Multi-Hypothesis Map-Matching Using Particle Filtering.

Author(s)
Dherbomez, G. Laneurit, C. & Bonnifait, J.
Year
Abstract

This paper describes a new Map-Matching method relying on the use of Particle Filtering. Since this method implements a multi-hypothesis road-tracking strategy, it is able to handle ambiguous situations arising at junctions or when positioning accuracy is low. In this Bayesian framework, map-matching integrity can be monitored using normalized innovation residuals. An interesting characteristic of this method is its efficient implementation since particles are constraint to the road network; the complexity is reduced to one dimension. Experimental tests carried out with real data are finally reported to illustrate the performance of the method in comparisonwith a ground truth. The current real-time implementation allows map-matching at 100 Hz with confidence indicators which is relevant for many map-aided advanced driver assistance systems (ADAS) applications.

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Publication

Library number
C 46978 (In: C 46669 CD-ROM) /72 / ITRD E852499
Source

In: ITS in daily life : proceedings of the 16th World Congress on Intelligent Transport Systems (ITS), Stockholm, Sweden, September 21-25, 2009, 8 p.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.