Citation

Larijani AN, Olteanu-Raimond AM, Perret J, Brédif M, Ziemlicki C. Transp. Res. Proc. 2015; 6: 64-78.

Copyright

(Copyright © 2015, Elsevier Publications)

DOI

10.1016/j.trpro.2015.03.006

PMID

unavailable

Abstract

This paper is an output of a French national project called iSpace&Time aiming to provide a 4 dimensional platform of an urban dynamics. In order to express the urban traffic, we took an advantage of the mobile phone data to investigate the behavior of the origin destination flow within the Paris and its suburb aiming to explore the different mode of the transportation. Indeed the spatiotemporal heterogeneities of mobile phone data make the task of mode of transportation separation very challenging, sometimes even impossible. Thus, by exploring the OD matrix in order to revealing any probable continues trends or any dominant trace of the flow stating a specific mode of transportation, the commuter trains happened to be somehow detectable. Then an individual-based step-by-step approach is proposed to estimate mode of transportation from mobile phone data. Analyzing the individual trajectory, the decision is given to a segment level with respect to different measures. An early promising outcome consists of detection of the segments in which people would take the metro.

Language: en

Keywords

mobile phone data; origin-destination matrix; smart data processing; transportation mode