Correction: Characterizing multicity urban traffic conditions using crowdsourced data

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Abstract

There are errors in the Author Contributions. The correct contributions are: Conceptualization: DJN SC NS VD. Data curation: DJN FG SC NS. Formal Analysis: DJN FG SC NS. Investigation: DJN FG SC VD. Methodology: DJN SC VD. Resources: VD. Supervision: VD. Validation: DJN SC. Writing–original draft: DJN NS. Writing–review & editing: DJN SC NS.

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Characterizing multicity urban traffic conditions using crowdsourced data

Divya Jayakumar Nair, Flavien Gilles, Sai Chand … (2019)

Road traffic congestion continues to manifest and propagate in cities around the world. The recent technological advancements in intelligent traveler information have a strong influence on the route choice behavior of drivers by enabling them to be more flexible in selecting their routes. Measuring traffic congestion in a city, understanding its spatial dispersion, and investigating whether the congestion patterns are stable (temporally, such as on a day-to-day basis) are critical to developing effective traffic management strategies. In this study, with the help of Google Maps API, we gather traffic speed data of 29 cities across the world over a 40-day period. We present generalized congestion and network stability metrics to compare congestion levels between these cities. We find that (a) traffic congestion is related to macroeconomic characteristics such as per capita income and population density of these cities, (b) congestion patterns are mostly stable on a day-to-day basis, and (c) the rate of spatial dispersion of congestion is smaller in congested cities, i.e. the spatial heterogeneity is less sensitive to increase in delays. This study compares the traffic conditions across global cities on a common datum using crowdsourced data which is becoming readily available for research purposes. This information can potentially assist practitioners to tailor macroscopic network congestion and reliability management policies. The comparison of different cities can also lead to benchmarking and standardization of the policies that have been used to date.

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Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 16 April 2019

Publication date Collection: 2019

Publication date PMC-release: 16 April 2019

Volume: 14

Issue: 4

Electronic Location Identifier: e0215728

Article

Publisher ID: PONE-D-19-10169

DOI: 10.1371/journal.pone.0215728

PMC ID: 6467445

PubMed ID: 30990856

SO-VID: 635111e8-bcb1-4d5e-999b-8d140956ff5c

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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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