Abstract
Advancements in biometrics-based authentication have led to its increasing prominence and are being incorporated into everyday tasks. Existing vehicle security systems rely currently on electronic alarm or smart card systems. A biometrie driver recognition system utilizing driving behavior signals can be incorporated into existing vehicle security system to form a multimodal identification system and offer a higher degree of protection. The system can be subsequently integrated into intelligent vehicle systems where it can be used for detection of any abnormal driver behavior with the purposes of improved safety or comfort level. In this chapter, we present features extracted using Gaussian Mixture Models (GMM) from accelerator and brake pedal pressure signals, which are then employed as input to the driver recognition module. A novel Evolving Fuzzy Neural Network (EFuNN) was used to illustrate the validity of the proposed system. Results obtained from the experiments are compared with those of statistical methods. They show potential of the proposed recognition system to be used in real-time scenarios. A high identification rate and the low verification error rate were indicated considerable difference in the way different drivers apply pressure to the pedals.
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References
S. Barua, “Authentication of cellular users through voice verification”. Systems, Man, and Cybernetics, 2000 IEEE International Conference, Volume: 1,8-11 Oct. 2000, Pages: 420–425
I. Pottier and G. Burel, “Identification and authentication of handwritten signatures with a connection ist approach”, Neural Networks, IEEE World Congress on Computational Intelligence, 1994 IEEE International Conference, Volume: 5,27 June-2 July 1994, Pages: 2948–2951
M.S. Obaidat B. Sadoun, “Verification of computer users using keystroke dynamics”, Systems, Man and Cybernetics, Part B, IEEE Transactions, Volume: 27, Issue: 2, April 1997, Pages: 261–269
D. Reynolds, “An overview of automatic speaker recognition technology”. Acoustics, Speech, and Signal Processing. Proceedings ICASSP, IEEE International Conference, Volume: 4, 13–17 May 2002. Pages: 4072–4075
K. Igarashi. K. Takeda, F. Itakura and H. Abut, “Biometrie Identification Using Driving Behavioral Signals”, Chapter 17 in DSP for In-Vehicle and Mobile Systems, Springer Science. Publishers, New York, 2005.
C. Bishop, Neural Networks for Pattern Recognition, Oxford: Clarendon Press, 1995
L. A. Zadeh, “Fuzzy Logic”, Computer, Vol. 1, No. 4, Pages: 83–93, 1988
L. Zhang. “Associative Memory and Fuzzy Neural Network for Speaker Recognition”, Unpublished Honor Year Project Report, School of Computer Engineering, Nanyang Technological University, Singapore 2004
H. Hui, J.H. Li, FJ. Song, and J. Widjaja, “ANFIS-based Fingerprint Matching Algorithm”, Optical Engineering, SPIE-International Society for Optical Engine, Volume: 43, Issue: 8, Aug. 2004. Pages: 1814–1819
N. Kawaguchi, S. Matsubara, K. Takeda, and F. Itakura, “Multimedia Data Collection of In-Car Speech Communication,” Proceedings 7th European Conference on Speech Communication and Technology, Sep. 2001. Pages: 2027–2030
J. Bengtsson, R. Johansson, and A. Sjogren, “Modeling of Drivers’ Behavior”. Proceedings of Advanced Intelligent Mechatronics. 2001 IEEE/ASME International Conference, Volume: 2, 8–12 July 2001 Pages: 1076–1081
H. Ohno, “Analysis and Modeling of Human Driving Behaviors Using Adaptive Cruise Control”, Industrial Electronics Society 2000, IECON 2000. 26th Annual Conference of the IEEE, Volume: 4, 22–28 Oct. 2000, Pages: 2803–2808
M. Chan, A. Herrera. and B. Andre, “Detection of changes in driving behaviour using unsupervised learning”, Systems. Man, and Cybernetics, 1994 IEEE International Conference on Humans. Information and Technology, Volume: 2, 2–5 Oct. 1994, Pages: 1979–1982
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Wahab, A., Keong, T.C., Abut, H., Takeda, K. (2007). Driver Recognition System Using FNN and Statistical Methods. In: Abut, H., Hansen, J.H.L., Takeda, K. (eds) Advances for In-Vehicle and Mobile Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-45976-9_2
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DOI: https://doi.org/10.1007/978-0-387-45976-9_2
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