Hidden Markov Models for Vehicle Tracking with Bluetooth
Bluetooth is a short range communication protocol. Bluetooth-enabled devices can be detected using road-side equipment, and each detected device reports a unique identifier. These unique identifiers can be used to track vehicles through road networks over time. The focus of this paper is on reconstructing the paths of vehicles through a road network using Bluetooth detection data. A method is proposed that uses Hidden Markov Models, which are a well-known tool for statistical pattern recognition. The proposed method is evaluated on a mixture of real and synthetic Bluetooth data with global positioning system (GPS) ground truth, and it outperforms a simple deterministic strategy by a large margin (30%-50%) in this case.
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Supplemental Notes:
- This paper was sponsored by TRB committee ABJ35 Highway Traffic Monitoring.
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Corporate Authors:
500 Fifth Street, NW
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Authors:
- Lees-Miller, John D
- Wilson, R Eddie
- Box, Simon
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Conference:
- Transportation Research Board 92nd Annual Meeting
- Location: Washington DC, United States
- Date: 2013-1-13 to 2013-1-17
- Date: 2013
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Photos; References;
- Pagination: 14p
- Monograph Title: TRB 92nd Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Bluetooth technology; Global Positioning System; Markov processes; Pattern recognition systems; Traffic surveillance; Vehicle to infrastructure communications; Vehicles
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I73: Traffic Control;
Filing Info
- Accession Number: 01477019
- Record Type: Publication
- Report/Paper Numbers: 13-3032
- Files: TRIS, TRB, ATRI
- Created Date: Mar 28 2013 9:00AM