LAMDA - Long Term Knowledge Building for Application of Mobile Network Data in Transport Systems Planning
Mobile network data is emerging as one of the most powerful- yet most complex - data sources for understanding how people and goods move through our cities. This project, led by LiU in collaboration with Telia, develops the methods and tools needed to turn highly granular, sensitive and noisy mobile network signals into reliable mobility insights that can support future transport planning, monitoring and traffic management.
Mobile network data is an incredibly complex data source that generates large amounts of data with greatly varying spatiotemporal accuracy, also spiced with sensitive privacy aspects. However, the data source has enormous potential to change the understanding of mobility and streamline both planning, monitoring and control of our traffic systems.
However, this will require long-term knowledge building to understand both the possibilities and potential of the data source. In order to develop and analyze the possibilities of the data source, access to not only aggregated and anonymized mobile network data, but also disaggregated mobile network data is needed.
In this project, LiU, together with Telia, will develop a framework for extracting and analyzing disaggregated mobile network data for selected SIM cards. The project will refine and evaluate the techniques previously developed at LiU to identify trips and estimate means of transport based on data in the mobile network and focus on data quality analysis. The project will also look at how data from the mobile network can be used to produce statistics on heavy goods traffic, travel mode, travel errand and how new types of data from the mobile network affect data quality.
Contact: David Gundlegård david.gundlegard@liu.se
Time period: January 2026- December 2028