What factors results in having a severe crash? a closer look on distraction-related factors

This study provides a comprehensive literature review to summarize all contributing factors and the logit-based models that were used to predict the severity of crashes. Using the General Estimates Systems (GES) dataset, as a subset and a branch of the National Automotive Sampling System in the US,...

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Autores principales:	Hesamoddin Razi-Ardakani, Ahmadreza Mahmoudzadeh, Mohammad Kermanshah
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2019
Materias:	distracted driving crash injury severity distraction-related factors national automotive sampling system (nass) generalized ordered logit Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/6e8684c4ee12404b82b015900e7fef95
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spelling	oai:doaj.org-article:6e8684c4ee12404b82b015900e7fef952021-11-04T15:51:57ZWhat factors results in having a severe crash? a closer look on distraction-related factors2331-191610.1080/23311916.2019.1708652https://doaj.org/article/6e8684c4ee12404b82b015900e7fef952019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311916.2019.1708652https://doaj.org/toc/2331-1916This study provides a comprehensive literature review to summarize all contributing factors and the logit-based models that were used to predict the severity of crashes. Using the General Estimates Systems (GES) dataset, as a subset and a branch of the National Automotive Sampling System in the US, a Generalized Ordered Logit (GLM) model is developed to predict the crash severity. The developed severity model detects the most important parameters based on characteristics of the driver, the environment, the vehicle, the road, and the type of crash. This study aims to take a more in-depth look into the distraction-related factors as one of the most important groups of contributing factors to traffic crashes. Distraction-related factors are categorized into five groups based on the generating source, including cellular phone, cognitive, passenger, outside events, and in-vehicle activities. Moreover, the effect of distraction on crashes in the presence of other factors is studied. Analyzing the severity of crashes revealed that cell phone usage and distraction caused by in-vehicle activities increase the severity of crashes, whereas other factors of distraction decrease the severity.Hesamoddin Razi-ArdakaniAhmadreza MahmoudzadehMohammad KermanshahTaylor & Francis Grouparticledistracted drivingcrash injuryseveritydistraction-related factorsnational automotive sampling system (nass)generalized ordered logitEngineering (General). Civil engineering (General)TA1-2040ENCogent Engineering, Vol 6, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	distracted driving crash injury severity distraction-related factors national automotive sampling system (nass) generalized ordered logit Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	distracted driving crash injury severity distraction-related factors national automotive sampling system (nass) generalized ordered logit Engineering (General). Civil engineering (General) TA1-2040 Hesamoddin Razi-Ardakani Ahmadreza Mahmoudzadeh Mohammad Kermanshah What factors results in having a severe crash? a closer look on distraction-related factors
description	This study provides a comprehensive literature review to summarize all contributing factors and the logit-based models that were used to predict the severity of crashes. Using the General Estimates Systems (GES) dataset, as a subset and a branch of the National Automotive Sampling System in the US, a Generalized Ordered Logit (GLM) model is developed to predict the crash severity. The developed severity model detects the most important parameters based on characteristics of the driver, the environment, the vehicle, the road, and the type of crash. This study aims to take a more in-depth look into the distraction-related factors as one of the most important groups of contributing factors to traffic crashes. Distraction-related factors are categorized into five groups based on the generating source, including cellular phone, cognitive, passenger, outside events, and in-vehicle activities. Moreover, the effect of distraction on crashes in the presence of other factors is studied. Analyzing the severity of crashes revealed that cell phone usage and distraction caused by in-vehicle activities increase the severity of crashes, whereas other factors of distraction decrease the severity.
format	article
author	Hesamoddin Razi-Ardakani Ahmadreza Mahmoudzadeh Mohammad Kermanshah
author_facet	Hesamoddin Razi-Ardakani Ahmadreza Mahmoudzadeh Mohammad Kermanshah
author_sort	Hesamoddin Razi-Ardakani
title	What factors results in having a severe crash? a closer look on distraction-related factors
title_short	What factors results in having a severe crash? a closer look on distraction-related factors
title_full	What factors results in having a severe crash? a closer look on distraction-related factors
title_fullStr	What factors results in having a severe crash? a closer look on distraction-related factors
title_full_unstemmed	What factors results in having a severe crash? a closer look on distraction-related factors
title_sort	what factors results in having a severe crash? a closer look on distraction-related factors
publisher	Taylor & Francis Group
publishDate	2019
url	https://doaj.org/article/6e8684c4ee12404b82b015900e7fef95
work_keys_str_mv	AT hesamoddinraziardakani whatfactorsresultsinhavingaseverecrashacloserlookondistractionrelatedfactors AT ahmadrezamahmoudzadeh whatfactorsresultsinhavingaseverecrashacloserlookondistractionrelatedfactors AT mohammadkermanshah whatfactorsresultsinhavingaseverecrashacloserlookondistractionrelatedfactors
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What factors results in having a severe crash? a closer look on distraction-related factors

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