Road Selection Using Multicriteria Fusion for the Road-Matching Problem

This paper presents a solution to road-matching and localization difficulties experienced by advanced driving-assistance systems (ADA) employing geographical information systems (GIS) and Global Positioning System (GPS) that uses a road selection scheme determined by several selection criteria from belief theory. A basic concept of belief theory, which is the generalization of certain Bayesian imports, is that uncertainty is admitted into the reasoning process and thereby can combine uncertain measurements coherently. The algorithm developed using this method was then tested in a real-time condition and discovered that the system was able to quantify ambiguity in road-matching problems without significant issue. Such a capacity is important to increase confidence in vehicle localization using GPS and GIS in advanced driving-assistance systems.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Authors:
  • El Najjar, Maan El Badaoui
  • Bonnifait, Philippe
• Publication Date: 2007-6

Language

• English

Media Info

• Media Type: Print
• Features: Figures; Photos; References;
• Pagination: pp 279-291
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 8
  • Issue Number: 2
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Data fusion; Driver support systems; Geographic information systems; Global Positioning System; Route choice; Theory
• Subject Areas: Highways; Research; Vehicles and Equipment; I90: Vehicles;

Filing Info

• Accession Number: 01054567
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: BTRIS, TRIS
• Created Date: Jun 18 2007 8:07PM