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

Cherif Smaili (1) , Maan El Badaoui El Najjar (1) , François Charpillet (1)

1 MAIA - Autonomous intelligent machine

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.

Mots clés: bayesian network; robotic; GPS; map-matching

Domaines: Intelligence artificielle [cs.AI]; Robotique [cs.RO]

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⟩