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Erschienen in: Artificial Life and Robotics 1/2015

01.03.2015 | Original Article

Detection of driver inattention from fluctuations in vehicle operating data

verfasst von: Shizuka Bando, Akio Nozawa

Erschienen in: Artificial Life and Robotics | Ausgabe 1/2015

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Abstract

Drivers have to drive their vehicle safely by properly using steering, throttling, and braking controls. However, drivers do not always maintain their concentration on managing their vehicles. The primary causes of driver inattention are distracting activities and drowsiness. Such driver inattention is thought to be one of the major causes of traffic accidents, and so the objective of the present study is to develop a new method for detecting driver inattention from fluctuations in vehicle operating data. Steering and throttle operations while driving were measured by acceleration sensors and respiration rhythm and an electrocardiogram were measured as physiological indices. The result of correlation between the estimative value, peaks and exponent values of frequency characteristics of vehicle operating data, and physiological indices, an association of sympathetic nervous system activation was indicated. The performance of detecting normal state, under cognitive stress state, and drowsy state by this method was an average correct discriminatory rate of 70 %.

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Metadaten
Titel
Detection of driver inattention from fluctuations in vehicle operating data
verfasst von
Shizuka Bando
Akio Nozawa
Publikationsdatum
01.03.2015
Verlag
Springer Japan
Erschienen in
Artificial Life and Robotics / Ausgabe 1/2015
Print ISSN: 1433-5298
Elektronische ISSN: 1614-7456
DOI
https://doi.org/10.1007/s10015-014-0191-8

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