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Conference papers
Large scale estimation of arterial traffic and structural analysis of traffic patterns using probe vehicles
Abstract : Estimating and analyzing traffi c conditions on large arterial networks is an inherently diffi cult task. The fi rst goal of this article is to demonstrate how arterial tra c conditions can be estimated using sparsely sampled GPS probe vehicle data provided by a small percentage of vehicles. Traffi c signals, stop signs, and other flow inhibitors make estimating arterial traffi c conditions significantly more diffi cult than estimating highway traffi c conditions. To address these challenges, we propose a statistical modeling framework that leverages a large historical database and relies on the fact that tra ffic conditions tend to follow distinct patterns over the course of a week. This model is operational in North California, as part of the Mobile Millennium tra ffic estimation platform. The second goal of the article is to provide a global network-level analysis of tra ffic patterns using matrix factorization and clustering methods. These techniques allow us to characterize spatial tra ffic patterns in the network and to analyze traffi c dynamics at a network scale. We identify tra ffic patterns that indicate intrinsic spatio-temporal characteristics over the entire network and give insight into the traffi c dynamics of an entire city. By integrating our estimation technique with our analysis method, we achieve a general framework for extracting, processing and interpreting traffi c information using GPS probe vehicle data.
Cited literature [4 references]
https://hal-mines-paristech.archives-ouvertes.fr/hal-00741497
Contributor : Fabien Moutarde <>
Submitted on : Friday, October 12, 2012 - 11:45:19 PM
Last modification on : Thursday, February 11, 2021 - 2:58:06 PM
Long-term archiving on: : Saturday, December 17, 2016 - 12:38:24 AM
Contributor : Fabien Moutarde <>
Submitted on : Friday, October 12, 2012 - 11:45:19 PM
Last modification on : Thursday, February 11, 2021 - 2:58:06 PM
Long-term archiving on: : Saturday, December 17, 2016 - 12:38:24 AM
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main_trb2012_Gaussian_NMF.pdf
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