Aggregated Mobile Phone Data in Transportation: A Literature Review

Mobile phone data are increasingly considered as a valuable data source for developing innovative mobility applications to support smart city objectives. aggregated mobile phone data, derived from anonymized and aggregated location signals generated by mobile devices, provide density-based insights into how people move and interact within urban environments, while ensuring compliance with privacy regulations. This study provides a literature review analysis of aggregated mobile phone data applications in transportation. The findings demonstrate the usability of aggregated mobile phone data to describe mobility flows. The methodological approach used in previous literature for extracting additional insights are classified to the the four-step transportation model as a conceptual framework. Furthermore, the review highlights the versatility of aggregated mobile phone data, showcasing its use not only for general mobility pattern analysis but also for specific applications, such as event-specific dynamics, traffic management and environmental impact analysis, and public transport planning. The study identifies three key directions for future research: (1) bridging data insights with urban planning policies through practical decision-making applications, (2) addressing the transfer-ability of data extraction methods across different data formats and structures through comparative studies, and (3) expanding the versatility of applications by integrating other complementary data sources.