Simulation of occupant kinematics and injury risk assessment in a passenger bus rollover

Jongpradist, Pattaramon; Laklaem, Thanapol; Thangtaweesuk, Prem; Nimmawit, Pakin

doi:10.1109/autosafe.2018.8373312

Cited by 1 publication

(1 citation statement)

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“…The rapid development of computer simulation technology has increased the use of simulation software, such as MADYMO, HyperMesh, and LS-DYNA, as alternative methods to generate sufficient injury data for investigations on injury prediction [13][14][15]. The reliability of simulation models impacts the effectiveness and practicability of simulation-based injury prediction algorithms directly.…”

Section: Introductionmentioning

confidence: 99%

Injury prediction algorithm for rear‐seat occupants in advanced automatic crash notification systems

Lü

Liu

Shu

et al. 2021

IET Intelligent Trans Sys

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An advanced automatic crash notification (AACN) system can predict the injuries of a vehicle's occupants when the vehicle is involved in a collision accident. The rear‐seat occupants are at significant risk in collision accidents owing to an inferior protection system and the absence of mandatory seat belt laws. However, only a few studies have focused on the injury prediction for rear‐seat occupants, which can be used in AACN system. Therefore, an injury prediction algorithm is proposed for rear‐seat occupants. Initially, a rear‐seat occupant simulation model is established and verified and the relationship between the head, neck, and chest injury levels and velocity variation is examined. Then, a rear‐seat occupant injury prediction algorithm is developed and AACN terminal is constructed to analyse the effects of the algorithm. The comparison of the obtained results with actual accident data validated that the proposed algorithm can effectively evaluate the injury levels of rear‐seat occupants. The study findings can enhance the prediction accuracy of all occupants’ injury levels based on their positions inside the vehicle and improve the efficiency of rescue operations, particularly in the case of rear‐seat occupants.

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Section: Introductionmentioning

confidence: 99%