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Spatio-temporal partitioning of transportation network using travel time data

Résumé : Nowadays, the deployment of sensing technology permits to collect massive 1 spatio-temporal data in urban cities. These data can provide comprehensive traffic state conditions for an urban network and for a particular day. However, they are often too numerous and too detailed to be of direct use, particularly for applications like delivery tour planning, trip advisors and dynamic route guidance. A rough estimation of travel times and their variability may be sufficient if the information is available at the full city scale. The concept of spatio-temporal speed cluster map is a promising avenue for these applications.
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Journal articles
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https://hal.archives-ouvertes.fr/hal-01804570
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Submitted on : Thursday, May 31, 2018 - 6:10:13 PM
Last modification on : Saturday, January 15, 2022 - 3:51:39 AM
Long-term archiving on: : Saturday, September 1, 2018 - 3:06:03 PM

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Clélia Lopez, Panchamy Krishnakumari, Ludovic Leclercq, Nicolas Chiabaut, Hans van Lint. Spatio-temporal partitioning of transportation network using travel time data. Transportation Research Record, SAGE Journal, 2017, 2623 (2), pp. 98-107. ⟨10.3141/2623-11⟩. ⟨hal-01804570⟩

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