Mobility behavior from cell phone communication data

The objective of SEMAPHORE was to provide transportation planning and forecasting systems with knowledge about individual mobility behavior extracted from cell phone communication data. This was achieved by statistical inference algorithms for semantic analysis of cell phone trajectories combining additional data sources such as land use and background knowledge. 

Mobility behavioral patterns were discovered and exploited for inference of missing data and statistical extrapolation. Translation of the data into the domain ontology of travel demand modelling and suitable interfaces allowed interoperability with the transportation planning software PTV VISUM™. This opened up cell phone data as a novel and rich source of information for transportation planning. SEMAPHORE demonstrated by empirical evaluation to have huge potential to improve the quality of the traffic models and to reduce the costs for mobility data surveys.