Gabauer D J, Gabler H C
Center for Injury Biomechanics, Virginia Tech, Blacksburg, VA, USA.
Annu Proc Assoc Adv Automot Med. 2006;50:57-71.
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.
本研究比较了ΔV和乘员碰撞速度（OIV，一种衡量碰撞严重程度的指标）在预测现实世界碰撞中乘员受伤情况方面的能力。大部分分析是使用191个案例进行的，这些案例包含来自事件数据记录器（EDR）的车辆运动学数据，并与详细的乘员受伤信息相匹配。使用二元逻辑回归为所有数据、系安全带子集和未系安全带子集生成受伤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相比ΔV没有显著的预测优势。
