Development of origin–destination matrices using mobile phone call data

By Md Shahadat Iqbal, Charisma F. Choudhury, Pu Wang, Marta C. González. 2014

496 citations recorded by the source corpus.

Abstract In this research, we propose a methodology to develop OD matrices using mobile phone Call Detail Records (CDR) and limited traffic counts. CDR, which consist of time stamped tower locations with caller IDs, are analyzed first and trips occurring within certain time windows are used to generate tower-to-tower transient OD matrices for different time periods. These are then associated with corresponding nodes of the traffic network and converted to node-to-node transient OD matrices. The actual OD matrices are derived by scaling up these node-to-node transient OD matrices. An optimization based approach, in conjunction with a microscopic traffic simulation platform, is used to determine the scaling factors that result best matches with the observed traffic counts. The methodology is demonstrated using CDR from 2.87 million users of Dhaka, Bangladesh over a month and traffic counts from 13 key locations over 3 days of that month. The applicability of the methodology is supported by a validation study.

Subfields: Transportation

View Paper: https://www.semanticscholar.org/paper/ee92559e81a47675aefb0251bc8617847e9c4d60

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In Transportation

Citations in the corpus

Inferring Passenger Travel Demand to Improve Urban Mobility in Developing Countries Using Cell Phone Data: A Case Study of Senegal (2016, background): “Despite the positive impacts of both the paratransit and largebus services, there are still unfathomable cases for improving the quality, reliability, accessibility, and coverage of public transport services in developing countries.”
Human mobility: Models and applications (2017, methodology): “The drawback of such approaches are related to their cost to setup, frequency of updates, and that they cover a limited sample of individuals (a few hundreds or thousands of households) [92].”
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2017, methodology): “[27] use CDR data collected in Dhaka, Bangladesh over a month, combined with traffic”
Origin-destination trips by purpose and time of day inferred from mobile phone data (2015, background): “It has been demonstrated that CDR data can be used to infer origin–destination (OD) trips using microsimulation and limited trafﬁc count data (Iqbal et al., 2014).”
The promises of big data and small data for travel behavior (aka human mobility) analysis (2016, methodology): “A more advanced scaling method involves the calculation of the scaling factors together with the traffic assignment step, either iteratively (Ma et al., 2012) or as an optimization problem (Iqbal et al., 2014; Toole et al., 2015).”