Third International Conference on Information Technology and Applications (ICITA'05) Volume 1 Automatic Vehicle Classification Instrument Based on Multiple Sensor Information Fusion Sydney, Australia July 04-July 07 ISBN: 0-7695-2316-1
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICITA.2005.82
This paper presents a kind of automatic vehicle classification (AVC) instrument for expressway toll collection system based on multiple sensor information fusion technique according to the complicated characteristics of vehicle types in China. In order to develop the instrument, we make use of the video detection segregator, infrared detection technique, piezomagnetic sensor, multiple sensor information fusion technique based on BP neural network. The training result is obtained by 1500 training samples and the training accuracy rate is up to 99.4%. And the Simulation accuracy rate on 500 samples is up to 99.2%. The results show that the classification precision is high and the instrument has great value to be popularized.
Index Terms:
AVC, ETC, Multiple Sensor Information Fusion, Neural Network
Citation:
Weiming Liu, Xueping Zhao, Jingfang Xiao, Youlong Wu, "Automatic Vehicle Classification Instrument Based on Multiple Sensor Information Fusion," icita, vol. 1, pp.379-382, Third International Conference on Information Technology and Applications (ICITA'05) Volume 1, 2005 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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