Using cell phone data to measure quality of service and passenger flows of Paris transit system

This paper shows that the particular conditions under which a cellular phone network is operated underground can make it possible to measure passenger flows in an underground transit system. With the help of the mobile network operator Orange, some experiments have been conducted in Paris underground transit system to assess the potential of this new kind of data for transportation studies. The results show that good estimates of dynamic quantities, such as travel times, train occupancy levels and origin-destination flows can be derived from cellular data. The travel times, train occupancy levels and origin-destination flows inferred from cellular data have been compared to direct field observations and Automatic Fare Collection data provided by the STIF (the public transport authority in the Paris metropolitan area). The quantities inferred from cellular data are shown to be consistent with those inferred from the other data sources.