Road Selection using Multi-Criteria Fusion for the Roadmap-Matching Problem

Maan El Badaoui El Najjar (1) , Philippe Bonnifait (2)

1 STF - Systèmes Tolérants aux Fautes
2 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

This paper presents a road selection strategy for novel road-matching methods that are designed to support real-time navigational features within Advanced Driving-Assistance Systems (ADAS). Selecting the most likely segment(s) is a crucial issue for the road-matching problem. The selection strategy merges several criteria using Belief theory. Particular attention is given to the development of belief functions from measurements and estimations of relative distances, headings, and velocities. Experimental results using data from antilock brake system sensors, the differential Global Positioning System receiver, and the accurate digital roadmap illustrate the performances of this approach, particularly in ambiguous situations.

Mots clés: Belief theory; Geographical Information System (GIS); Global Positioning System (GPS); localization; sensor fusion

Domaines: Automatique / Robotique

Maan El Badaoui El Najjar, Philippe Bonnifait. Road Selection using Multi-Criteria Fusion for the Roadmap-Matching Problem. IEEE Transactions on Intelligent Transportation Systems, 2007, 8 - Issue 2, pp.279-291. ⟨10.1109/TITS.2007.895312⟩. ⟨inria-00172595v2⟩