Exploring the Potential of Mobile Phone Data in Travel Pattern Analysis

To support increasingly complex planning activities, many agencies are facing the challenges of obtaining highly nuanced travel behavior data while managing shrinking financial resources. Recent advancements in smartphones and GPS technologies present new opportunities to track travelers' trips. Many studies have applied GPS-based data to planning and demand analysis, but cell phone (mobile phone) GPS data have not received much attention. Google location history (GLH) data provide an opportunity to explore the potential of cell phone GPS data. This paper presents the findings of a study that used GLH data, including the data-processing algorithm used to derive travel information, and their potential applications to understanding travel patterns. For the pilot study, GLH data were obtained from 25 participants over a 1-month period. The data showed that GLH provides a sufficient amount of high-resolution data that can be used to study people's movement without a burden on the respondent. The algorithms developed in this study worked well with the pilot data. However, because of the limitations of the pilot data as a result of the sample size and sample representation, conclusions cannot be drawn from the results of the analysis conducted in this study. Nevertheless, this pilot study shows the potential of mobile phone GPS data as a supplement or complement to conventional data. Given the high rate of penetration of smartphones and the low respondent burden, these data could facilitate the investigation of various issues, such as the reason for less frequent long-distance travel, daily variations in travel behavior, and human mobility patterns on a large spatiotemporal scale.