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Journal Article

Citation

Shrinivas V, Bastien C, Davies H, Daneshkhah A, Hardwicke J. Transp. Eng. (Amsterdam) 2023; 11: e100158.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.treng.2022.100158

PMID

unavailable

Abstract

Pedestrians account for 26% of all traffic fatalities worldwide. According to in-depth collision databases, around 3500 variables can affect the outcome of a collision, making it crucial to establish the relationship between each variable and the outcome. To date, there is no method defined to assess these variables' relevance other than a statistical correlation, which can sometimes lead to reasonable conclusions, but only under specific circumstances. This article addresses this issue by first conducting a literature review to determine all relevant variables, followed by developing a variable selection criterion to select crucial variables, and then conducting a meta-analysis to quantify these relationships. Epidemiological studies published between 1990 and 2022 were examined, including 93 papers from 19 different nations that considered 904,655 pedestrian collisions. Of the 204 variables that were extracted from these studies, 152 were examined using the variable selection criterion, and 68 were found to be significant. Of these, 20 were included in the meta-analysis, which combined odds ratios to aggregate the effect of a variable across various studies, thus removing study-specific conclusions. This study makes a compelling argument that using statistical correlation by itself is insufficient to determine a variable's significance. The proposed method is an objective way to distinguish the variables for stakeholders and identify their relevance. This study offers a definitive list of the 15 characteristics that must be present in any pedestrian-to-vehicle collision databases, as well as a list of 53 variables that require additional investigation, allowing for appropriate actions for safer roads.


Language: en

Keywords

Accident; Influential parameters; Injury severity; Meta-analysis; Pedestrian; Systematic review

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