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Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach

The purpose of this research is (1) to investigate the relationship between crash severity and the age and gender of the at-fault driver, the socio-economic characteristics of the surrounding environment, and road conditions, and (2) to explain the probability of a bodily injury crash, including fat...

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Autores principales: Lee, Dongkwan, Guldmann, Jean-Michel, von Rabenau, Burkhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9915014/
https://www.ncbi.nlm.nih.gov/pubmed/36767700
http://dx.doi.org/10.3390/ijerph20032338
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author Lee, Dongkwan
Guldmann, Jean-Michel
von Rabenau, Burkhard
author_facet Lee, Dongkwan
Guldmann, Jean-Michel
von Rabenau, Burkhard
author_sort Lee, Dongkwan
collection PubMed
description The purpose of this research is (1) to investigate the relationship between crash severity and the age and gender of the at-fault driver, the socio-economic characteristics of the surrounding environment, and road conditions, and (2) to explain the probability of a bodily injury crash, including fatality, with the alternative being a property damage only crash. In contrast to earlier research that has focused on young and old drivers, age is considered here on its lifetime continuum. A logit model is adopted and the gender and age of the at-fault drivers are part of the independent explanatory variables. The unit of analysis is the individual crash. Since age is a continuous variable, this analysis shows more precisely how age impacts accident severity and identifies when age has little effect. According to the results, the type of vehicle, timing of the crash, type of road and intersection, road condition, regional and locational factors, and socio-economic characteristic have a significant impact on crashes. Regarding the effect of age, when an accident occurs the probability of bodily injury or fatality is 0.703 for female drivers, and 0.718 for male drivers at 15 years of age. These probabilities decline very slightly to 0.696 and 0.711, respectively, around 33 years of age, then very slightly increase to 0.697 and 0.712, respectively, around 47.5 years of age. The results show that age affects crash severity following a polynomial curve. While the overall pattern is one of a downward trend with age, this trend is weak until the senior years. The policy implications of the results are discussed.
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spelling pubmed-99150142023-02-11 Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach Lee, Dongkwan Guldmann, Jean-Michel von Rabenau, Burkhard Int J Environ Res Public Health Article The purpose of this research is (1) to investigate the relationship between crash severity and the age and gender of the at-fault driver, the socio-economic characteristics of the surrounding environment, and road conditions, and (2) to explain the probability of a bodily injury crash, including fatality, with the alternative being a property damage only crash. In contrast to earlier research that has focused on young and old drivers, age is considered here on its lifetime continuum. A logit model is adopted and the gender and age of the at-fault drivers are part of the independent explanatory variables. The unit of analysis is the individual crash. Since age is a continuous variable, this analysis shows more precisely how age impacts accident severity and identifies when age has little effect. According to the results, the type of vehicle, timing of the crash, type of road and intersection, road condition, regional and locational factors, and socio-economic characteristic have a significant impact on crashes. Regarding the effect of age, when an accident occurs the probability of bodily injury or fatality is 0.703 for female drivers, and 0.718 for male drivers at 15 years of age. These probabilities decline very slightly to 0.696 and 0.711, respectively, around 33 years of age, then very slightly increase to 0.697 and 0.712, respectively, around 47.5 years of age. The results show that age affects crash severity following a polynomial curve. While the overall pattern is one of a downward trend with age, this trend is weak until the senior years. The policy implications of the results are discussed. MDPI 2023-01-28 /pmc/articles/PMC9915014/ /pubmed/36767700 http://dx.doi.org/10.3390/ijerph20032338 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lee, Dongkwan
Guldmann, Jean-Michel
von Rabenau, Burkhard
Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach
title Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach
title_full Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach
title_fullStr Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach
title_full_unstemmed Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach
title_short Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach
title_sort impact of driver’s age and gender, built environment, and road conditions on crash severity: a logit modeling approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9915014/
https://www.ncbi.nlm.nih.gov/pubmed/36767700
http://dx.doi.org/10.3390/ijerph20032338
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