Understanding Passenger Patterns in Public Transit Through Smart Card and Socioeconomic Data: A case study in Rennes, France - Archive ouverte HAL Access content directly
Conference Papers Year : 2014

Understanding Passenger Patterns in Public Transit Through Smart Card and Socioeconomic Data: A case study in Rennes, France

(1) , (1) , (1) , (1)
1

Abstract

Data collected by Automated Fare Collection (AFC) systems are a valuable resource for studying the travel habits of large city inhabitants. In this paper, we present an approach to mining the temporal behavior of the passengers in a public transportation system in order to extract relevant and easily interpretable clusters. Such classification can be useful for several applications. It may help transport operators better know the demand of their customers and propose targeted incentives, services, and tools accordingly. From a city perspective, this may also help redesign and improve existing transportation policies. To achieve this objective, an additional step of analysis is required and the clustering results need to be contextualized. The spatial location of the different types of passengers is then of great interest. We propose a first step in this direction through a rough estimation of the regular passengers' 'residence' location and the analysis of socioeconomic information available at a fine-grained spatial level. The approach is applied on a real dataset from the metropolitan area of Rennes (France) with four weeks of smart card data containing trips made by both bus and subway.
Not file

Dates and versions

hal-01053794 , version 1 (01-08-2014)

Identifiers

  • HAL Id : hal-01053794 , version 1

Cite

Mohamed Khalil El Mahrsi, Etienne Come, Johanna Baro, Latifa Oukhellou. Understanding Passenger Patterns in Public Transit Through Smart Card and Socioeconomic Data: A case study in Rennes, France. ACM SIGKDD Workshop on Urban Computing, Aug 2014, France. 9p. ⟨hal-01053794⟩
336 View
0 Download

Share

Gmail Facebook Twitter LinkedIn More