Tracking vehicular speed variations by warping mobile phone signal strengths

Gayathri Chandrasekaran, Tam Vu, Alexander Varshavsky, Marco Gruteser, Richard P. Martin, Jie Yang, Yingying Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

46 Scopus citations

Abstract

In this paper, we consider the problem of tracking fine-grained speeds variations of vehicles using signal strength traces from GSM enabled phones. Existing speed estimation techniques using mobile phone signals can provide longer-term speed averages but cannot track short-term speed variations. Understanding short-term speed variations, however, is important in a variety of traffic engineering applications-for example, it may help distinguish slow speeds due to traffic lights from traffic congestion when collecting real time traffic information. Using mobile phones in such applications is particularly attractive because it can be readily obtained from a large number of vehicles. Our approach is founded on the observation that the large-scale path loss and shadow fading components of signal strength readings (signal profile) obtained from the mobile phone on any given road segment appear similar over multiple trips along the same road segment except for distortions along the time axis due to speed variations. We therefore propose a speed tracking technique that uses a Derivative Dynamic Time Warping (DDTW) algorithm to realign a given signal profile with a known training profile from the same road. The speed tracking technique then translates the warping path (i.e., the degree of stretching and compressing needed for alignment) into an estimated speed trace. Using 6.4 hours of GSM signal strength traces collected from a vehicle, we show that our algorithm can estimate vehicular speed with a median error of ± 5mph compared to using a GPS and can capture significant speed variations on road segments with a precision of 68% and a recall of 84%.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Pervasive Computing and Communications, PerCom 2011
Pages213-221
Number of pages9
DOIs
StatePublished - Jun 8 2011
Event9th IEEE International Conference on Pervasive Computing and Communications, PerCom 2011 - Seattle, WA, United States
Duration: Mar 21 2011Mar 25 2011

Publication series

Name2011 IEEE International Conference on Pervasive Computing and Communications, PerCom 2011

Other

Other9th IEEE International Conference on Pervasive Computing and Communications, PerCom 2011
CountryUnited States
CitySeattle, WA
Period3/21/113/25/11

All Science Journal Classification (ASJC) codes

  • Software

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    Chandrasekaran, G., Vu, T., Varshavsky, A., Gruteser, M., Martin, R. P., Yang, J., & Chen, Y. (2011). Tracking vehicular speed variations by warping mobile phone signal strengths. In 2011 IEEE International Conference on Pervasive Computing and Communications, PerCom 2011 (pp. 213-221). [5767589] (2011 IEEE International Conference on Pervasive Computing and Communications, PerCom 2011). https://doi.org/10.1109/PERCOM.2011.5767589