Morphed Human Body Models for Vehicle Safety

This technical report investigates the use of morphed human body models (HBMs) to predict population injury outcomes in vehicle crashes. The study focuses on the number of HBMs required to accurately represent occupant variability and rib fracture risk during frontal and side crashes. It employs regression methods, including regularized linear regression and Gaussian process regression, to create metamodels that can predict rib fracture risk based on occupant characteristics such as sex, height, and weight. The findings suggest that using 25 individuals of each sex is sufficient for modeling population rib fracture risk outcomes. Additionally, an optimization method is introduced to select representative individuals for various crash scenarios. The report emphasizes the potential of HBMs to enhance vehicle safety evaluations by incorporating occupant diversity, thereby improving the design of safety systems. The methodology discussed could be extended to other crash types and vehicles, contributing to future research in occupant safety.