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Open AccessFeature PaperArticle

Evaluating Origin–Destination Matrices Obtained from CDR Data

1
Dipartimento di Scienze e Metodi dell’Ingegneria, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy
2
Centro En&Tech, University of Modena and Reggio Emilia, 42124 Reggio Emilia, Italy
3
Centro Softech-ICT, University of Modena and Reggio Emilia, 41125 Modena, Italy
4
Dipartimento di Ingegneria Enzo Ferrari, University of Modena and Reggio Emilia, 41125 Modena, Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(20), 4470; https://doi.org/10.3390/s19204470
Received: 1 August 2019 / Revised: 30 September 2019 / Accepted: 10 October 2019 / Published: 15 October 2019
(This article belongs to the Special Issue Mobile Sensing: Platforms, Technologies and Challenges)
Understanding and correctly modeling urban mobility is a crucial issue for the development of smart cities. The estimation of individual trips from mobile phone positioning data (i.e., call detail records (CDR)) can naturally support urban and transport studies as well as marketing applications. Individual trips are often aggregated in an origin–destination (OD) matrix counting the number of trips from a given origin to a given destination. In the literature dealing with CDR data there are two main approaches to extract OD matrices from such data: (a) in time-based matrices, the analysis focuses on estimating mobility directly from a sequence of CDRs; (b) in routine-based matrices (OD by purpose) the analysis focuses on routine kind of movements, like home-work commute, derived from a trip generation model. In both cases, the OD matrix measured by CDR counts is scaled to match the actual number of people moving in the area, and projected to the road network to estimate actual flows on the streets. In this paper, we describe prototypical approaches to estimate OD matrices, describe an actual implementation, and present a number of experiments to evaluate the results from multiple perspectives. View Full-Text
Keywords: mobility patterns; CDR data; OD matrices mobility patterns; CDR data; OD matrices
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MDPI and ACS Style

Mamei, M.; Bicocchi, N.; Lippi, M.; Mariani, S.; Zambonelli, F. Evaluating Origin–Destination Matrices Obtained from CDR Data. Sensors 2019, 19, 4470. https://doi.org/10.3390/s19204470

AMA Style

Mamei M, Bicocchi N, Lippi M, Mariani S, Zambonelli F. Evaluating Origin–Destination Matrices Obtained from CDR Data. Sensors. 2019; 19(20):4470. https://doi.org/10.3390/s19204470

Chicago/Turabian Style

Mamei, Marco; Bicocchi, Nicola; Lippi, Marco; Mariani, Stefano; Zambonelli, Franco. 2019. "Evaluating Origin–Destination Matrices Obtained from CDR Data" Sensors 19, no. 20: 4470. https://doi.org/10.3390/s19204470

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