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Conference Papers Year : 2007

Multi-Sensor Fusion Method using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching

Cherif Smaili
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Abstract

This paper presents a multi-sensor fusion strategy for a novel road-matching method designed to support real-time navigational features within advanced driving-assistance systems. Managing multihypotheses is a useful strategy for the road-matching problem. The multi-sensor fusion and multi-modal estimation are realized using Dynamical Bayesian Network. Experimental results, using data from Antilock Braking System (ABS) sensors, a differential Global Positioning System (GPS) receiver and an accurate digital roadmap, illustrate the performances of this approach, especially in ambiguous situations.
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Dates and versions

inria-00170426 , version 1 (07-09-2007)

Identifiers

  • HAL Id : inria-00170426 , version 1
  • ARXIV : 0709.1099

Cite

Cherif Smaili, Maan El Badaoui El Najjar, François Charpillet. Multi-Sensor Fusion Method using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching. 19th IEEE International Conference on Tools with Artificial Intelligence - ICTAI 2007, Oct 2007, Patras, Greece. 6 p. ⟨inria-00170426⟩
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