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Open AccessArticle

Methods for Inferring Route Choice of Commuting Trip From Mobile Phone Network Data

1
Department of Computer Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
2
Excellence Center in Infrastructure Technology and Transportation Engineering, Department of Computer Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
3
Sociology and Economics of Networks and Services Department, Orange Labs, 92320 Châtillon, France
4
SENSEable City Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(5), 306; https://doi.org/10.3390/ijgi9050306
Received: 30 March 2020 / Revised: 30 April 2020 / Accepted: 4 May 2020 / Published: 7 May 2020
For billing purposes, telecom operators collect communication logs of our mobile phone usage activities. These communication logs or so called CDR has emerged as a valuable data source for human behavioral studies. This work builds on the transportation modeling literature by introducing a new approach of crowdsource-based route choice behavior data collection. We make use of CDR data to infer individual route choice for commuting trips. Based on one calendar year of CDR data collected from mobile users in Portugal, we proposed and examined methods for inferring the route choice. Our main methods are based on interpolation of route waypoints, shortest distance between a route choice and mobile usage locations, and Voronoi cells that assign a route choice into coverage zones. In addition, we further examined these methods coupled with a noise filtering using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and commuting radius. We believe that our proposed methods and their results are useful for transportation modeling as it provides a new, feasible, and inexpensive way for gathering route choice data, compared to costly and time-consuming traditional travel surveys. It also adds to the literature where a route choice inference based on CDR data at this detailed level—i.e., street level—has rarely been explored. View Full-Text
Keywords: commuting trip; route choice inference; mobile phone network data; CDR; call detail records commuting trip; route choice inference; mobile phone network data; CDR; call detail records
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Sakamanee, P.; Phithakkitnukoon, S.; Smoreda, Z.; Ratti, C. Methods for Inferring Route Choice of Commuting Trip From Mobile Phone Network Data. ISPRS Int. J. Geo-Inf. 2020, 9, 306.

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