Using App Usage Data From Mobile Devices to Improve Activity-Based Travel Demand Models

In the last years we have seen several studies showing the potential of mobile network data to reconstruct activity and mobility patterns of the population. These data sources allow continuous monitoring of the population with a higher degree of spatial and temporal resolution and at a lower cost co...

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Bibliographic Details
Published inIEEE transactions on big data Vol. 10; no. 5; pp. 633 - 643
Main Authors Gonzalez, Ana Belen Rodriguez, Burrieza-Galan, Javier, Diaz, Juan Jose Vinagre, de Castro, Ines Peirats, Wilby, Mark Richard, Cantu-Ros, Oliva Garcia
Format Journal Article
LanguageEnglish
Published IEEE 01.10.2024
Subjects
Application usage data
Big Data
Big Data analytics
location of activities
Mobile handsets
mobile phone data
Monitoring
Sociology
Soft sensors
Statistics
travel demand models
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Summary:In the last years we have seen several studies showing the potential of mobile network data to reconstruct activity and mobility patterns of the population. These data sources allow continuous monitoring of the population with a higher degree of spatial and temporal resolution and at a lower cost compared with traditional methods. However, for certain applications, the spatial resolution of these data sources is still not enough since it typically provides a spatial resolution of hundreds of meters in urban areas and of few kilometers in rural areas. In this article, we fill this gap by proposing a methodology that utilises GPS data from the usage of different applications in mobile devices. This approach improves the spatial precision in the location of activities, previously identified with the mobile network data.
ISSN:2332-7790
2372-2096
DOI:10.1109/TBDATA.2024.3366088