Exploring factors affecting the injury severity of highway-rail grade crossing crashes during the COVID-19 pandemic

The outbreak of COVID-19 pandemic could alter the injury severity pattern of highway-rail grade crossing (HRGC) crashes. To compare factors affecting injury severities before and during the pandemic, HRGC crashes occurring between 2018 and 2021 in the United States were collected. A random parameters logit model with heterogeneity in means was developed to investigate the impact of multiple factors during the pandemic (2020-2021). Besides, a multinomial logit model was developed for the pre-pandemic (2018-2019) crashes. The present study indicates that the existence of old drivers and illuminated crossings generated random parameters with heterogeneity in means during the pandemic, which were affected by the driver in vehicle, estimated train speed, and crossing AADT indicators. As for the pre-pandemic period, no significant random parameters and unobserved heterogeneity were captured. Significant variables also differed markedly between these two periods, with no significant driver-related or vehicle-related indicators identified from 2018 to 2019.

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Publication Details

Journal
Transportation Letters
Published
2024-08-22
DOI
https://doi.org/10.1080/19427867.2024.2392062
Citations
3
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
1.09
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article

Exploring factors affecting the injury severity of highway-rail grade crossing crashes during the COVID-19 pandemic

Min Xu, Qiaoqiao Ren
3 citations
Transportation Letters
Traffic and Road Safety
1.09
article

Exploring factors affecting the injury severity of highway-rail grade crossing crashes during the COVID-19 pandemic

Min Xu, Qiaoqiao Ren
article en
3 citations

Abstract

The outbreak of COVID-19 pandemic could alter the injury severity pattern of highway-rail grade crossing (HRGC) crashes. To compare factors affecting injury severities before and during the pandemic, HRGC crashes occurring between 2018 and 2021 in the United States were collected. A random parameters logit model with heterogeneity in means was developed to investigate the impact of multiple factors during the pandemic (2020-2021). Besides, a multinomial logit model was developed for the pre-pandemic (2018-2019) crashes. The present study indicates that the existence of old drivers and illuminated crossings generated random parameters with heterogeneity in means during the pandemic, which were affected by the driver in vehicle, estimated train speed, and crossing AADT indicators. As for the pre-pandemic period, no significant random parameters and unobserved heterogeneity were captured. Significant variables also differed markedly between these two periods, with no significant driver-related or vehicle-related indicators identified from 2018 to 2019.

Transportation LettersVol. 17(5)
Hong Kong Polytechnic University (HK)
Good health and well-being
Openalex Percentile: Top 24%
Traffic and Road Safety
1.09
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