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Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19
Traffic congestion has been a persistent problem in cities globally. Theoretically, commuting-related congestion can be relieved by promoting working from home (WFH). Amid the COVID-19 pandemic, WFH arrangement has been encouraged or enforced to reduce the spread of the coronavirus. Under these circ...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784440/ https://www.ncbi.nlm.nih.gov/pubmed/35095163 http://dx.doi.org/10.1016/j.cities.2022.103610 |
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author | Loo, Becky P.Y. Huang, Zhiran |
author_facet | Loo, Becky P.Y. Huang, Zhiran |
author_sort | Loo, Becky P.Y. |
collection | PubMed |
description | Traffic congestion has been a persistent problem in cities globally. Theoretically, commuting-related congestion can be relieved by promoting working from home (WFH). Amid the COVID-19 pandemic, WFH arrangement has been encouraged or enforced to reduce the spread of the coronavirus. Under these circumstances, it was reported that traffic congestion has been alleviated in many cities. However, changes in congestion patterns within a city have not been studied in-depth. In this study, we analysed the congestion index (CI) at peak hours, when commuting-related congestion is typically most serious, throughout different waves of the pandemic in Hong Kong. Results show that under WFH arrangement, peak-hour congestion has been alleviated. Within a day, morning peak congestion was more relieved. Spatially, significant drops in CI were found not only in the central business district and urban cores but also in some new town areas. This paper has significant implications for urban planners in creating more sustainable cities that duly consider the commuting needs of residents, and cautions against the optimism that WFH can relieve urban transport problems despite jobs-housing imbalance. While the WFH arrangement has potentials to ease commuting congestion, future e-working and transport measures need to take spatial and temporal dimensions into account. |
format | Online Article Text |
id | pubmed-8784440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87844402022-01-24 Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19 Loo, Becky P.Y. Huang, Zhiran Cities Article Traffic congestion has been a persistent problem in cities globally. Theoretically, commuting-related congestion can be relieved by promoting working from home (WFH). Amid the COVID-19 pandemic, WFH arrangement has been encouraged or enforced to reduce the spread of the coronavirus. Under these circumstances, it was reported that traffic congestion has been alleviated in many cities. However, changes in congestion patterns within a city have not been studied in-depth. In this study, we analysed the congestion index (CI) at peak hours, when commuting-related congestion is typically most serious, throughout different waves of the pandemic in Hong Kong. Results show that under WFH arrangement, peak-hour congestion has been alleviated. Within a day, morning peak congestion was more relieved. Spatially, significant drops in CI were found not only in the central business district and urban cores but also in some new town areas. This paper has significant implications for urban planners in creating more sustainable cities that duly consider the commuting needs of residents, and cautions against the optimism that WFH can relieve urban transport problems despite jobs-housing imbalance. While the WFH arrangement has potentials to ease commuting congestion, future e-working and transport measures need to take spatial and temporal dimensions into account. Elsevier Ltd. 2022-05 2022-01-24 /pmc/articles/PMC8784440/ /pubmed/35095163 http://dx.doi.org/10.1016/j.cities.2022.103610 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Loo, Becky P.Y. Huang, Zhiran Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19 |
title | Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19 |
title_full | Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19 |
title_fullStr | Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19 |
title_full_unstemmed | Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19 |
title_short | Spatio-temporal variations of traffic congestion under work from home (WFH) arrangements: Lessons learned from COVID-19 |
title_sort | spatio-temporal variations of traffic congestion under work from home (wfh) arrangements: lessons learned from covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784440/ https://www.ncbi.nlm.nih.gov/pubmed/35095163 http://dx.doi.org/10.1016/j.cities.2022.103610 |
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