Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/17119
Title: Building a validation measure for activity-based transportation models based on mobile phone data
Authors: LIU, Feng 
JANSSENS, Davy 
Cui, JianXun
Wang, YunPeng
WETS, Geert 
COOLS, Mario 
Issue Date: 2014
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Source: EXPERT SYSTEMS WITH APPLICATIONS, 41 (14), p. 6174-6189
Abstract: Activity-based micro-simulation transportation models typically predict 24-h activity-travel sequences for each individual in a study area. These sequences serve as a key input for travel demand analysis and forecasting in the region. However, despite their importance, the lack of a reliable benchmark to evaluate the generated sequences has hampered further development and application of the models. With the wide deployment of mobile phone devices today, we explore the possibility of using the travel behavioral information derived from mobile phone data to build such a validation measure. Our investigation consists of three steps. First, the daily trajectory of locations, where a user performed activities, is constructed from the mobile phone records. To account for the discrepancy between the stops revealed by the call data and the real location traces that the user has made, the daily trajectories are then transformed into actual travel sequences. Finally, all the derived sequences are classified into typical activity-travel patterns which, in combination with their relative frequencies, define an activity-travel profile. The established profile characterizes the current activity-travel behavior in the study area, and can thus be used as a benchmark for the assessment of the activity-based transportation models. By comparing the activity-travel profiles derived from the call data with statistics that stern from traditional activity-travel surveys, the validation potential is demonstrated. In addition, a sensitivity analysis is carried out to assess how the results are affected by the different parameter settings defined in the profiling process. (C) 2014 Elsevier Ltd. All rights reserved.
Notes: [Liu, Feng; Janssens, Davy; Wets, Geert] Hasselt Univ, Transportat Res Inst IMOB, B-3590 Diepenbeek, Belgium. [Cui, JianXun] HIT, Dept Transport Engn, Harbin 1500, Peoples R China. [Wang, YunPeng] Beihang Univ, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China. [Cools, Mario] Univ Liege, LEMA, B-4000 Liege, Belgium.
Keywords: Activity-travel sequences; Activity-based transportation models; Travel surveys; Mobile phone data;computer science; artificial intelligence; engineering, electrical & electronic; operations research & management science
Document URI: http://hdl.handle.net/1942/17119
ISSN: 0957-4174
e-ISSN: 1873-6793
DOI: 10.1016/j.eswa.2014.03.054
ISI #: 000338604700012
Rights: © 2014 Elsevier Ltd. All rights reserved.
Category: A1
Type: Journal Contribution
Validations: ecoom 2015
Appears in Collections:Research publications

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