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The next-generation household travel surveys, the core data generation mechanism for supporting both short- and long-term transportation planning applications, are poised to be transformed. It is now increasingly recognized that passively-solicited big data, or large amount of data generated through various types of subscription services, will play an important role in this transformation. Passively-solicited data in its various forms (e.g., mobile sightings, app-based data) not only differ substantially from the household travel survey data, but also among themselves. The authors argue that the very first step for the passively-solicited data to be integrated into the next-generation household travel surveys is to understand their differences. This paper proposes a three-order analysis framework to analyze these differences. Two case studies each involving a big dataset and a corresponding survey dataset are analyzed to demonstrate their respective properties. The analysis results confirm many distinct properties of such big data as compared between themselves and to the survey data.

This paper was sponsored by TRB committee ABJ40 Standing Committee on Travel Survey Methods.

19-04203

English

15p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Data analysis; Data collection; Mobile applications; Mobility; Smartphones

National Household Travel Survey

Data and Information Technology; Society; Transportation (General)

Transportation Research Board Annual Meeting 2019 Paper #19-04203

TRIS, TRB, ATRI

Dec 7 2018 9:30AM