Citation

Hou L, Peng Y, Sun D. Accid. Anal. Prev. 2020; 146: e105725.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.aap.2020.105725

PMID

32805462

Abstract

Human necks are vulnerable in train collision accidents. To design a safer cab workspace, the driver neck injury mechanism should be investigated first. In this study, this issue is addressed by investigating how neck injuries are influenced by the cab workspace dimensions. The driver-console-seat dynamic models are developed to quantify the neck injuries. The three-pivot head-neck-upper torso model is used to evaluate the relative rotation angle between head and upper torso (β+γ). The injury mechanism with the larger (β+γ) value results in more severe neck injuries. The decision tree model is established to explore the most important cab workspace dimensional parameter. The driver submarining posture (the driver exhibits the tendency of sliding down from the seat after contacting the console) generates more (β+γ) value than the flipping over behavior (the driver contacts the console and the upper body continues to move over the top of the console). Four neck injury mechanisms are classified, in which the chest-first impact mechanisms are more dangerous than the knee-first impact mechanisms. The distance between the console edge and knee bolster has the greatest effect on the neck injury. This parameter determines the injury mechanism type as it influences the first contact region of the driver. The distance between the console and seat and the pedal height are the secondary dominant attributes. These three parameters should be considered preferentially for establishing driver protection measures.

Language: en

Keywords

Data mining; Cab workspace; Human neck injury; Impact injury mechanism; Train collision