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Injury Risk Functions in Frontal Impacts Using Data from Crash Pulse Recorders

机译:使用碰撞脉冲记录器的数据在正面碰撞中造成伤害的风险函数

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摘要

Knowledge of how crash severity influences injury risk in car crashes is essential in order to create a safe road transport system. Analyses of real-world crashes increase the ability to obtain such knowledge.The aim of this study was to present injury risk functions based on real-world frontal crashes where crash severity was measured with on-board crash pulse recorders.Results from 489 frontal car crashes (26 models of four car makes) with recorded acceleration-time history were analysed. Injury risk functions for restrained front seat occupants were generated for maximum AIS value of two or greater (MAIS2+) using multiple logistic regression. Analytical as well as empirical injury risk was plotted for several crash severity parameters; change of velocity, mean acceleration and peak acceleration. In addition to crash severity, the influence of occupant age and gender was investigated.A strong dependence between injury risk and crash severity was found. The risk curves reflect that small changes in crash severity may have a considerable influence on the risk of injury. Mean acceleration, followed by change of velocity, was found to be the single variable that best explained the risk of being injured (MAIS2+) in a crash. Furthermore, all three crash severity parameters were found to predict injury better than age and gender. However, age was an important factor. The very best model describing MAIS2+ injury risk included delta V supplemented by an interaction term of peak acceleration and age.
机译:为了创建安全的道路运输系统,必须了解碰撞严重程度如何影响车祸中受伤的风险。对真实世界的碰撞进行分析可以提高获得此类知识的能力。本研究的目的是基于真实世界的正面碰撞提供伤害风险功能,其中使用车载碰撞脉冲记录仪测量碰撞的严重性.489辆正面汽车的结果分析了具有记录的加速时间历史记录的撞车事故(26个模型的四个汽车品牌)。使用多重logistic回归分析得出,对于受约束的前排座位乘员而言,受伤风险函数的最大AIS值等于或大于2(MAIS2 +)。绘制了几个碰撞严重性参数的分析性和经验性伤害风险;速度,平均加速度和峰值加速度的变化。除撞车严重程度外,还研究了乘员年龄和性别的影响,发现伤害风险与撞车严重程度之间存在强烈的依赖性​​。风险曲线反映出碰撞严重程度的微小变化可能会对伤害风险产生重大影响。发现平均加速度,然后是速度变化,是最能说明事故发生时受伤的风险(MAIS2 +)的唯一变量。此外,发现所有三个碰撞严重性参数比年龄和性别更好地预测伤害。但是,年龄是重要因素。描述MAIS2 +伤害风险的最好模型包括delta V,并加上峰值加速度和年龄的相互作用项。

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