Modeling driver operation behavior by linear prediction analysis and auto associative neural network

Authors:
MD Rizal Othman;Zhong Zhang;Takashi Imamura;Tetsuo Miyake
Affiliations:
University Malaysia Pahang, Pahang, Malaysia and Department of Production System Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan;Department of Production System Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan;Department of Production System Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan;Department of Production System Engineering, Toyohashi University of Technology, Toyohashi, Aichi, Japan
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

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Abstract

This paper presents a new method for modeling driver operation behavior. The proposed method is based on using the predictor coefficients as feature vectors extracted from driving operation signal by linear prediction analysis (LPA). The distribution of the feature vectors is captured by employing auto associative neural networks (AANN) model. The performance of the model was evaluated through driver identification process and the results obtained demonstrate that the model can grasp the individual characteristics of the driver.