Abstract

A novel methodology to infer transportation mode taken by mobile device users between regions of interest is introduced. It relies on analysing anonymised billing data, namely call detail records, supplied by mobile network operators as the primary source of user-created data. Coupled with the spatial coverage and distribution of mobile network cells and geographical route map information of major transportation modes, assumed to be partially non-overlapping, user travel paths can be predicted. Journey specific trajectories are constructed and analysed using the concept of virtual cell path for each qualified pre-processed list of activities from each unique user. After classification, kernel density paths for each route were generated both for illustration and validation purposes. Dierentiation between rail and road users travelling between Dublin and Cork in the Republic of Ireland is shown as an example application case study