Smart Card clustering to extract typical temporal passenger habits in Transit network. Two case studies: Rennes in France and Gatineau in Canada - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Smart Card clustering to extract typical temporal passenger habits in Transit network. Two case studies: Rennes in France and Gatineau in Canada

Résumé

In this paper we will investigate a statistical modeling to perform the clustering of passengers based on their ticketing logs in the public transport. The aim is partition the passengers into groups on the basis of their travel hours. The clustering is proposed to be performed in unsupervised way by using advanced data partitioning tools, that is dedicated Gaussian mixture models. Doing so, we will be able to extract typical patterns describing different types of transport usage, namely sporadic usage, typical home-work commute behavior, scholar usage etc.

Domaines

Sociologie
Fichier principal
Vignette du fichier
doc00027288.pdf (132.63 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01570726 , version 1 (31-07-2017)

Identifiants

  • HAL Id : hal-01570726 , version 1

Citer

Anne Sarah Briand, Etienne Come, Martin Trepanier, Latifa Oukhellou. Smart Card clustering to extract typical temporal passenger habits in Transit network. Two case studies: Rennes in France and Gatineau in Canada. 3rd International Workshop and Symposium: "Research and applications on the use of passive data from public transport", May 2017, Santiago, Chile. ⟨hal-01570726⟩
199 Consultations
183 Téléchargements

Partager

Gmail Facebook X LinkedIn More