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Communication Dans Un Congrès Année : 2017

Spatio-temporal partitioning of transportation network using travel time data

Résumé

Nowadays, the deployment of sensing technology permits to collect massive 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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Dates et versions

hal-01493425 , version 1 (21-03-2017)

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  • HAL Id : hal-01493425 , version 1

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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. 96th Transportation Research Board Annual Meeting, Jan 2017, WASHINGTON, United States. 14 p. ⟨hal-01493425⟩
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