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.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ABJ35 Highway Traffic Monitoring.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Lees-Miller, John D
    • Wilson, R Eddie
    • Box, Simon
  • Conference:
  • Date: 2013


  • 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

Filing Info

  • Accession Number: 01477019
  • Record Type: Publication
  • Report/Paper Numbers: 13-3032
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 28 2013 9:00AM