Reconciliation of Regional Travel Model and Passive Device Tracking Data

Abstract

The ability to passively track large numbers of mobile devices has generated a lot of excitement in recent years. Traditional travel surveys without Global Positioning Satellite (GPS) tracking, either wholly or in part, seems passe today. However, GPS tracking can only overcome some of the problems associated with travel diary surveys. It can capture missed trips and route choice information, but at increased cost per survey. However, it does nothing to ease the rising cost and difficulty associated with contacting, recruiting, retaining households in the first place, or collecting and processing the data. Passive tracking overcomes these limitations, at the expense of giving up interaction with the device owner. Thus, information about the traveler, trip purpose, and other details must be inferred or lost. The ideal solution is to use both travel diaries and passive tracking together. While techniques for fusing these data are yet to be proven the concept has strong intuitive appeal. Until such techniques emerge the question becomes whether such data can be used on their own, and whether they resemble the output of travel models built using traditional survey data. The opportunity to answer such questions arose recently in the Research Triangle Region of North Carolina, which served as a pilot project for using origin destination data from AirSage as an adjunct to modeling. A detailed analysis of the differences between the AirSage data and the Triangle Regional Model (TRM) has been completed. The differences were subtle in some cases and surprising in others. This paper reports on the findings of this comparison. A brief description of the AirSage data and TRM provides the context for the discussion. Presented in this paper is the methodology for comparing the two data sources along with the results. The results show that the highway assignment using AirSage data is comparable to the highway assignment using model estimated trip tables, supporting the use of passively collected cellular data as a low cost option for travel model validation.

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