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http://dx.doi.org/10.5391/JKIIS.2009.19.5.641

Interacting Multiple Model Vehicle-Tracking System Based on Neural Network  

Hwang, Jae-Pil (Yonsei University, School of Electrical and Electronic Engr.)
Park, Seong-Keun (Yonsei University, School of Electrical and Electronic Engr.)
Kim, Eun-Tai (Yonsei University, School of Electrical and Electronic Engr.)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.19, no.5, 2009 , pp. 641-647 More about this Journal
Abstract
In this paper, a new filtering scheme for adaptive cruise control (ACC) system is presented. In the proposed scheme, the identification of the mode of the preceding vehicle is considered as a classification problem and it is done by a neural network classifier. The neural network classifier outputs a posterior probability of the mode of the preceding vehicle and the probability is directly used in the IMM framework. Finally, ten scenarios are made and the proposed NIMM is tested on them to show its validity.
Keywords
Interacting multiple model; Kalman filter; Adaptive Cruise Control;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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