Pedestrian safety assessments via full human body models and advanced injury criteria - Duarte, Marcelo R. G.; Duddeck, Fabian; Raponi, Elena; Alves, Marcilio (Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2023)
Understanding the dynamics of car-to-pedestrian-collisions (CPCs) is critical to reducing fatalities. Data collected from traffic accidents are insufficient in quantity and quality to support the reconstruction of the kinematics and thus to draw empirical conclusions. Due to the high costs associated with conducting physical CPC tests, numerical simulations using the finite element method play an important role in better understanding the human biological response to these events. Rapid advances in computational efficiencies have enabled the use of increasingly complex models to evaluate pedestrian safety. In this work, we show that CPC simulations using full finite element human body models (HBMs) enable results that cannot be obtained with conventional dummy models. More specifically, we report injuries predicted in pedestrian femur simulations (such as bone fractures and tendon ruptures) and evaluate the use of different criteria to predict head injuries, such as maximum rotational acceleration, maximum linear acceleration, head injury criterion, and brain maximum principal strain. To this end, we consider CPCs using an example analysis for a sedan (public domain Toyota Yaris) traveling at 40 km/h and impacting four different human body models: a 50th and a 95th percentile adult male, a 5th percentile adult female, and a 10-year-old child. HBMs can be used to define advanced injury criteria that can account for many more factors than standard indices. Our work suggests that current pedestrian safety regulations are inadequate and therefore paves the way for the use of novel and advanced injury criteria through the use of HBMs to enable the design of safer vehicles.