This paper introduces a micro-simulation of urban traffic flows within a large scale scenario implemented for the Greater Dublin region in Ireland. Traditionally, the data available for traffic simulations come from a population census and dedicated road surveys which only partly cover shopping, leisure or recreational trips. To account for the latter, the presented traffic modelling framework exploits the digital footprints of city inhabitants on services such as Twitter and Foursquare. We enriched the model with findings from our previous studies on geographical layout of communities in a country-wide mobile phone network to account for socially related journeys. These datasets were used to calibrate a variant of a radiation model of spatial choice, which we introduced in order to drive individuals' decisions on trip destinations within an assigned daily activity plan. We observed that given the distribution of population, the workplace locations, a comprehensive set of urban facilities and a list of typical activity sequences of city dwellers collected within a national road survey, the developed micro-simulation reproduces not only the journey statistics but also the traffic volumes at main road segments with surprising accuracy.
['Gavin McArdle', 'Aonghus Lawlor', 'Eoghan Furey', 'Alexei Pozdnoukhov']
City-scale traffic simulation from digital footprints