Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes

Detalhes bibliográficos
Autor(a) principal: Santos, Bertha
Data de Publicação: 2017
Outros Autores: Picado Santos, Luis, Trindade, Valdemiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.6/8243
Resumo: For consolidated road networks, the identification, programming, and implementation of maintenance actions enables addressing the deficiencies identified in the infrastructure, ensuring the provision of an adequate service to users. The performance of such actions along the infrastructure lifetime makes it necessary to study the impact that road work zones may have on road crashes since these areas change locally and temporarily the traffic conditions offered to users (lower speeds, the presence of work equipment and workers, narrow lanes, changes in vertical and horizontal signs, etc.). This study aims to analyze the Portuguese official road work zones crash data from 2013-2015 period by using binary logistic regression models to identify the most significant factors influencing work zone crashes. Official data was processed in order to be used in a statistical analysis software and the binary logistic regressions were performed for the analysis of Portuguese work zone crashes by the type of crash (pedestrian, angle, rear-end and run-off-road), driver age groups (under 25 years, 25 to 64 and over 65 years) and a predominant contributing factor as speeding, unexpected obstacle on the road and the disregard for vertical road signs and safety distance (main contributing factors identified in this study). Results obtained shows that factors as “urban environment”, “one driver involved is running straightly”, “clean and dry pavement” and “daylight” have positive impact in a large number of models. The identification of these factors allows supporting the definition of strategies aimed at the reduction of the number and severity of crashes in road work areas.
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spelling Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone CrashesRoad SafetyWork Zone SafetyWork Zone CrashesBinary Logistic RegressionFor consolidated road networks, the identification, programming, and implementation of maintenance actions enables addressing the deficiencies identified in the infrastructure, ensuring the provision of an adequate service to users. The performance of such actions along the infrastructure lifetime makes it necessary to study the impact that road work zones may have on road crashes since these areas change locally and temporarily the traffic conditions offered to users (lower speeds, the presence of work equipment and workers, narrow lanes, changes in vertical and horizontal signs, etc.). This study aims to analyze the Portuguese official road work zones crash data from 2013-2015 period by using binary logistic regression models to identify the most significant factors influencing work zone crashes. Official data was processed in order to be used in a statistical analysis software and the binary logistic regressions were performed for the analysis of Portuguese work zone crashes by the type of crash (pedestrian, angle, rear-end and run-off-road), driver age groups (under 25 years, 25 to 64 and over 65 years) and a predominant contributing factor as speeding, unexpected obstacle on the road and the disregard for vertical road signs and safety distance (main contributing factors identified in this study). Results obtained shows that factors as “urban environment”, “one driver involved is running straightly”, “clean and dry pavement” and “daylight” have positive impact in a large number of models. The identification of these factors allows supporting the definition of strategies aimed at the reduction of the number and severity of crashes in road work areas.uBibliorumSantos, BerthaPicado Santos, LuisTrindade, Valdemiro2020-01-13T11:05:00Z2017-102017-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.6/8243engSantos B, Picado-Santos L, Trindade V RSS 2017 - Road Safety & Simulation (2017)info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-15T09:48:06Zoai:ubibliorum.ubi.pt:10400.6/8243Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:48:37.225181Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
title Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
spellingShingle Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
Santos, Bertha
Road Safety
Work Zone Safety
Work Zone Crashes
Binary Logistic Regression
title_short Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
title_full Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
title_fullStr Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
title_full_unstemmed Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
title_sort Using Binary Logistic Regression to Explain the Impact of Accident Factors on Work Zone Crashes
author Santos, Bertha
author_facet Santos, Bertha
Picado Santos, Luis
Trindade, Valdemiro
author_role author
author2 Picado Santos, Luis
Trindade, Valdemiro
author2_role author
author
dc.contributor.none.fl_str_mv uBibliorum
dc.contributor.author.fl_str_mv Santos, Bertha
Picado Santos, Luis
Trindade, Valdemiro
dc.subject.por.fl_str_mv Road Safety
Work Zone Safety
Work Zone Crashes
Binary Logistic Regression
topic Road Safety
Work Zone Safety
Work Zone Crashes
Binary Logistic Regression
description For consolidated road networks, the identification, programming, and implementation of maintenance actions enables addressing the deficiencies identified in the infrastructure, ensuring the provision of an adequate service to users. The performance of such actions along the infrastructure lifetime makes it necessary to study the impact that road work zones may have on road crashes since these areas change locally and temporarily the traffic conditions offered to users (lower speeds, the presence of work equipment and workers, narrow lanes, changes in vertical and horizontal signs, etc.). This study aims to analyze the Portuguese official road work zones crash data from 2013-2015 period by using binary logistic regression models to identify the most significant factors influencing work zone crashes. Official data was processed in order to be used in a statistical analysis software and the binary logistic regressions were performed for the analysis of Portuguese work zone crashes by the type of crash (pedestrian, angle, rear-end and run-off-road), driver age groups (under 25 years, 25 to 64 and over 65 years) and a predominant contributing factor as speeding, unexpected obstacle on the road and the disregard for vertical road signs and safety distance (main contributing factors identified in this study). Results obtained shows that factors as “urban environment”, “one driver involved is running straightly”, “clean and dry pavement” and “daylight” have positive impact in a large number of models. The identification of these factors allows supporting the definition of strategies aimed at the reduction of the number and severity of crashes in road work areas.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
2017-10-01T00:00:00Z
2020-01-13T11:05:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.6/8243
url http://hdl.handle.net/10400.6/8243
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Santos B, Picado-Santos L, Trindade V RSS 2017 - Road Safety & Simulation (2017)
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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