@inproceedings{840d6a29db984c3185540073764583eb,
title = "Map matching algorithm using interval analysis and dempster-shafer theory",
abstract = "The goal of map matching methods is to compute an accurate position of a vehicle from an initial estimated position using a digital road network data. In this paper, a new map matching method based on Dempster-Shafer theory and interval analysis is presented. The core idea of this method is the use of Dempster-Shafer theory for modeling partial information on model and measurement uncertainties and for managing multiple hypothesis situations. This technique proves to be relevant to treat junction roads situations or parallel roads. The results on simulated data show the usefulness of the proposed method.",
keywords = "Data fusion, Dempster-Shafer theory, Interval analysis, Map matching, Multiple hypothesis technique, State estimation",
author = "Ghalia Nassreddine and Fahed Abdallah and Thierry Denoeux",
year = "2009",
doi = "10.1109/IVS.2009.5164328",
language = "English",
isbn = "9781424435043",
series = "IEEE Intelligent Vehicles Symposium, Proceedings",
pages = "494--499",
booktitle = "2009 IEEE Intelligent Vehicles Symposium",
note = "2009 IEEE Intelligent Vehicles Symposium ; Conference date: 03-06-2009 Through 05-06-2009",
}