Gabauer Douglas J, Gabler Hampton C
Virginia Tech-Wake Forest Center for Injury Biomechanics, 100F Randolph Hall MC 0238, Blacksburg, VA 24061, USA.
Accid Anal Prev. 2008 Mar;40(2):548-58. doi: 10.1016/j.aap.2007.08.011. Epub 2007 Sep 17.
The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk curves were generated using binary logistic regression for belted and unbelted data subsets. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV and ASI were found to offer no significant predictive advantage over the simpler delta-V.
乘员碰撞速度（OIV）和加速度严重程度指数（ASI）是用于评估涉及路边安全硬件（如护栏）的实车碰撞试验中乘员受伤风险的相互竞争的碰撞严重程度衡量指标。Delta-V，即车辆速度的最大变化量，是现实世界碰撞中碰撞严重程度的传统指标。本研究比较了OIV、ASI和Delta-V在现实世界正面碰撞中区分严重和非严重乘员伤害的能力。来自事件数据记录器（EDR）的车辆运动学数据与180起现实世界碰撞的详细乘员伤害信息相匹配。使用二元逻辑回归为系安全带和未系安全带的数据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量并进行单独的ROC曲线分析，发现计算量更大的OIV和ASI相对于更简单的Delta-V没有显著的预测优势。
