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Understanding Road Usage Patterns in Urban Areas

In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own...

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Detalles Bibliográficos
Autores principales: Wang, Pu, Hunter, Timothy, Bayen, Alexandre M., Schechtner, Katja, González, Marta C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526957/
https://www.ncbi.nlm.nih.gov/pubmed/23259045
http://dx.doi.org/10.1038/srep01001
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author Wang, Pu
Hunter, Timothy
Bayen, Alexandre M.
Schechtner, Katja
González, Marta C.
author_facet Wang, Pu
Hunter, Timothy
Bayen, Alexandre M.
Schechtner, Katja
González, Marta C.
author_sort Wang, Pu
collection PubMed
description In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a network of road usage by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.
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spelling pubmed-35269572012-12-20 Understanding Road Usage Patterns in Urban Areas Wang, Pu Hunter, Timothy Bayen, Alexandre M. Schechtner, Katja González, Marta C. Sci Rep Article In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a network of road usage by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach. Nature Publishing Group 2012-12-20 /pmc/articles/PMC3526957/ /pubmed/23259045 http://dx.doi.org/10.1038/srep01001 Text en Copyright © 2012, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Article
Wang, Pu
Hunter, Timothy
Bayen, Alexandre M.
Schechtner, Katja
González, Marta C.
Understanding Road Usage Patterns in Urban Areas
title Understanding Road Usage Patterns in Urban Areas
title_full Understanding Road Usage Patterns in Urban Areas
title_fullStr Understanding Road Usage Patterns in Urban Areas
title_full_unstemmed Understanding Road Usage Patterns in Urban Areas
title_short Understanding Road Usage Patterns in Urban Areas
title_sort understanding road usage patterns in urban areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526957/
https://www.ncbi.nlm.nih.gov/pubmed/23259045
http://dx.doi.org/10.1038/srep01001
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