Multi-Hypothesis Map-Matching Using Particle Filtering Dherbomez, G ; Laneurit, C ; Bonnifait, J
Utgivningsinformation: Bryssel ITS in daily life: 16th world congress and exhibition on intelligent transport systems and services, Stockholm 21-25 September 2009. Paper, 2009Beskrivning: 8 sÄmnen: Bibl.nr: VTI P1835:16 [World]Location: Abstrakt: 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 comparison with 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.| Aktuellt bibliotek | Status | |
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| Statens väg- och transportforskningsinstitut | Tillgänglig |
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 comparison with 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.