WCDMA for UMTS: Radio Access for Third Generation Mobile Communications
WCDMA for UMTS: Radio Access for Third Generation Mobile Communications
Measuring serendipity: connecting people, locations and interests in a mobile 3G network
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
IEEE Transactions on Intelligent Transportation Systems
Traffic Monitoring Using Floating Car Data in Hefei
IPTC '10 Proceedings of the 2010 International Symposium on Intelligence Information Processing and Trusted Computing
Driving with knowledge from the physical world
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome
IEEE Transactions on Intelligent Transportation Systems
Steps towards the extraction of vehicular mobility patterns from 3g signaling data
TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
Data-Driven Intelligent Transportation Systems: A Survey
IEEE Transactions on Intelligent Transportation Systems
| Hi-index | 0.00 |
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, we propose to leverage the mobile cellular network as a ubiquitous mobility sensor. We 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, our approach exploits also data from idle users resulting in an enormous gain in coverage and estimation accuracy. By validating our approach against four different traffic monitoring datasets collected on a sample highway over one month, we show that our method can detect congestions very accurately and in a timely manner.