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A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)

Abstract

Spatiotemporal data, and more specifically origin–destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes. Traditionally, high-cost and hard-to-update household travel surveys are used to produce large-scale origin–destination flow information of individuals’ whereabouts. In this paper, we propose a methodology to estimate origin–destination (O–D) matrices based on passively-collected cellular network signalling data of millions of anonymous mobile phone users in the Rhône-Alpes region, France. Unlike Call Detail Record (CDR) data which rely only on phone usage, signalling data include all network-based records providing higher spatiotemporal granularity. The explored dataset, which consists of time-stamped traces from 2G and 3G cellular networks with users’ unique identifier and cell tower locations, is used to first analyse the cell phone activity degree indicators of each user in order to qualify the mobility information involved in these records. These indicators serve as filtering criteria to identify users whose device transactions are sufficiently distributed over the analysed period to allow studying their mobility. Trips are then extracted from the spatiotemporal traces of users for whom the home location could be detected. Trips have been derived based on a minimum stationary time assumption that enables to determine activity (stop) zones for each user. As a large, but still partial, fraction of the population is observed, scaling is required to obtain an O–D matrix for the full population. We propose a method to perform this scaling and we show that signalling data-based O–D matrix carries similar estimations as those that can be obtained via travel surveys.

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Notes

  1. 1.

    Global System for Mobile communications.

  2. 2.

    Universal Mobile Telecommunication System.

  3. 3.

    A “Location Area” is a set of cells (antennas) that are grouped together to optimise signalling.

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Acknowledgements

MF’s Ph.D. is funded by Orange. The authors would like to thank Orange for giving them access to the mobile phone data collected in the Rhône-Alpes region and Region Auvergne Rhône-Alpes for making the EDR data available. This work has been also supported by the French ANR project, PROMENADE, grant number ANR-18-CE22-0008. The authors are grateful for the comments by the anonymous reviewers that greatly improved the paper. The authors alone are responsible for the contents of this paper.

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MF: Literature search and review, study conception and design, draft manuscript preparation. MF, TB, ZS, PB, AF and SG: Analysis and interpretation of results, manuscript editing and review.

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Correspondence to Mariem Fekih.

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Fekih, M., Bellemans, T., Smoreda, Z. et al. A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France). Transportation 48, 1671–1702 (2021). https://doi.org/10.1007/s11116-020-10108-w

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Keywords

  • Passive cellular signalling data
  • Big data analysis
  • Travel survey
  • Home detection
  • Trip extraction
  • Origin–destination matrix