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Future Transportation
Volume 3
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10.3390/futuretransp3010015
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Article

Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data

by
Manon Seppecher
1,*,
Ludovic Leclercq
1,*,
Angelo Furno
1,
Thamara Vieira da Rocha
2,
Jean-Marc André
2 and
Jérôme Boutang
2
1
LICIT-ECO7 Lab, ENTPE, Université Gustave Eiffel, 69675 Bron, France
2
Citepa, 42 rue de Paradis, 75010 Paris, France
*
Authors to whom correspondence should be addressed.
Future Transp. 2023, 3(1), 254-273; https://doi.org/10.3390/futuretransp3010015
Submission received: 2 December 2022 / Revised: 13 January 2023 / Accepted: 29 January 2023 / Published: 21 February 2023
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Abstract

Over the last two decades, mobile phone data have appeared to be a promising data source for mobility analysis. The structure, abundance, and accessibility of call detail records (CDRs) make them particularly suitable for such use. However, their exploitation is often limited to estimating origin–destination matrices of a restricted part of the population: regular travellers. Although these studies provide valuable information for policymakers, their scope remains limited to this subpopulation analysis. In the present work, we develop a collective mobility reconstruction method adapted to nonregular travellers. The method relies on the notion of the detour ratio, which makes it robust to the lack of mobile phone data as well as its application to large instances (large and dense telecommunication networks). It is used to conduct a longitudinal analysis of the macroscopic mobility patterns in Santiago de Cali, Colombia, thanks to call detail data shared by communication provider CLARO as part of a research project conducted by Citepa, Paris, the Green City Big Data Project.
Keywords: mobile phone data; call detail records; mobility patterns; macroscopic mobility reconstruction; collective mobility reconstruction; total travelled distances mobile phone data; call detail records; mobility patterns; macroscopic mobility reconstruction; collective mobility reconstruction; total travelled distances

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MDPI and ACS Style

Seppecher, M.; Leclercq, L.; Furno, A.; Vieira da Rocha, T.; André, J.-M.; Boutang, J. Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data. Future Transp. 2023, 3, 254-273. https://doi.org/10.3390/futuretransp3010015

AMA Style

Seppecher M, Leclercq L, Furno A, Vieira da Rocha T, André J-M, Boutang J. Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data. Future Transportation. 2023; 3(1):254-273. https://doi.org/10.3390/futuretransp3010015

Chicago/Turabian Style

Seppecher, Manon, Ludovic Leclercq, Angelo Furno, Thamara Vieira da Rocha, Jean-Marc André, and Jérôme Boutang. 2023. "Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data" Future Transportation 3, no. 1: 254-273. https://doi.org/10.3390/futuretransp3010015

APA Style

Seppecher, M., Leclercq, L., Furno, A., Vieira da Rocha, T., André, J.-M., & Boutang, J. (2023). Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data. Future Transportation, 3(1), 254-273. https://doi.org/10.3390/futuretransp3010015

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