title: The TimeGeo modeling framework for urban motility without travel surveys.
abstract: Well-established fine-scale urban mobility models today depend on detailed but cumbersome and expensive travel surveys for their calibration. Not much is known, however, about the set of mechanisms needed to generate complete mobility profiles if only using passive datasets with mostly sparse traces of individuals. In this study, we present a mechanistic modeling framework (TimeGeo) that effectively generates urban mobility patterns with resolution of 10 min and hundreds of meters. It ties together the inference of home and work activity locations from data, with the modeling of flexible activities (e.g., other) in space and time. The temporal choices are captured by only three features: the weekly home-based tour number, the dwell rate, and the burst rate. These combined generate for each individual: (i) stay duration of activities, (ii) number of visited locations per day, and (iii) daily mobility networks. These parameters capture how an individual deviates from the circadian rhythm of the population, and generate the wide spectrum of empirically observed mobility behaviors. The spatial choices of visited locations are modeled by a rank-based exploration and preferential return (r-EPR) mechanism that incorporates space in the EPR model. Finally, we show that a hierarchical multiplicative cascade method can measure the interaction between land use and generation of trips. In this way, urban structure is directly related to the observed distance of travels. This framework allows us to fully embrace the massive amount of individual data generated by information and communication technologies (ICTs) worldwide to comprehensively model urban mobility without travel surveys.
authors: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors: Shan
authors: S
authors: Jiang
authors: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors: Yingxiang
authors: Y
authors: Yang
authors: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors: Siddharth
authors: S
authors: Gupta
authors: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors: Daniele
authors: D
authors: Veneziano
authors: Research & Innovation Center, Ford Motor Company, Palo Alto, CA 9304;
authors: Shounak
authors: S
authors: Athavale
authors: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139; Center for Advanced Urbanism, Massachusetts Institute of Technology, Cambridge, MA 02139 martag@mit.edu.
authors: Marta C
authors: MC
authors: González
mesh_terms: D002958:City Planning / Q000706:statistics & numerical data; D063426:Human Migration / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D011157:Population Dynamics / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires; D014195:Travel
keywords: human mobility; mobile phone data; networks; urban model; urban planning