01661312

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Passively-generated mobile phone data is emerging as a potential data source for transportation research and applications. Despite the large amount of studies based on the mobile phone data, only a few have reported the problems associated with such data, and documented how they have processed the data. In this paper, the authors propose a data processing framework to address two key problems of anonymous mobile phone data: locational uncertainty and oscillation. They show the effectiveness of their proposed methods in addressing these two problems compared to the state of art algorithms in the field. The authors also demonstrate that without proper processing applied to the data, the statistical regularity of human mobility patterns—a key, significant trait identified for human mobility—is overestimated. They hope this study will stimulate more studies in examining the problems associated with such data and developing methods to address them. Though not as glamorous as those directly deriving insights on mobility patterns (such as statistical regularity), understanding problems of such data and developing solutions is a fundamental research topic on which results of mobility patterns are based.

This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting. Alternate title: Passively Generated Cell Phone Data: Data Issues and Processing Required

18-05118

English

6p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Maps; References; Tables

Algorithms; Cellular telephones; Data analysis; Data collection; Mobility

Data and Information Technology; Highways; Planning and Forecasting

Transportation Research Board Annual Meeting 2018 Paper #18-05118

TRIS, TRB, ATRI

Jan 8 2018 11:17AM