
Citations
1
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.27

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article

Smart Corridor+: A Testbed-As-A-Service for Intelligent Transportation Research

Mina Sartipi, Yasir Hassan, Austin Harris
1 citations
Traffic Prediction and Management Techniques
0.27
article

Smart Corridor+: A Testbed-As-A-Service for Intelligent Transportation Research

Mina Sartipi, Yasir Hassan, Austin Harris
article en
1 citations

Abstract

Urbanization over the next decade will present many complex challenges to cities. Transportation plays an important role in a city’s ability to address urbanization and create resilient, sustainable, inclusive, and safer cities for all. However, challenges introduced by urbanization will decrease the effectiveness of current transportation methodologies. By utilizing innovations in sensing, computing, and communication along with machine learning and real-time data, intelligent transportation systems (ITS) can advance transportation efficiency and effectiveness. Integrating these technologies into intelligent transportation systems can potentially reduce congestion, pollution, energy consumption, and traffic incidents. This integration is at the forefront of academic and industry research. Although testbeds have been developed for the development, testing, and validation of ITS solutions, existing testbeds focus on narrow aspects of the ITS domain and are unable to support large-scale experimentation and integrations. Additionally, access to resources and data is limited and not remotely accessible to potential researchers. In this paper, we propose a smart city and ITS Testbed-As-A-Service. The testbed is located in downtown Chattanooga, TN, and offers a unified platform for a wide range of ITS applications including connected and autonomous vehicles, wireless communication, cooperative transportation, internet-of-things (IoT), and edge-based AI.

University of Tennessee at Chattanooga (US)
National Science Foundation
Industry, innovation and infrastructure
Openalex Percentile: Top 40%
Traffic Prediction and Management Techniques
0.27
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