Document Type



Doctor of Philosophy (PhD)


Civil Engineering

First Advisor's Name

Xia Jin

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Mohammed Hadi

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

B M Golam Kibria

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Yan Xiao

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

Seung Jae Lee

Fifth Advisor's Committee Title

Committee Member


Mobile phone, GPS Data, Travel Pattern Analysis

Date of Defense



In order to support efficient transportation planning decisions, household travel survey data with high levels of accuracy are essential. Due to a number of issues associated with conventional household travel surveys, including high cost, low response rate, trip misreporting, and respondents’ self-reporting bias, government and private agencies are desperately searching for alternative data collection methods. Recent advancements in smart phones and Global Positioning System (GPS) technologies present new opportunities to track travelers’ trips. Considering the high penetration rate of smartphones, it seems reasonable to use smartphone data as a reliable source of individual travel diary. Many studies have applied GPS-Based data in planning and demand analysis but mobile phone GPS data has not received much attention. The Google Location History (GLH) data provide an opportunity to explore the potential of these data. This research presents a study using GLH data, including the data processing algorithm in deriving travel information and the potential applications in understanding travel patterns. The main goal of this study is to explore the potential of using cell phone GPS data to advance the understanding in mobility and travel behavior. The objectives of the study include: a) assessing the technical feasibility of using smartphones in transportation planning as a substitute of traditional household survey b) develop algorithms and procedures to derive travel information from smartphones; and c) identify applications in mobility and travel behavior studies that could take advantage of these smartphones GPS data, which would not have been possible with conventional data collection methods.

This research aims to demonstrate how accurate travel information can be collected and analyzed with lower cost using smartphone GPS data and what analysis applications can be made possible with this new data source. Moreover, the framework developed in this study can provide valuable insights for others who are interested in using cell phone data. GLH data are obtained from 45 participants in a two-month period for the study. The results show great promise of using GLH data as a supplement or complement to conventional travel diary data. It shows that GLH provides sufficient high resolution data that can be used to study people’s movement without respondent burden, and potentially it can be applied to a large scale study easily. The developed algorithms in this study work well with the data. This study supports that transportation data can be collected with smartphones less expensively and more accurately than by traditional household travel survey. These data provide the opportunity to facilitate the investigation of various issues, such as less frequent long-distance travel, hourly variations in travel behavior, and daily variations in travel behavior.





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