Published in Proceedings of the 2006 IEEE Intelligent Transportation Systems Conference: Toronto, Canada, September 17, 2006, pages 1006-1011.
NOTE: At the time of publication, the author Christopher Clark was not yet affiliated with Cal Poly.
The definitive version is available at https://doi.org/10.1109/ITSC.2006.1707353.
The majority of today's navigation techniques for intelligent transportation systems use Global Positioning Systems (GPS) that can provide position information with bounded errors. However, because of the low accuracy and multi-path problem, it is challenging to determine a vehicle's position at lane level. With Markov-based approach based on sharing information among a group of vehicles that are traveling close to each other, the lane positions of vehicles can be found. The algorithm shows its effectiveness in both simulations and experiments with real data.
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