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Development of point mass occupant injury criteria using event data recorders.

机译:使用事件数据记录器来开发点状乘员伤害准则。

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This paper presents an estimate of the probability of serious occupant injury in frontal crashes based on vehicle kinematics information. Occupant injury risk is developed by modeling the human as a point mass and computing the occupant impact velocity (OIV) using the flail space model. Event Data Recorder data provide vehicle kinematics information for real world crashes with known injury outcomes. A data set of 211 cases is used for methodology development and preliminary insight to the injury prediction capability of the metric. Using logistic regression, injury risk curves are generated for all data, a belted occupant subset and an unbelted occupant subset. Based on the models, an occupant restrained by an airbag and safety belt is found to have a lower risk of injury than an occupant only restrained by an airbag. A 50% probability of serious injury is found to correspond to an OIV of 11.2 m/s and 15.9 m/s for unbelted and belted occupants, respectively.
机译:本文提出了基于车辆运动学信息的正面碰撞中严重乘员受伤概率的估计。通过将人建模为点质量并使用连ail空间模型计算乘员撞击速度(OIV),可以开发乘员伤害风险。事件数据记录器数据为已知伤害结果的现实世界碰撞提供车辆运动学信息。 211个案例的数据集用于方法开发和对度量指标的伤害预测能力的初步了解。使用逻辑回归,将为所有数据,安全带乘员子集和未系安全带的乘员子集生成伤害风险曲线。根据这些模型,发现受安全气囊和安全带约束的乘员比仅受安全气囊约束的乘员的受伤风险低。发现未系安全带和安全带的乘员发生严重伤害的概率为50%,分别对应于11.2 m / s和15.9 m / s的OIV。

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