論文

査読有り
2013年

Prediction of drowsy driving using behavioral measures of drivers - Change of neck bending angle and sitting pressure distribution

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Atsuo Murata
  • ,
  • Taiga Koriyama
  • ,
  • Takuya Endoh
  • ,
  • Takehito Hayami

8025
1
開始ページ
78
終了ページ
87
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1007/978-3-642-39173-6_10
出版者・発行元
Springer

Recently, in Japan, the percentage of the death toll in traffic accidents due to drowsy driving is the most dominant in all death tolls in traffic accidents. Therefore, it is essential for automotive manufacturers to develop a warning system of drowsy driving. A lot of studies are conducted to prevent traffic accident due to drowsy driving, and make an attempt to assess drowsiness by physiological measures such as EEG. However, it is difficult to use such equipment for predicting drowsiness, because it is difficult to equip an automotive cockpit with such equipment due to expensiveness and measurement noise. As more convenient measure used to predict drowsiness, it was examined whether the neck bending angle and the sitting pressure distribution could be used to discriminate the arousal level. The effectiveness of these convenient measures was experimentally assessed. In order to prevent traffic accidents due to drowsy driving, an attempt was made to predict drowsiness (low arousal state) using the change of neck bending angle and sitting pressure distribution. As a result, these measures were found to be useful for evaluating arousal level and predicting arousal level in advance. © 2013 Springer-Verlag.

リンク情報
DOI
https://doi.org/10.1007/978-3-642-39173-6_10
DBLP
https://dblp.uni-trier.de/rec/conf/hci/MurataKEH13
URL
http://dblp.uni-trier.de/db/conf/hci/hci2013-22.html#conf/hci/MurataKEH13
ID情報
  • DOI : 10.1007/978-3-642-39173-6_10
  • ISSN : 0302-9743
  • ISSN : 1611-3349
  • DBLP ID : conf/hci/MurataKEH13
  • SCOPUS ID : 84879894105

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