Large scale estimation of arterial traffic and structural analysis of traffic patterns using probe vehicles

Aude Hofleitner 1 Ryan Herring 2 Alexandre Bayen 3 Yufei Han 4 Fabien Moutarde 4 Arnaud De La Fortelle 4, 5
1 EECS - Electrical Engineering and Computer Science [Berkeley]
2 California Center for Innovative Transportation,
3 CEE - Department of Civil and Environmental Engineering [Berkeley]
4 CAOR - Centre de Robotique
5 IMARA - Informatique, Mathématiques et Automatique pour la Route Automatisée
Inria Paris-Rocquencourt
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.
Type de document :
Communication dans un congrès
Transportation Research Board 91st Annual Meeting (TRB'2012), Jan 2012, Washington, United States. 2012
Liste complète des métadonnées

Littérature citée [4 références]  Voir  Masquer  Télécharger
https://hal-mines-paristech.archives-ouvertes.fr/hal-00741497
Contributeur : Fabien Moutarde <>
Soumis le : vendredi 12 octobre 2012 - 23:45:19
Dernière modification le : lundi 12 novembre 2018 - 11:02:33
Document(s) archivé(s) le : samedi 17 décembre 2016 - 00:38:24

Fichier

main_trb2012_Gaussian_NMF.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00741497, version 1

Collections

ENSMP | ENSMP_CAOR | PARISTECH | INRIA | PSL | INSTITUT-TELECOM | INRIA-ROCQ

Citation

Aude Hofleitner, Ryan Herring, Alexandre Bayen, Yufei Han, Fabien Moutarde, et al.. Large scale estimation of arterial traffic and structural analysis of traffic patterns using probe vehicles. Transportation Research Board 91st Annual Meeting (TRB'2012), Jan 2012, Washington, United States. 2012. 〈hal-00741497〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

525

Téléchargements de fichiers

413

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD