Analysis of Network-level Traffic States using Locality Preservative Non-negative Matrix Factorization

Abstract : In this paper, we propose to perform clustering and temporal prediction on network-level traffic states of large-scale traffic networks. Rather than analyzing dynamics of traffic states on individual links, we study overall spatial configurations of traffic states in the whole network and temporal dynamics of global traffic states. With our analysis, we can not only find out typical spatial patterns of global traffic states in daily traffic scenes, but also acquire long-term general predictions of the spatial patterns, which could be used as prior knowledge for modeling temporal behaviors of traffic flows. For this purpose, we use a locality preservation constraints based non-negative matrix factorization (LPNMF) to obtain a low-dimensional representation of network-level traffic states. Clustering and temporal prediction are then performed on the proposed compact representation. Experiments on realistic simulated traffic data are provided to check and illustrate the validity of our proposed approach.
Type de document :
Communication dans un congrès
14th IEEE Intelligent Transport Systems Conference (ITSC'2011), Oct 2011, Washington, United States. 2011
Liste complète des métadonnées

Littérature citée [11 références]  Voir  Masquer  Télécharger

https://hal-mines-paristech.archives-ouvertes.fr/hal-00638207
Contributeur : Fabien Moutarde <>
Soumis le : vendredi 4 novembre 2011 - 11:54:10
Dernière modification le : lundi 12 novembre 2018 - 10:54:47
Document(s) archivé(s) le : dimanche 5 février 2012 - 02:22:04

Fichier

LPNMF-trafficMining_ITSC11_FIN...
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00638207, version 1

Collections

Citation

Yufei Han, Fabien Moutarde. Analysis of Network-level Traffic States using Locality Preservative Non-negative Matrix Factorization. 14th IEEE Intelligent Transport Systems Conference (ITSC'2011), Oct 2011, Washington, United States. 2011. 〈hal-00638207〉

Partager

Métriques

Consultations de la notice

286

Téléchargements de fichiers

190