ABSTRACT
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.
- A. Buvaneswari, J. M. Graybeal, D. A. James, D. Lambert, C. Liu, and W. M. MacDonald. A statistical view of the transient signals that support a wireless call. Technometrics, 49, 2007.Google Scholar
- M. Y. Chen, T. Sohn, D. Chmelev, D. H. J. Hightower, J. Hughes, A. LaMarca, F. Potter, I. Smith, and A. Varshavsky. Practical metropolitan-scale positioning for gsm phones. In Proc. of the 8th Int. Conference on Ubiquitous Computing, Irvine, California, Sept. 2006. Google ScholarDigital Library
- K. Kleisouris, B. Firner, R. Howard, Y. Zhang, and R. P. Martin. Detecting intra-room mobility with signal strength descriptors. In Proc. of the 11th ACM Int. Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc '10, pages 71--80, 2010. Google ScholarDigital Library
- J. Krumm, J. Letchner, and E. Horvitz. Map matching with travel time constraints. In Society of Automotive Engineers (SAE) 2007 World Congress, April 2007.Google ScholarCross Ref
- A. LaMarca, Y. Chawathe, S. Consolvo, J. Hightower, I. Smith, J. Scott, T. Sohn, J. Howard, J. Hughes, F. Potter, J. Tabert, P. Powledge, G. Borriello, and B. Schilit. Place lab: Device positioning using radio beacons in the wild. In Proc. of the 3rd Int. Conference on Pervasive Computing, Lecture Notes in Computer Science. Springer-Verlag, May 2005. Google ScholarDigital Library
- E. Levina and P. Bickel. The Earth Mover's Distance is the Mallows Distance: Some Insights from Statistics. In ICCV 2001, pages 251--256, 2001.Google ScholarCross Ref
- NJ Department of Transportation. Roadway information and traffic counts. www.state.nj.us/transportation/refdata/roadway/traffic.shtm.Google Scholar
- Y. Rubner, C. Tomasi, and L. J. Guibas. A metric for distributions with applications to image databases. In Proceedings of the Sixth International Conference on Computer Vision, ICCV '98, pages 59--, Washington, DC, USA, 1998. IEEE Computer Society. Google ScholarDigital Library
- Y. Rubner, C. Tomasi, and L. J. Guibas. The earth mover's distance as a metric for image retrieval. Int. J. Comput. Vision, 40:99--121, November 2000. Google ScholarDigital Library
- A. Thiagarajan, L. S. Ravindranath, H. Balakrishnan, S. Madden, and L. Girod. Accurate, Low-Energy Trajectory Mapping for Mobile Devices. In 8th USENIX Symp. on Networked Systems Design and Implementation (NSDI), Boston, MA, March 2011. Google ScholarDigital Library
- A. Thiagarajan, L. S. Ravindranath, K. LaCurts, S. Toledo, J. Eriksson, S. Madden, and H. Balakrishnan. VTrack: Accurate, Energy-Aware Traffic Delay Estimation Using Mobile Phones. In 7th ACM Conference on Embedded Networked Sensor Systems (SenSys), Berkeley, CA, November 2009. Google ScholarDigital Library
- US Department of Transportation. Driver electronic device use in 2009. Traffic Safety Facts Research Note, DOT HS 811--372, September 2010.Google Scholar
- A. Varshavsky, D. Pankratov, J. Krumm, and E. de Lara. Calibree: Calibration-free localization using relative distance estimations. In Proc. of the 6th International Conference on Pervasive Computing, May 2008. Google ScholarDigital Library
- A. Varshavsky and S. Patel. chapter 7: Location in ubiquitous computing. Ubiquitous Computing Fundamentals, 2010.Google Scholar
- SkyHook Wireless, http://www.skyhookwireless.com.Google Scholar
- Navizon, http://www.navizon.com.Google Scholar
Index Terms
- Route classification using cellular handoff patterns
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