Comparison of delta-v and occupant impact velocity crash severity metrics using event data recorders.

D J Gabauer, H C Gabler
{"title":"Comparison of delta-v and occupant impact velocity crash severity metrics using event data recorders.","authors":"D J Gabauer,&nbsp;H C Gabler","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>This research compares the ability of delta-V and the occupant impact velocity (OIV), a competing measure of crash severity, to predict occupant injury in real world collisions. A majority of the analysis is performed using 191 cases with vehicle kinematics data from Event Data Recorders (EDRs) matched with detailed occupant injury information. Cumulative probability of injury risk curves are generated using binary logistic regression for all data, a belted subset, and an unbelted subset. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV is found to offer no significant predictive advantage over delta-V.</p>","PeriodicalId":80490,"journal":{"name":"Annual proceedings. Association for the Advancement of Automotive Medicine","volume":"50 ","pages":"57-71"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3217488/pdf/aam50_p055.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual proceedings. Association for the Advancement of Automotive Medicine","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This research compares the ability of delta-V and the occupant impact velocity (OIV), a competing measure of crash severity, to predict occupant injury in real world collisions. A majority of the analysis is performed using 191 cases with vehicle kinematics data from Event Data Recorders (EDRs) matched with detailed occupant injury information. Cumulative probability of injury risk curves are generated using binary logistic regression for all data, a belted subset, and an unbelted subset. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV is found to offer no significant predictive advantage over delta-V.

使用事件数据记录仪比较delta-v和乘员冲击速度碰撞严重性指标。
这项研究比较了delta-V和乘员冲击速度(OIV)的能力,OIV是一种碰撞严重程度的竞争指标,用于预测现实世界碰撞中乘员的伤害。大部分分析使用了191个案例的车辆运动学数据,这些数据来自事件数据记录仪(EDRs),与详细的乘员受伤信息相匹配。使用二元逻辑回归对所有数据、系带子集和未系带子集生成伤害风险曲线的累积概率。通过比较可用的拟合统计数据并进行单独的ROC曲线分析,发现计算量更大的OIV与delta-V相比没有显著的预测优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信