Vehicular speed estimation using received signal strength from mobile phones

Authors:
Gayathri Chandrasekaran;Tam Vu;Alexander Varshavsky;Marco Gruteser;Richard P. Martin;Jie Yang;Yingying Chen
Affiliations:
Rutgers University, North Brunswick, NJ, USA;Rutgers University, North Brunswick, NJ, USA;AT&T Labs, Florham Park, NJ, USA;Rutgers University, North Brunswick, NJ, USA;Rutgers University, North Brunswick, NJ, USA;Stevens Institute of Technology, Hoboken, NJ, USA;Stevens Institute of Technology, Hoboken, NJ, USA
Venue:
Proceedings of the 12th ACM international conference on Ubiquitous computing
Year:
2010

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Abstract

This paper introduces an algorithm that estimates the speed of a mobile phone by matching time-series signal strength data to a known signal strength trace from the same road. Knowing a mobile phone's speed is useful, for example, to estimate traffic congestion or other transportation performancemetrics. The proposed algorithmcan be implemented in the carrier's infrastructure with Network Measurement Reports obtained by a base station or on a mobile phone with signal strength readings obtained by the handset and depending on implementation choices, promises lower energy consumption than Global Positioning System (GPS) receivers. We evaluate the effectiveness of our algorithm on highway and arterial roads using GSM signal strength traces obtained from several phones over a one month period. The results show that the Correlation algorithm is significantly more accurate than existing techniques based on handoffs or phone localization.