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How Can “Big Data” Be Harnessed to Enhance Congestion Management

Received: 17 June 2021     Accepted: 14 July 2021     Published: 29 July 2021
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Abstract

Traffic congestion is a key issue facing transport planners and managers around the world with many now asking if there are any promising technologies offering new solutions. In the US, the cost of congestion was $121 billion in 2012 and in 2015 alone Australia’s capital cities were estimated to have a combined congestion cost of $16 billion, expected increase to $37 billion by 2030. With the rapidly growing availability of data and the ability to analyse large data sets this paper investigates the question “What role can 'Big Data' play to assist with congestion management?” There is great interest and hype around 'Big Data' and this paper provides a summary of an investigation into its value to assist in relieving congestion. The paper explores the emerging types of large data sets, considers how data will be sourced and shared by vehicles and transport infrastructure in the future, ad explores some of the associated challenges. Despite the opportunities of Big Data not being fully realised it is already clear that it presents a significant tool for transport planners and managers around the world to assist in managing congestion. The research is based on research undertaken with the Sustainable Built Environment National Research Centre (SBEnrc).

Published in International Journal of Transportation Engineering and Technology (Volume 7, Issue 3)
DOI 10.11648/j.ijtet.20210703.11
Page(s) 60-67
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Big Data, Predictive Congestion Management, Technology Enabled Transport

References
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Cite This Article
  • APA Style

    Karlson Hargroves, Daena Ho, Daniel Conley, Peter Newman. (2021). How Can “Big Data” Be Harnessed to Enhance Congestion Management. International Journal of Transportation Engineering and Technology, 7(3), 60-67. https://doi.org/10.11648/j.ijtet.20210703.11

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    ACS Style

    Karlson Hargroves; Daena Ho; Daniel Conley; Peter Newman. How Can “Big Data” Be Harnessed to Enhance Congestion Management. Int. J. Transp. Eng. Technol. 2021, 7(3), 60-67. doi: 10.11648/j.ijtet.20210703.11

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    AMA Style

    Karlson Hargroves, Daena Ho, Daniel Conley, Peter Newman. How Can “Big Data” Be Harnessed to Enhance Congestion Management. Int J Transp Eng Technol. 2021;7(3):60-67. doi: 10.11648/j.ijtet.20210703.11

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  • @article{10.11648/j.ijtet.20210703.11,
      author = {Karlson Hargroves and Daena Ho and Daniel Conley and Peter Newman},
      title = {How Can “Big Data” Be Harnessed to Enhance Congestion Management},
      journal = {International Journal of Transportation Engineering and Technology},
      volume = {7},
      number = {3},
      pages = {60-67},
      doi = {10.11648/j.ijtet.20210703.11},
      url = {https://doi.org/10.11648/j.ijtet.20210703.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijtet.20210703.11},
      abstract = {Traffic congestion is a key issue facing transport planners and managers around the world with many now asking if there are any promising technologies offering new solutions. In the US, the cost of congestion was $121 billion in 2012 and in 2015 alone Australia’s capital cities were estimated to have a combined congestion cost of $16 billion, expected increase to $37 billion by 2030. With the rapidly growing availability of data and the ability to analyse large data sets this paper investigates the question “What role can 'Big Data' play to assist with congestion management?” There is great interest and hype around 'Big Data' and this paper provides a summary of an investigation into its value to assist in relieving congestion. The paper explores the emerging types of large data sets, considers how data will be sourced and shared by vehicles and transport infrastructure in the future, ad explores some of the associated challenges. Despite the opportunities of Big Data not being fully realised it is already clear that it presents a significant tool for transport planners and managers around the world to assist in managing congestion. The research is based on research undertaken with the Sustainable Built Environment National Research Centre (SBEnrc).},
     year = {2021}
    }
    

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    T1  - How Can “Big Data” Be Harnessed to Enhance Congestion Management
    AU  - Karlson Hargroves
    AU  - Daena Ho
    AU  - Daniel Conley
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    Y1  - 2021/07/29
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ijtet.20210703.11
    DO  - 10.11648/j.ijtet.20210703.11
    T2  - International Journal of Transportation Engineering and Technology
    JF  - International Journal of Transportation Engineering and Technology
    JO  - International Journal of Transportation Engineering and Technology
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.ijtet.20210703.11
    AB  - Traffic congestion is a key issue facing transport planners and managers around the world with many now asking if there are any promising technologies offering new solutions. In the US, the cost of congestion was $121 billion in 2012 and in 2015 alone Australia’s capital cities were estimated to have a combined congestion cost of $16 billion, expected increase to $37 billion by 2030. With the rapidly growing availability of data and the ability to analyse large data sets this paper investigates the question “What role can 'Big Data' play to assist with congestion management?” There is great interest and hype around 'Big Data' and this paper provides a summary of an investigation into its value to assist in relieving congestion. The paper explores the emerging types of large data sets, considers how data will be sourced and shared by vehicles and transport infrastructure in the future, ad explores some of the associated challenges. Despite the opportunities of Big Data not being fully realised it is already clear that it presents a significant tool for transport planners and managers around the world to assist in managing congestion. The research is based on research undertaken with the Sustainable Built Environment National Research Centre (SBEnrc).
    VL  - 7
    IS  - 3
    ER  - 

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Author Information
  • Curtin University Sustainability Policy Institute, Curtin University, Perth, Australia

  • Curtin University Sustainability Policy Institute, Curtin University, Perth, Australia

  • Curtin University Sustainability Policy Institute, Curtin University, Perth, Australia

  • Curtin University Sustainability Policy Institute, Curtin University, Perth, Australia

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