Abstract
This paper describes a novel road-matching method designed to support the real-time navigational function of cars for advanced systems applications in the area of driving assistance. This method provides an accurate estimation of position for a vehicle relative to a digital road map using Belief Theory and Kalman filtering. Firstly, an Extended Kalman Filter combines the DGPS and ABS sensor measurements to produce an approximation of the vehicle’s pose, which is then used to select the most likely segment from the database. The selection strategy merges several criteria based on distance, direction and velocity measurements using Belief Theory. A new observation is then built using the selected segment, and the approximate pose adjusted in a second Kalman filter estimation stage. The particular attention given to the modeling of the system showed that incrementing the state by the bias (also called absolute error) of the map significantly increases the performance of the method. Real experimental results show that this approach, if correctly initialized, is able to work over a substantial period without GPS.
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Maan El Badaoui El Najjar was born in Tripoli-Lebanon in 1975. He received his engineer diploma and his M.S. degree in control system and automation from the Institut National Polytechnique de Grenoble, France, in 1999 and 2000 respectively and his Ph.D. degree in control system from the Université de Technologie de Compiègne, France, in 2003. He is research and teaching associate at the Heudiasyc laboratory of the Université de Technologie de Compiègne. His current research interests include robot localization, map-aided navigation techniques, sensor fusion and Bayesian estimation techniques.
Philippe Bonnifait graduated from the Ecole Superieure d’Electronique de l’Ouest, France, in 1992 and received the Ph.D. degree in automatic control and computer science from the Ecole Centrale de Nantes, France, in 1997. He joined the Institut de Recherche en Communications et Cybernétique de Nantes (IRCCyN UMR 6597), France, in 1993. Since September 1998, he is with Heudiasyc UMR 6599, France, and he is Assistant Professor at the Université de Technologie de Compiègne. His current research interests are in intelligent outdoor vehicles, with particular emphasis on applications to dynamic localisation.
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El Najjar, M.E., Bonnifait, P. A Road-Matching Method for Precise Vehicle Localization Using Belief Theory and Kalman Filtering. Auton Robot 19, 173–191 (2005). https://doi.org/10.1007/s10514-005-0609-1
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DOI: https://doi.org/10.1007/s10514-005-0609-1