イクノ ソウイチロウ
Soichiro Ikuno
生野 壮一郎 所属 コンピュータサイエンス学部 コンピュータサイエンス学科 職種 教授 |
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言語種別 | 英語 |
発行・発表の年月 | 2022/12 |
形態種別 | 学術論文 |
査読 | 査読あり |
標題 | Pre-braking Behaviors Analysis based on Hilbert–Huang Transform |
執筆形態 | 共著 |
掲載誌名 | CCF Transactions on Pervasive Computing and Interaction |
掲載区分 | 国外 |
出版社・発行元 | Springer |
著者・共著者 | Wu, B., Zhu, Y., Dong, R., Sato, K., Ikuno, S., Nishimura, S., Jin, Q. |
概要 | Previous studies have shown that about 90% of traffic accidents are due to human error, which means that human factors may affect a driver's braking behaviors and thus their driving safety, especially when the driver makes a braking motion. However, most studies have mounted sensors on the brake pad, ignoring to some extent an analysis of the driver's behavior before the brake pad is pressed (pre-braking). Therefore, to determine the effect of different human factors on drivers' pre-braking behaviors, this study focused on analyzing drivers' local joints (knee, ankle, and toe) by a motion capture device. A Hilbert–Huang Transform (HHT)-based local human body movement analysis method was used to decompose the realistic complex pre-braking actions into sub-actions such as intrinsic mode functions (IMF1, IMF2, etc.). Analysis of the results showed that IMF1 is a common and necessary action when pre-braking for all drivers, and IMF2 may be the safety assurance action that allows right-foot transverse movement at the beginning part of the pre-braking process. We also found that the experienced, male, and Phys.50 groups may have consistent characteristics in the HHT scheme, which could mean that such drivers would have better performance and efficiency during the pre-braking process. The results of this study will be useful in decomposing and discerning the specific actions that lead to accidents, providing insights into driver training for novice drivers, and guiding the construction of daily automated driver assistance or accident prevention systems (advanced driver assistance systems, ADASs). |