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19th IEEE International Conference on Tools with Artificial Intelligence - Vol.1 (ICTAI 2007)
Multi-sensor Fusion Method Using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching
Paris, France
October 29-October 31
ISBN: 0-7695-3015-X
ASCII Text
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Cherif Smaili, Maan E. El Najjar, Fran?ois Charpillet, "Multi-sensor Fusion Method Using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching," Tools with Artificial Intelligence, IEEE International Conference on, vol. 1, pp. 146-151, 19th IEEE International Conference on Tools with Artificial Intelligence - Vol.1 (ICTAI 2007), 2007.
 
 
BibTex
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@article{ 10.1109/ICTAI.2007.70,
author = {Cherif Smaili and Maan E. El Najjar and Fran?ois Charpillet},
title = {Multi-sensor Fusion Method Using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching},
journal ={Tools with Artificial Intelligence, IEEE International Conference on},
volume = {1},
year = {2007},
issn = {1082-3409},
pages = {146-151},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICTAI.2007.70},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Tools with Artificial Intelligence, IEEE International Conference on
TI - Multi-sensor Fusion Method Using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching
SN - 1082-3409
SP146
EP151
A1 - Cherif Smaili,
A1 - Maan E. El Najjar,
A1 - Fran?ois Charpillet,
PY - 2007
VL - 1
JA - Tools with Artificial Intelligence, IEEE International Conference on
ER -
 
This paper presents a multi-sensor fusion strategy for a novel road-matching method designed to support real-time navigational features within advanced driving-assistance systems. Managing multi- hypotheses is a useful strategy for the road-matching problem. The multi-sensor fusion and multi-modal estimation are realized using Dynamical Bayesian Network. Experimental results, using data from Anti- lock Braking System (ABS) sensors, a differential Global Positioning System (GPS) receiver and an accurate digital roadmap, illustrate the performances of this approach, especially in ambiguous situations.
Citation:
Cherif Smaili, Maan E. El Najjar, Fran?ois Charpillet, "Multi-sensor Fusion Method Using Dynamic Bayesian Network for Precise Vehicle Localization and Road Matching," ictai, vol. 1, pp.146-151, 19th IEEE International Conference on Tools with Artificial Intelligence - Vol.1 (ICTAI 2007), 2007
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