Deriving origin destination data from a mobile phone network

By N. Caceres, J. Wideberg, F. Benitez. 2007

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Development of origin–destination matrices using mobile phone call data (2014, methodology): “(35) use a GSM network simulator 85 to simulate the detailed movements of phones that are turned on.”
Human mobility: Models and applications (2017, background): “Consequently, to circumvent these difficulties, a large body of literature has dealt with extracting OD matrices from recently available, individual digital footprints [91, 92, 93, 94, 95, 90, 96, 97, 98].”
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2017, background): “As wireless mobile connectivity has changed the way people communicate, work, and play, mobile phone data can be used to derive the spatiotemporal information of anonymous phone users’ whereabouts for analysis of their mobility patterns [14], [15], [16].”
Traffic state estimation on highway: A comprehensive survey (2017, methodology): “, 2010), CDR (call digital records) (Caceres et al., 2007; Wu et al., 2015) and similar data from mobile phones (Asakura and Hato, 2004))”
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.”