Citation

Terranova P, Perez MA. Accid. Anal. Prev. 2023; 193: e107292.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.aap.2023.107292

PMID

37742440

Abstract

In the last two decades, the number of registered motorcycles and mopeds in the US has nearly doubled, from 4.3 million in 2002 to 8.6 million in 2021 (Teoh, 2021). This increase has raised concerns regarding the potential hazards associated with these vehicles, as motorcycle riders represent 14% of all traffic fatalities despite only accounting for 3% of the total registered vehicles (NHTSA, 2021). Advanced Rider Assistance Systems (ARAS) could play an important role in addressing this issue, but standardized methodologies that estimate their potential benefit through injury prevention and mitigation are still needed (Savino et al., 2020). To conduct these types of analyses, e.g., Lucci et al. (2022), accurate injury prediction models that rely on rigorous crash retrospective analysis are necessary. Furthermore, while impact speed has received substantial attention in the literature as an injury predictor (Ding et al., 2019), impact angle and crash configuration--which have been demonstrated to be important injury-related factors (Xiao et al., 2020, Pai, 2009)--have not been thoroughly evaluated as injury predictors. To address this last limitation, the current investigation builds on McMurry's previous work on automated driving systems (McMurry et al., 2021), and introduces a novel approach to evaluate motorcycle injury risk in planar impacts from any direction, making it well-suitable for ARAS design and evaluation. Two primary research questions were examined in this investigation. (1) Are there any correlations between crash configuration, injury severity, and injured body parts? (2) Can the principal direction of force (PDOF, a quantification of impact angle) be used as a predictor of the injury severity in two-vehicle crashes?

Language: en

Keywords

Injury; Road safety; Crash analysis; Motorcycle; Powered-two wheeler (PTW)