"Road Selection using Multi-Criteria Fusion for the Roadmap-Matching Problem"
Résumé
This paper presents a road selection strategy for novel road-matching methods designed to support real-time navigational features within Advanced Driving-Assistance Systems. 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 ABS sensors, a differential GPS receiver and an accurate digital roadmap, illustrate the performances of this approach, especially in ambiguous situations.