Identification of Cognitive Distraction Using Physiological Features for Adaptive Driving Safety Supporting System
Joint Authors
Kawanaka, Haruki
Bhuiyan, Md. Shoaib
Miyaji, Masahiro
Oguri, Koji
Source
International Journal of Vehicular Technology
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-08
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Telecommunications Engineering
Electronic engineering
Abstract EN
It was identified that traffic accidents relate closely to the driver’s mental and physical states immediately before the accident by our questionnaire survey.
Distraction is one of the key human factors involved in traffic accidents.
We reproduced driver’s cognitive distraction on a driving simulator by means of imposing cognitive loads such as doing arithmetic and having conversation while driving.
Visual features such as test subjects’ gaze direction, pupil diameter, and head orientation, together with heart rate from ECG, were used in this study to detect the cognitive distraction.
We improved detection accuracy obtained from earlier studies by using the AdaBoost.
This paper also suggests a multiclass identification using Error-Correcting Output Coding, which can identify the degree of cognitive load.
Finally, we verified the effectiveness of the multiclass identification by conducting a series of experiments.
All these aimed at developing a constituent technology of a driver monitoring system that is expected to create adaptive driving safety supporting system to lower the number of traffic accidents.
American Psychological Association (APA)
Kawanaka, Haruki& Miyaji, Masahiro& Bhuiyan, Md. Shoaib& Oguri, Koji. 2013. Identification of Cognitive Distraction Using Physiological Features for Adaptive Driving Safety Supporting System. International Journal of Vehicular Technology،Vol. 2013, no. 2013, pp.1-18.
https://search.emarefa.net/detail/BIM-500472
Modern Language Association (MLA)
Kawanaka, Haruki…[et al.]. Identification of Cognitive Distraction Using Physiological Features for Adaptive Driving Safety Supporting System. International Journal of Vehicular Technology No. 2013 (2013), pp.1-18.
https://search.emarefa.net/detail/BIM-500472
American Medical Association (AMA)
Kawanaka, Haruki& Miyaji, Masahiro& Bhuiyan, Md. Shoaib& Oguri, Koji. Identification of Cognitive Distraction Using Physiological Features for Adaptive Driving Safety Supporting System. International Journal of Vehicular Technology. 2013. Vol. 2013, no. 2013, pp.1-18.
https://search.emarefa.net/detail/BIM-500472
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-500472