Travel demand estimation and network assignment based on cellular network data

Cellular networks' signaling data provide means for analyzing the efficiency of an underlying transportation system and assisting the formulation of models to predict its future use. This paper describes how signaling data can be processed and used in order to act as means for generating input for traditional transportation analysis models. Specifically, we propose a tailored set of mobility metrics and a computational pipeline including trip extraction, travel demand estimation as well as route and link travel flow estimation based on Call Detail Records (CDR) from mobile phones. The results are based on the analysis of data from the Data for development “D4D” challenge and include data from Côte d'Ivoire and Senegal.