Comprehensive Review of Travel Behavior and Mobility Pattern Studies That Used Mobile Phone Data

Abstract

Traditional data acquisition methods, such as surveys and diaries, used in transportation studies have become burdensome and inefficient in comparison to the emerging sources of passively collected data. These newer data sources have the ability to improve data quality and accuracy and the potential to complement conventional data. This paper presents a comprehensive review of studies that have utilized passively collected data, such as data from personal or vehicle GPS devices, mobile phone network data, and—more recently—smartphone GPS data. This review focuses on the data-processing algorithms that have been used to derive travel information from trajectory traces, as well as the variety of applications that have been conducted on the basis of these data. Some applications of these data have included origin–destination estimation, real-time traffic monitoring, and human mobility pattern analysis. Although passively collected data have great potential, issues with possible sample bias and a lack of demographic data require further research. This study may help people interested in employing these data to understand better the current practices, as well as the potential and the challenges associated with the data.