Driver Injury Metric and Risk Variability as a Function of Occupant Position in Real World Motor Vehicle Crashes
Motor vehicle crashes (MVCs) are a worldwide public health concern, resulting in annual totals of approximately 1.24 million deaths and 20-50 million injured occupants. Real world crash reconstructions using finite element (FE) vehicle and human body models (HBMs) have the potential to elucidate injury mechanisms, predict injury risk, and evaluate injury mitigation system effectiveness, ultimately leading to a reduced risk of fatality and severe injury in MVCs. The purpose of the work presented herein was to create a novel framework for FE frontal MVC reconstruction and injury analysis considering two primary constraints: (1) a shortage of specific FE vehicle models and (2) uncertainty in the case occupant’s position immediately before the crash event.
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