Application of particle filters to a map-matching algorithm

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.