Prediction of road accident severity using the ordered probit model

Detalhes bibliográficos
Autor(a) principal: Garrido, Rui
Data de Publicação: 2014
Outros Autores: Bastos Silva, Ana, Almeida, Ana Maria de, Almeida, J-P Duarte de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/45691
https://doi.org/10.1016/j.trpro.2014.10.107
Resumo: The ordered probit model is used to examine the contribution of several factors to the injury severity faced by motor-vehicle occupants involved in road accidents. The estimated results suggest that motor-vehicle occupants travelling in light-vehicles, at two-way roads, and on dry road surfaces tend to suffer more severe injuries than those who travel in heavy-vehicles, at one-way roads, and on wet road surfaces. Additionally, the driver's seat is clearly the safest seating position, urban areas seem to originate less serious accidents than rural areas, and women tend to be more likely to suffer serious or fatal injuries than men.
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spelling Prediction of road accident severity using the ordered probit modelRoad safetyroad accident modellinginjury severitymotor-vehicle occupantsordered probit modelThe ordered probit model is used to examine the contribution of several factors to the injury severity faced by motor-vehicle occupants involved in road accidents. The estimated results suggest that motor-vehicle occupants travelling in light-vehicles, at two-way roads, and on dry road surfaces tend to suffer more severe injuries than those who travel in heavy-vehicles, at one-way roads, and on wet road surfaces. Additionally, the driver's seat is clearly the safest seating position, urban areas seem to originate less serious accidents than rural areas, and women tend to be more likely to suffer serious or fatal injuries than men.Elsevier2014-11-08info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/45691http://hdl.handle.net/10316/45691https://doi.org/10.1016/j.trpro.2014.10.107eng2352-1465http://www.sciencedirect.com/science/article/pii/S2352146514002701?via%3DihubGarrido, RuiBastos Silva, AnaAlmeida, Ana Maria deAlmeida, J-P Duarte deinfo: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:RCAAP2021-08-25T08:25:06Zoai:estudogeral.uc.pt:10316/45691Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:53:44.750647Repositório 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 Prediction of road accident severity using the ordered probit model
title Prediction of road accident severity using the ordered probit model
spellingShingle Prediction of road accident severity using the ordered probit model
Garrido, Rui
Road safety
road accident modelling
injury severity
motor-vehicle occupants
ordered probit model
title_short Prediction of road accident severity using the ordered probit model
title_full Prediction of road accident severity using the ordered probit model
title_fullStr Prediction of road accident severity using the ordered probit model
title_full_unstemmed Prediction of road accident severity using the ordered probit model
title_sort Prediction of road accident severity using the ordered probit model
author Garrido, Rui
author_facet Garrido, Rui
Bastos Silva, Ana
Almeida, Ana Maria de
Almeida, J-P Duarte de
author_role author
author2 Bastos Silva, Ana
Almeida, Ana Maria de
Almeida, J-P Duarte de
author2_role author
author
author
dc.contributor.author.fl_str_mv Garrido, Rui
Bastos Silva, Ana
Almeida, Ana Maria de
Almeida, J-P Duarte de
dc.subject.por.fl_str_mv Road safety
road accident modelling
injury severity
motor-vehicle occupants
ordered probit model
topic Road safety
road accident modelling
injury severity
motor-vehicle occupants
ordered probit model
description The ordered probit model is used to examine the contribution of several factors to the injury severity faced by motor-vehicle occupants involved in road accidents. The estimated results suggest that motor-vehicle occupants travelling in light-vehicles, at two-way roads, and on dry road surfaces tend to suffer more severe injuries than those who travel in heavy-vehicles, at one-way roads, and on wet road surfaces. Additionally, the driver's seat is clearly the safest seating position, urban areas seem to originate less serious accidents than rural areas, and women tend to be more likely to suffer serious or fatal injuries than men.
publishDate 2014
dc.date.none.fl_str_mv 2014-11-08
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/45691
http://hdl.handle.net/10316/45691
https://doi.org/10.1016/j.trpro.2014.10.107
url http://hdl.handle.net/10316/45691
https://doi.org/10.1016/j.trpro.2014.10.107
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2352-1465
http://www.sciencedirect.com/science/article/pii/S2352146514002701?via%3Dihub
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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