Modelling long-distance route choice using mobile phone call detail record data: a case study of Senegal

Abstract

The growing mobile phone penetration rates have led to the emergence of large-scale call detail records (CDRs) that could serve as a low-cost data source for travel behaviour modelling. However, to the best of our knowledge, there is no previous study evaluating the potential of CDR data in the context of route choice behaviour modelling. Being event-driven, the data are discontinuous and only able to yield partial trajectories, thus presenting serious challenges for route identification. This paper proposes techniques for inferring the users' chosen routes or subsets of their likely routes from partial CDR trajectories, as well as data fusion with external sources of information such as route costs, and then adapts the broad choice framework to the current modelling scenario. The model results show that CDR data can capture the expected travel behaviour and the derived values of travel time are found to be realistic for the study area.

KEYWORDS:

• Route choice behaviour
• broad choice
• mobile phone data
• call detail records
• value of travel time

Acknowledgement

The research in this paper used mobile phone data made available as part of the Orange Data for Development Challenge. We would like to thank the Economic and Social Research Council (ESRC) of the UK and the Institute for Transport Studies, University of Leeds for funding this research. Dr Charisma Choudhury and Professor Stephane Hess also acknowledge the financial support from European Union FP7 (through the Marie Curie Career Integration Grant PCIG14-GA-2013-631782-NGDBM) and the European Research Council (through the Consolidator Grant 615596-DECISIONS) respectively.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 A-GPS data comprises of triangulated mobile phone positions obtained by enhancing standalone GPS data using neighbouring cell tower locations to obtain more accurate and precise positions in poor satellite signal conditions.

2 CDR data reports the time stamped locations of communication events (i.e. voice calls, text messages, and data calls) as well as the details of the request (i.e. the duration and direction).

3 GSM data reports the IDs of all the GSM cells traversed by an active mobile phone at regular time intervals (irrespective of the calling or texting patterns of the users).

Additional information

Funding

This work was supported by FP7 Ideas: European Research Council [grant number 615596]; Economic and Social Research Council [Advanced Quantitative Scholarship].