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Application of particle filters to a map-matching algorithm

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Abstract

This paper presents a numerical probabilistic approach to the map-matching problem within the framework of the Bayesian theory. The proposed solution is based on the sequential Monte Carlo method—the so-called particle filtering. This algorithm can be adapted for implementation on real-time portable car navigation systems equipped with GPS or dead reckoning sensors. The reliability and accuracy of this algorithm were investigated using simulated data and data from real-world driving tests in urban environments.

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Authors and Affiliations

  1. Department of Computer Systems, Tampere University of Technology, Tampere, Finland

    P. Davidson, J. Collin & J. Takala

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  1. P. Davidson
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  2. J. Collin
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  3. J. Takala
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Davidson, P., Collin, J. & Takala, J. Application of particle filters to a map-matching algorithm. Gyroscopy Navig. 2, 285–292 (2011). https://doi.org/10.1134/S2075108711040067

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  • DOI: https://doi.org/10.1134/S2075108711040067

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