Assessing the transferability of crash prediction models for two lane highways in Brazil

Detalhes bibliográficos
Autor(a) principal: Silva, Karla Cristina Rodrigues
Data de Publicação: 2017
Tipo de documento: Tese
Idioma: eng
Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
Texto Completo: http://www.teses.usp.br/teses/disponiveis/18/18144/tde-10112017-215500/
Resumo: The present study focused on evaluating some crash prediction models for two lane highways on Brazilian conditions. Also, the transferability of models was considered, specifically by means of a comparison between Brazil, HSM and Florida. The analysis of two lane highways crash prediction models was promising when the road characteristics were well known and there was not much difference from base conditions. This conclusion was attained regarding the comparison of results for all segments, non-curved segments and curved segments, confirming that a transferred model can be used with caution. In addition, two novel models for Brazilian two-lane highways segments were estimated. The model developed showed better results for non-curved segments in the calibration/validation sample. Thus, for a general analysis purpose of non-curved segments this model is recommended. Finally, there are many factors that could not be measured by these models and reflects road safety various condition. Even so, the study of crash predict models in Brazilian context could provide a better start point in safety road analysis.
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spelling Assessing the transferability of crash prediction models for two lane highways in BrazilAvaliação da transferabilidade de modelos de previsão de acidentes em rodovias de pista simples do BrasilBrasilBrazilCrash prediction modelFloridaFloridaHSMHSMMétodo de previsão de acidentesRodovia de pista simplesSafety analysisSegurança viáriaTransferabilidadeTransferabilityTwo lane highwayThe present study focused on evaluating some crash prediction models for two lane highways on Brazilian conditions. Also, the transferability of models was considered, specifically by means of a comparison between Brazil, HSM and Florida. The analysis of two lane highways crash prediction models was promising when the road characteristics were well known and there was not much difference from base conditions. This conclusion was attained regarding the comparison of results for all segments, non-curved segments and curved segments, confirming that a transferred model can be used with caution. In addition, two novel models for Brazilian two-lane highways segments were estimated. The model developed showed better results for non-curved segments in the calibration/validation sample. Thus, for a general analysis purpose of non-curved segments this model is recommended. Finally, there are many factors that could not be measured by these models and reflects road safety various condition. Even so, the study of crash predict models in Brazilian context could provide a better start point in safety road analysis.O foco desta pesquisa foi avaliar a aplicação de alguns modelos de previsão de acidentes em rodovias de pista simples de três estados brasileiros. Ainda, a transferabilidade destes modelos foi abordada, especificamente por meio de uma comparação entre características do Brasil, Florida e aquelas recomendadas pelo Highway Safety Manual. O uso dos distintos modelos se mostrou promissor para situações nas quais as características da via se mantiveram semelhantes às condições para as quais os modelos foram desenvolvidos. A avaliação foi empreendida para todos os segmentos homogêneos, separados posteriormente segundo a existência de curvas horizontais. Adicionalmente, dois novos modelos foram equacionados para a amostra brasileira. O modelo de previsão de acidentes desenvolvido apresentou melhores medidas de desempenho para segmentos sem curvas horizontais, sendo recomendável para previsão de acidentes em análises preliminares. Por fim, foi constatado que outros fatores não contemplados pelos modelos podem ter impactado as condições de segurança dos locais estudados. Ainda assim, essa pesquisa representa no contexto do Brasil um ponto de partida em análises relacionadas à segurança de rodovias de pista simples.Biblioteca Digitais de Teses e Dissertações da USPFerraz, Antonio Clóvis PintoSilva, Karla Cristina Rodrigues2017-09-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://www.teses.usp.br/teses/disponiveis/18/18144/tde-10112017-215500/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2018-07-19T17:03:58Zoai:teses.usp.br:tde-10112017-215500Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212018-07-19T17:03:58Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Assessing the transferability of crash prediction models for two lane highways in Brazil
Avaliação da transferabilidade de modelos de previsão de acidentes em rodovias de pista simples do Brasil
title Assessing the transferability of crash prediction models for two lane highways in Brazil
spellingShingle Assessing the transferability of crash prediction models for two lane highways in Brazil
Silva, Karla Cristina Rodrigues
Brasil
Brazil
Crash prediction model
Florida
Florida
HSM
HSM
Método de previsão de acidentes
Rodovia de pista simples
Safety analysis
Segurança viária
Transferabilidade
Transferability
Two lane highway
title_short Assessing the transferability of crash prediction models for two lane highways in Brazil
title_full Assessing the transferability of crash prediction models for two lane highways in Brazil
title_fullStr Assessing the transferability of crash prediction models for two lane highways in Brazil
title_full_unstemmed Assessing the transferability of crash prediction models for two lane highways in Brazil
title_sort Assessing the transferability of crash prediction models for two lane highways in Brazil
author Silva, Karla Cristina Rodrigues
author_facet Silva, Karla Cristina Rodrigues
author_role author
dc.contributor.none.fl_str_mv Ferraz, Antonio Clóvis Pinto
dc.contributor.author.fl_str_mv Silva, Karla Cristina Rodrigues
dc.subject.por.fl_str_mv Brasil
Brazil
Crash prediction model
Florida
Florida
HSM
HSM
Método de previsão de acidentes
Rodovia de pista simples
Safety analysis
Segurança viária
Transferabilidade
Transferability
Two lane highway
topic Brasil
Brazil
Crash prediction model
Florida
Florida
HSM
HSM
Método de previsão de acidentes
Rodovia de pista simples
Safety analysis
Segurança viária
Transferabilidade
Transferability
Two lane highway
description The present study focused on evaluating some crash prediction models for two lane highways on Brazilian conditions. Also, the transferability of models was considered, specifically by means of a comparison between Brazil, HSM and Florida. The analysis of two lane highways crash prediction models was promising when the road characteristics were well known and there was not much difference from base conditions. This conclusion was attained regarding the comparison of results for all segments, non-curved segments and curved segments, confirming that a transferred model can be used with caution. In addition, two novel models for Brazilian two-lane highways segments were estimated. The model developed showed better results for non-curved segments in the calibration/validation sample. Thus, for a general analysis purpose of non-curved segments this model is recommended. Finally, there are many factors that could not be measured by these models and reflects road safety various condition. Even so, the study of crash predict models in Brazilian context could provide a better start point in safety road analysis.
publishDate 2017
dc.date.none.fl_str_mv 2017-09-04
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.teses.usp.br/teses/disponiveis/18/18144/tde-10112017-215500/
url http://www.teses.usp.br/teses/disponiveis/18/18144/tde-10112017-215500/
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv
dc.rights.driver.fl_str_mv Liberar o conteúdo para acesso público.
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Liberar o conteúdo para acesso público.
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv
dc.publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
dc.source.none.fl_str_mv
reponame:Biblioteca Digital de Teses e Dissertações da USP
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Biblioteca Digital de Teses e Dissertações da USP
collection Biblioteca Digital de Teses e Dissertações da USP
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)
repository.mail.fl_str_mv virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br
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