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.

The novel reconstruction process was developed to address these two constraints using a pair of subsequent studies presented herein as individual chapters. First, a generic simplified vehicle model was developed and tuned to mimic the frontal crash environment of a specific vehicle model using crash test data. Subsequently, FE reconstructions of two CIREN frontal crash events were performed. Regional level injury metrics based on occupant kinematics were implemented into the Total HUman Model for Safety (THUMS) and analyzed to predict injury risks as a function of the occupant’s pre-crash position within the occupant compartment.

The results from these studies demonstrate the ability to reconstruct a wide array of real world frontal MVCs and predict regional level injury risks and variability due to occupant position. The novel MVC reconstruction paradigm will facilitate future injury metric and risk function development based on living human subjects in real world MVCs.