Injury Prediction Model for Automatic Collision Notification Based on Japanese Accident Data

• 吉田 傑

  (株)本田技術研究所

• 長谷川 卓

  (株)本田技術研究所

• 富永 茂

  日本大学

• 西本 哲也

  日本大学

Bibliographic Information

Other Title

• 事故データによる傷害予測に関する研究
• ジコ データ ニ ヨル ショウガイ ヨソク ニ カンスル ケンキュウ

Abstract

The estimation results of passenger injury risk from quantitative information recorded by SRS unit are useful both of emergency activity and medical treatment service after accidents. Injury prediction model for estimating occupant′s serious injury risk based on Japanese accident data base using logistic regression modeling technique. Risk factors using in this model are delta-V, crash direction, belt use, multiple impact and occupant′s age. Serious injury risk of a total of 240 cases of crash mode was estimated by the model. The comparison has done between estimated serious injury risk and actual injury of 22 cases of Japanese in-depth accident data. The results show that injury prediction model has a good possibility for predicting injury risk based on onboard data and its application for post crash safety.

Journal

• Transactions of Society of Automotive Engineers of Japan

  Transactions of Society of Automotive Engineers of Japan 43 (2), 275-280, 2012

  Society of Automotive Engineers of Japan

Keywords

• Safety
• Automatic collision notification
• Injury prediction
• Serious injury risk
• Field triage

Details

• CRID: 1390001204615008768
• NII Article ID: 130004515783
• NII Article ID: 40019253876
• NII Book ID: AN00105913
• DOI: 10.11351/jsaeronbun.43.275
• ISSN: 18830811
• ISSN: 02878321
• NDL BIB ID: 023631692
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I023631692
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed