A Study on Injury Prediction Method for Occupants Using Vehicle Body Deformation
車体変形を考慮した乗員傷害予測手法に関する研究
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- Available on the other site
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- Publication code
- 20214737
- Paper/Info type
- JSAE Transaction
Vol.52 No.5
- Pages
- 1125-1130(Total 6 p)
- Date of publication
- Sep 2021
- Publisher
- JSAE
- Language
- Japanese
Detailed Information
| Category(J) | 研究論文 Translation |
|---|---|
| Category(E) | ResearchPaper |
| Author(J) | 1) 國行 浩史, 2) 島 朋宏, 3) 吉田 隆人, 4) 北野 太一 |
| Author(E) | 1) Hiroshi Kuniyuki, 2) Tomohiro Shima, 3) Takato Yoshida, 4) Taichi Kitano |
| Affiliation(J) | 1) 公立諏訪東京理科大学, 2) 公立諏訪東京理科大学, 3) 公立諏訪東京理科大学, 4) 公立諏訪東京理科大学 |
| Abstract(J) | 先進衝突自動通報システムは乗員傷害予測精度が重要であり、車体変形の情報が必要であることが示唆されている。本研究では，米国の事故データを用いて側突時に評価すべき車体変形因子を抽出し、それを用いた傷害予測式の改善を検討した。その結果、ルーフ変形量を考慮することで従来モデルから改善することができた。 Translation |
| Abstract(E) | Accurate occupant injury prediction is important for Advance Automatic Collision Notification in accidents. In previous report, it was found that vehicle body deformation information was needed to improve injury prediction. This paper studied vehicle body deformation factor for occupant injury prediction in side impact crashes using an accident database in the U.S.(NASS-CDS) and constructed injury prediction model using those factors. As a result, roof deformation factor is found to be important for improving injury prediction model. The analytical method using photos of deformed vehicles was considered to measure the roof deformation in NASS-CDS accident cases. Roof deformations with 30 cm and above have a higher odds ratio of 2.944 compared to those below 30 cm. Therefore, this factor is considered to be included in injury prediction model with sensitivity improved to approximately 88% from the conventional model. |
