Ford Motor Company, Dearborn, Michigan 48121, USA.
Traffic Inj Prev. 2010 Aug;11(4):371-81. doi: 10.1080/15389581003739685.
The numerical basis for assigning star ratings in the next-generation USA New Car Assessment Program (NCAP) for frontal impacts was assessed. That basis, the Combined Probability of Injury, or CPI, is the probability of an occupant sustaining an injury to any of the specified body regions. For an NCAP test, a CPI value is computed by (a) using risk curves to convert body-region responses from a test dummy into body-region risks and (b) using a theoretical, overarching CPI equation to convert those separate body-region risks into a single CPI value. Though the general concept of applying a CPI equation to assign star ratings has existed since 1994, there will be numerous changes to the 2011 frontal NCAP: there will be two additional body regions (n = 4 vs. 2), the injury probabilities will be evaluated for lower-severity (more likely) injury levels, and some of the occupant responses will change. These changes could yield more disperse CPIs that could yield more disperse ratings. However, the reasons for this increased dispersion should be consistent with real-world findings. Related assessments were the topic of this two-part study, focused on drivers.
In Part 1, the CPI equation was assessed without applying risk curves. Specifically, field injury probabilities for the four body regions were used as inputs to the CPI equation, and the resulting equation-produced CPIs were compared with the field CPIs. In Part 2, subject to analyses of test dummy responses from recent NCAP tests, the effect of risk curve choice on CPIs was assessed. Specifically, dispersion statistics were compared for CPIs based on various underlying risk curves applied to data from 2001-2005 model year vehicles (n = 183).
From Part 1, the theoretical CPI equation for four body regions demonstrated acceptable fidelity when provided field injury rates (R(2)= 0.92), with the equation-based CPIs being approximately 12 percent lower than those of ideal correlation. From Part 2, the 2011 NCAP protocol (i.e., application of a four-body-region CPI equation whose inputs were from risk curves) generally increased both the CPIs and their dispersion relative to the current NCAP protocol. However, the CPIs generally increased due to an emphasis on neck injury-an emphasis not observed in real-world crashes. Subject to alternative risk curves for the neck and chest, again there was increased dispersion of the CPIs, but the unrealistic emphasis on the neck was eliminated. However, risk estimates for the knee/thigh/hip (KTH) for NCAP-type events remained understated and did not fall within the confidence bands of the field data. Accordingly, KTH risk estimation is an area for future research.
评估下一代美国新车评估计划(NCAP)正面碰撞中星级评定的数值基础。该基础是综合损伤概率(CPI),即乘员在任何指定身体部位受伤的概率。对于 NCAP 测试,CPI 值通过以下方式计算:(a)使用风险曲线将测试假人身体部位的反应转换为身体部位风险,(b)使用理论上的总体 CPI 方程将这些单独的身体部位风险转换为单个 CPI 值。虽然自 1994 年以来,应用 CPI 方程来分配星级的一般概念就已经存在,但 2011 年正面 NCAP 将有许多变化:将增加两个额外的身体部位(n = 4 比 2),将评估较低严重程度(更可能)损伤水平的损伤概率,并且一些乘员反应将发生变化。这些变化可能导致 CPI 分布更加分散,从而导致评级更加分散。然而,这种分散的原因应该与实际情况一致。相关评估是本研究的主题,重点是驾驶员。
在第 1 部分中,不应用风险曲线评估 CPI 方程。具体来说,将四个身体部位的现场损伤概率用作 CPI 方程的输入,并且将产生的方程产生的 CPI 与现场 CPI 进行比较。在第 2 部分中,根据最近 NCAP 测试的测试假人响应分析,评估了风险曲线选择对 CPI 的影响。具体来说,比较了基于各种基础风险曲线的数据的 CPI 分散统计数据,这些风险曲线应用于 2001-2005 年车型年车辆的数据(n = 183)。
从第 1 部分可以看出,当提供现场损伤率时,四个身体部位的理论 CPI 方程具有可接受的保真度(R(2)= 0.92),基于方程的 CPI 比理想相关性低约 12%。从第 2 部分可以看出,2011 年 NCAP 协议(即,应用输入来自风险曲线的四部位 CPI 方程)通常会增加 CPI 及其分散度,与当前 NCAP 协议相比。然而,CPI 的增加主要是由于对颈部损伤的重视 - 这在实际碰撞中并未观察到。对于颈部和胸部的替代风险曲线,CPI 的分散度再次增加,但对颈部的不切实际的重视被消除了。然而,对于 NCAP 类型事件的膝盖/大腿/臀部(KTH)的风险估计仍然偏低,并且不在现场数据的置信带内。因此,KTH 风险估计是未来研究的一个领域。