Driver recognition system using FNN and statistical methods

Abdul Rahman, Abdul Wahab and Tan, Chin Keong and Abut, Huseyin and Takeda, Kazuya (2007) Driver recognition system using FNN and statistical methods. In: Advances for in-vehicle and mobile systems. Challenges for International Standards . Springer US, Spring Street, USA, pp. 11-23. ISBN 978-0-387-33503-2 (P), 978-0-387-45976-9 (O)

PDF - Published Version Restricted to Repository staff only Download (1MB) | Request a copy

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 biometric 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.

Item Type:	Book Chapter
Additional Information:	6145/38176
Uncontrolled Keywords:	driving profile, behavioral modeling, verification and identification, soft computing, accelerator and brake pressure, dynamic driver profiling
Subjects:	H Social Sciences > HA Statistics
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Prof Abdul Wahab Abdul Rahman
Date Deposited:	11 Sep 2014 16:22
Last Modified:	04 Jun 2020 15:37
URI:	http://irep.iium.edu.my/id/eprint/38176

Actions (login required)

View Item