Cellular Data Meet Vehicular Traffic Theory: Location Area Updates and Cell Transitions for Travel Time Estimation
Road traffic can be monitored by means of static sensors and derived from floating car data, i.e., reports from a sub-set of vehicles. These approaches suffer from a number of technical and economical limitations. Alternatively, the authors propose to leverage the mobile cellular network as a ubiquitous mobility sensor. They show how vehicle travel times and road congestion can be inferred from anonymized signaling data collected from a cellular mobile network. While other previous studies have considered data only from active devices, e.g., engaged in voice calls, their approach exploits also data from idle users resulting in an enormous gain in coverage and estimation accuracy.