A study on the performance of WordSID thorax module for thorax injury prediction in e-Bike rider based on real accident data.

Abstract

In this study, the analysis of 2824 vulnerable road users (VRU) accident data from China's FASS (Future mobile traffic Accident Scenario Study) database indicates that VRU side impacts are the most common collision scenarios. A typical accident (minivan-toeBike) from the FASS database was selected for accident reconstruction. WordSID thorax module has been employed to evaluate e-Bike rider thorax injuries and its kinematic difference has been investigated as well. The e-Bike rider was simulated by THUMS (Total Human Model for Safety). The kinematic data of THUMS thorax obtained from the accident reconstruction were used as the boundary conditions of WorldSID dummy thorax to simulate the collision between thorax and accident vehicle, and the deflection of WorldSID dummy thorax was outputted and compared with THUMS rib deflection. The accident reconstruction results using the THUMS model match the human thorax injury conditions. The WorldSID thorax module can effectively replicate the motion of the thorax and predict thorax injury conditions in the minivan-to-eBike collision, but it does not reflect the bending of the spine during the e-Bike rider impact process, nor does it consider the impact of forces on the head, neck, and lower limbs. Therefore, further improvements are still necessary.