Prediction of pedestrian injuries in motorcycle-pedestrian crashes using THUMS FE-HBM

Abstract

This study focuses on the high fatality rates associated with motorcycles as a mode of transport in India, surpassing trucks and cars. Over the last decade, motorcycle-related fatalities have seen a staggering increase of 232%. The Finite Element-Human Body Models (FE-HBM) have been validated for occupants and pedestrians in car crashes. However, the performance against motorcycle impact is lacking in the literature. The primary objective of this research is to evaluate the THUMS model for injury prediction in motorcycle-pedestrian impact scenarios using a finite element motorcycle model of a widely used two wheeler in India. The motorcycle model is initially validated against a rigid wall, after which it is utilised to predict injuries in real-life motorcycle-pedestrian crash scenarios. Through multi-body simulations, crucial pre-crash parameters such as pedestrian orientation, offset and speed are estimated for five actual motorcycle-pedestrian crashes. Subsequently, finite element simulations are conducted to validate the model’s accuracy in predicting pedestrian injuries. The study closely predicts the occurrence and location of fractures in long bones using strain-based criteria in four out of five cases.