The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Calibree: Calibration-Free Localization Using Relative Distance Estimations
Pervasive '08 Proceedings of the 6th International Conference on Pervasive Computing
VTrack: accurate, energy-aware road traffic delay estimation using mobile phones
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Detecting intra-room mobility with signal strength descriptors
Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
Accurate, low-energy trajectory mapping for mobile devices
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Practical metropolitan-scale positioning for GSM phones
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Human mobility modeling at metropolitan scales
Proceedings of the 10th international conference on Mobile systems, applications, and services
Scalable mining of common routes in mobile communication network traffic data
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Human mobility characterization from cellular network data
Communications of the ACM
Modeling cellular user mobility using a leap graph
PAM'13 Proceedings of the 14th international conference on Passive and Active Measurement
A probabilistic approach to mining mobile phone data sequences
Personal and Ubiquitous Computing
Vector field k-means: clustering trajectories by fitting multiple vector fields
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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Understanding utilization of city roads is important for urban planners. In this paper, we show how to use handoff patterns from cellular phone networks to identify which routes people take through a city. Specifically, this paper makes three contributions. First, we show that cellular handoff patterns on a given route are stable across a range of conditions and propose a way to measure stability within and between routes using a variant of Earth Mover's Distance. Second, we present two accurate classification algorithms for matching cellular handoff patterns to routes: one requires test drives on the routes while the other uses signal strength data collected by high-resolution scanners. Finally, we present an application of our algorithms for measuring relative volumes of traffic on routes leading into and out of a specific city, and validate our methods using statistics published by a state transportation authority.