Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps

Abstract In this paper, we investigate the day-to-day regularity of urban congestion patterns. We first partition link speed data every 10 min into 3D clusters that propose a parsimonious sketch of the congestion pulse. We then gather days with similar patterns and use consensus clustering methods t...

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Autores principales:	Clélia Lopez, Ludovic Leclercq, Panchamy Krishnakumari, Nicolas Chiabaut, Hans van Lint
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0a830179f3ff4ff08f3720637172b061
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id	oai:doaj.org-article:0a830179f3ff4ff08f3720637172b061
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spelling	oai:doaj.org-article:0a830179f3ff4ff08f3720637172b0612021-12-02T15:05:37ZRevealing the day-to-day regularity of urban congestion patterns with 3D speed maps10.1038/s41598-017-14237-82045-2322https://doaj.org/article/0a830179f3ff4ff08f3720637172b0612017-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-14237-8https://doaj.org/toc/2045-2322Abstract In this paper, we investigate the day-to-day regularity of urban congestion patterns. We first partition link speed data every 10 min into 3D clusters that propose a parsimonious sketch of the congestion pulse. We then gather days with similar patterns and use consensus clustering methods to produce a unique global pattern that fits multiple days, uncovering the day-to-day regularity. We show that the network of Amsterdam over 35 days can be synthesized into only 4 consensual 3D speed maps with 9 clusters. This paves the way for a cutting-edge systematic method for travel time predictions in cities. By matching the current observation to historical consensual 3D speed maps, we design an efficient real-time method that successfully predicts 84% trips travel times with an error margin below 25%. The new concept of consensual 3D speed maps allows us to extract the essence out of large amounts of link speed observations and as a result reveals a global and previously mostly hidden picture of traffic dynamics at the whole city scale, which may be more regular and predictable than expected.Clélia LopezLudovic LeclercqPanchamy KrishnakumariNicolas ChiabautHans van LintNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Clélia Lopez Ludovic Leclercq Panchamy Krishnakumari Nicolas Chiabaut Hans van Lint Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
description	Abstract In this paper, we investigate the day-to-day regularity of urban congestion patterns. We first partition link speed data every 10 min into 3D clusters that propose a parsimonious sketch of the congestion pulse. We then gather days with similar patterns and use consensus clustering methods to produce a unique global pattern that fits multiple days, uncovering the day-to-day regularity. We show that the network of Amsterdam over 35 days can be synthesized into only 4 consensual 3D speed maps with 9 clusters. This paves the way for a cutting-edge systematic method for travel time predictions in cities. By matching the current observation to historical consensual 3D speed maps, we design an efficient real-time method that successfully predicts 84% trips travel times with an error margin below 25%. The new concept of consensual 3D speed maps allows us to extract the essence out of large amounts of link speed observations and as a result reveals a global and previously mostly hidden picture of traffic dynamics at the whole city scale, which may be more regular and predictable than expected.
format	article
author	Clélia Lopez Ludovic Leclercq Panchamy Krishnakumari Nicolas Chiabaut Hans van Lint
author_facet	Clélia Lopez Ludovic Leclercq Panchamy Krishnakumari Nicolas Chiabaut Hans van Lint
author_sort	Clélia Lopez
title	Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
title_short	Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
title_full	Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
title_fullStr	Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
title_full_unstemmed	Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
title_sort	revealing the day-to-day regularity of urban congestion patterns with 3d speed maps
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/0a830179f3ff4ff08f3720637172b061
work_keys_str_mv	AT clelialopez revealingthedaytodayregularityofurbancongestionpatternswith3dspeedmaps AT ludovicleclercq revealingthedaytodayregularityofurbancongestionpatternswith3dspeedmaps AT panchamykrishnakumari revealingthedaytodayregularityofurbancongestionpatternswith3dspeedmaps AT nicolaschiabaut revealingthedaytodayregularityofurbancongestionpatternswith3dspeedmaps AT hansvanlint revealingthedaytodayregularityofurbancongestionpatternswith3dspeedmaps
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Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps

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