Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function

Motorcyclists account for more than 380 000 deaths annually worldwide from road traffic accidents. Motorcyclists are the most vulnerable road users worldwide to road safety (28% of global fatalities), together with cyclists and pedestrians. Approximately 80% of deaths are from low- or middle-income...

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Autores:
Ospina-Mateus, Holman
Quintana Jiménez, Leonardo Augusto
Lopez-Valdes, Francisco J.
Sana, Shib Sankar
Tipo de recurso:
Fecha de publicación:
2021
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12302
Acceso en línea:
https://hdl.handle.net/20.500.12585/12302
Palabra clave:
Crashes
Empirical Bayesian approach
Motorcycle
Negative binomial regression
Prone-section
Safety performance function
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openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
title Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
spellingShingle Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
Crashes
Empirical Bayesian approach
Motorcycle
Negative binomial regression
Prone-section
Safety performance function
title_short Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
title_full Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
title_fullStr Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
title_full_unstemmed Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
title_sort Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function
dc.creator.fl_str_mv Ospina-Mateus, Holman
Quintana Jiménez, Leonardo Augusto
Lopez-Valdes, Francisco J.
Sana, Shib Sankar
dc.contributor.author.none.fl_str_mv Ospina-Mateus, Holman
Quintana Jiménez, Leonardo Augusto
Lopez-Valdes, Francisco J.
Sana, Shib Sankar
dc.subject.keywords.spa.fl_str_mv Crashes
Empirical Bayesian approach
Motorcycle
Negative binomial regression
Prone-section
Safety performance function
topic Crashes
Empirical Bayesian approach
Motorcycle
Negative binomial regression
Prone-section
Safety performance function
description Motorcyclists account for more than 380 000 deaths annually worldwide from road traffic accidents. Motorcyclists are the most vulnerable road users worldwide to road safety (28% of global fatalities), together with cyclists and pedestrians. Approximately 80% of deaths are from low- or middle-income countries. Colombia has a rate of 9.7 deaths per 100 000 inhabitants, which places it 10th in the world. Motorcycles in Colombia correspond to 57% of the fleet and generate an average of 51% of fatalities per year. This study aims to identify significant factors of the environment, traffic volume, and infrastructure to predict the number of accidents per year focused only on motorcyclists. The prediction model used a negative binomial regression for the definition of a Safety Performance Function (SPF) for motorcyclists. In the second stage, Bayes' empirical approach is implemented to identify motorcycle crash-prone road sections. The study is applied in Cartagena, one of the capital cities with more traffic crashes and motorcyclists dedicated to informal transportation (motorcycle taxi riders) in Colombia. The data of 2884 motorcycle crashes between 2016 and 2017 are analyzed. The proposed model identifies that crashes of motorcyclists per kilometer have significant factors such as the average volume of daily motorcyclist traffic, the number of accesses (intersections) per kilometer, commercial areas, and the type of road and it identifies 55 critical accident-prone sections. The research evidences coherent and consistent results with previous studies and requires effective countermeasures for the benefit of road safety for motorcyclists.
publishDate 2021
dc.date.issued.none.fl_str_mv 2021-05-11
dc.date.accessioned.none.fl_str_mv 2023-07-21T15:55:24Z
dc.date.available.none.fl_str_mv 2023-07-21T15:55:24Z
dc.date.submitted.none.fl_str_mv 2023-07
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dc.identifier.citation.spa.fl_str_mv Ospina-Mateus, H., Quintana Jiménez, L.A., Lopez-Valdes, F.J., Sana, S.S. Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function (2021) RAIRO - Operations Research, 55 (3), pp. 1257-1278. DOI: 10.1051/ro/2021055
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/12302
dc.identifier.doi.none.fl_str_mv 10.1051/ro/2021055
dc.identifier.instname.spa.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv Ospina-Mateus, H., Quintana Jiménez, L.A., Lopez-Valdes, F.J., Sana, S.S. Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function (2021) RAIRO - Operations Research, 55 (3), pp. 1257-1278. DOI: 10.1051/ro/2021055
10.1051/ro/2021055
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/12302
dc.language.iso.spa.fl_str_mv eng
language eng
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dc.rights.cc.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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dc.format.extent.none.fl_str_mv 22 páginas
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dc.publisher.place.spa.fl_str_mv Cartagena de Indias
dc.source.spa.fl_str_mv RAIRO - Operations Research - vol. 55 No. 3 (2021)
institution Universidad Tecnológica de Bolívar
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spelling Ospina-Mateus, Holman1b4b1bc0-3606-4c14-bb13-dbc9d4251891Quintana Jiménez, Leonardo Augustofadbc121-f32c-427a-ae59-4f4a37ed4471Lopez-Valdes, Francisco J.5a4268e2-55b2-412f-814e-1a12bd7d3511Sana, Shib Sankare81af3d1-9873-434c-8df4-41a1929550652023-07-21T15:55:24Z2023-07-21T15:55:24Z2021-05-112023-07Ospina-Mateus, H., Quintana Jiménez, L.A., Lopez-Valdes, F.J., Sana, S.S. Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance function (2021) RAIRO - Operations Research, 55 (3), pp. 1257-1278. DOI: 10.1051/ro/2021055https://hdl.handle.net/20.500.12585/1230210.1051/ro/2021055Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarMotorcyclists account for more than 380 000 deaths annually worldwide from road traffic accidents. Motorcyclists are the most vulnerable road users worldwide to road safety (28% of global fatalities), together with cyclists and pedestrians. Approximately 80% of deaths are from low- or middle-income countries. Colombia has a rate of 9.7 deaths per 100 000 inhabitants, which places it 10th in the world. Motorcycles in Colombia correspond to 57% of the fleet and generate an average of 51% of fatalities per year. This study aims to identify significant factors of the environment, traffic volume, and infrastructure to predict the number of accidents per year focused only on motorcyclists. The prediction model used a negative binomial regression for the definition of a Safety Performance Function (SPF) for motorcyclists. In the second stage, Bayes' empirical approach is implemented to identify motorcycle crash-prone road sections. The study is applied in Cartagena, one of the capital cities with more traffic crashes and motorcyclists dedicated to informal transportation (motorcycle taxi riders) in Colombia. The data of 2884 motorcycle crashes between 2016 and 2017 are analyzed. The proposed model identifies that crashes of motorcyclists per kilometer have significant factors such as the average volume of daily motorcyclist traffic, the number of accesses (intersections) per kilometer, commercial areas, and the type of road and it identifies 55 critical accident-prone sections. The research evidences coherent and consistent results with previous studies and requires effective countermeasures for the benefit of road safety for motorcyclists.22 páginasPdfapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2RAIRO - Operations Research - vol. 55 No. 3 (2021)Prediction of motorcyclist traffic crashes in Cartagena (Colombia): Development of a safety performance functioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1CrashesEmpirical Bayesian approachMotorcycleNegative binomial regressionProne-sectionSafety performance functionCartagena de IndiasAASHTO, The Highway Safety Manual. 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