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

Karlson Hargroves; Daena Ho; Daniel Conley; Peter Newman

doi:doi:10.11648/j.ijtet.20210703.11

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

Karlson Hargroves, Daena Ho, Daniel Conley, Peter Newman

Published in International Journal of Transportation Engineering and Technology (Volume 7, Issue 3)

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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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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TY  - JOUR
T1  - How Can “Big Data” Be Harnessed to Enhance Congestion Management
AU  - Karlson Hargroves
AU  - Daena Ho
AU  - Daniel Conley
AU  - Peter Newman
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
SP  - 60
EP  - 67
PB  - Science Publishing Group
SN  - 2575-1751
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

Karlson Hargroves

Curtin University Sustainability Policy Institute, Curtin University, Perth, Australia
Daena Ho

Curtin University Sustainability Policy Institute, Curtin University, Perth, Australia
Daniel Conley

Curtin University Sustainability Policy Institute, Curtin University, Perth, Australia
Peter Newman

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

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Plain Text BibTeX RIS

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

Copy | Download

@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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TY  - JOUR
T1  - How Can “Big Data” Be Harnessed to Enhance Congestion Management
AU  - Karlson Hargroves
AU  - Daena Ho
AU  - Daniel Conley
AU  - Peter Newman
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
SP  - 60
EP  - 67
PB  - Science Publishing Group
SN  - 2575-1751
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  -

Copy | Download