Steering wheel motion analysis for detection of the driver's drowsiness

Authors:
Daniel Haupt;Petr Honzik;Peter Raso;Ondrej Hyncica
Affiliations:
Department of Control and Instrumentation, Brno University of Technology, Brno, Czech Republic;Department of Control and Instrumentation, Brno University of Technology, Brno, Czech Republic;Department of Control and Instrumentation, Brno University of Technology, Brno, Czech Republic;Department of Control and Instrumentation, Brno University of Technology, Brno, Czech Republic
Venue:
MMES'11/DEEE'11/COMATIA'11 Proceedings of the 2nd international conference on Mathematical Models for Engineering Science, and proceedings of the 2nd international conference on Development, Energy, Environment, Economics, and proceedings of the 2nd international conference on Communication and Management in Technological Innovation and Academic Globalization
Year:
2011

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Abstract

Reliable system for driver's drowsiness recognition is the aim of many studies. Unfortunately, majority of researchers work with data acquired in laboratory with ideal or simulated conditions. Therefore it is difficult to implement their results to real car and prove its reliability and accuracy. The analyzed data in this paper is acquired from real traffic and therefore it contains all disadvantages partially modeled in laboratory. For data acquisition has been chosen in-direct measurement from car CAN bus in order to not affect the driver. All data are preprocessed according to assumptions about driver's behavior and transformed to frequency domain by means of orthogonal transform (STFT, CWT and DWT). Subsequently, data is analyzed by data mining methods including features extraction and filter feature selection. The performance of the features is measured by the area under the receiver operating characteristic.