Application of bayesian techniques for the identification of accident-prone road sections
The use of Bayesian techniques for the identification of accident-prone road sections has become very important in recent years. The objective of this investigation consisted of identifying accident-prone road sections in the Municipality of Ocaña (Colombia) using the Bayesian Method (BM); the model...
- Autores:
-
Guerrero-Barbosa, Thomas Edison
Amarís-Castro, Gloria Estefany
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2014
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/50496
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/50496
http://bdigital.unal.edu.co/44493/
- Palabra clave:
- Bayesian Method
accident-prone sections
hazard ranking
road safety
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Guerrero-Barbosa, Thomas Edison3e2ae7e4-2469-49b6-8de7-2b2e4b5e08e5300Amarís-Castro, Gloria Estefanyd81b8c4c-8049-43f1-9570-5ca6e2cc89d53002019-06-29T10:21:43Z2019-06-29T10:21:43Z2014-10-24https://repositorio.unal.edu.co/handle/unal/50496http://bdigital.unal.edu.co/44493/The use of Bayesian techniques for the identification of accident-prone road sections has become very important in recent years. The objective of this investigation consisted of identifying accident-prone road sections in the Municipality of Ocaña (Colombia) using the Bayesian Method (BM); the modeling approach developed involved the creation of a database of accidents that occurred between the years 2007 (January) and 2013 (August) and the application of the methodology on 15 sections of urban road. The final analyses show that the BM is an original and fast tool that is easily implemented, it provides results in which 4 accident-prone or dangerous road sections were identified and ranked them in order of danger, establishing a danger ranking that provides a prioritization for investments and the implementation of preventive and/or corrective policies that will maximize benefits associated with road safety.application/pdfspaUniversidad Nacional de Colombia Sede Medellínhttp://revistas.unal.edu.co/index.php/dyna/article/view/41333Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaDyna; Vol. 81, núm. 187 (2014); 209-214 DYNA; Vol. 81, núm. 187 (2014); 209-214 2346-2183 0012-7353Guerrero-Barbosa, Thomas Edison and Amarís-Castro, Gloria Estefany (2014) Application of bayesian techniques for the identification of accident-prone road sections. Dyna; Vol. 81, núm. 187 (2014); 209-214 DYNA; Vol. 81, núm. 187 (2014); 209-214 2346-2183 0012-7353 .Application of bayesian techniques for the identification of accident-prone road sectionsArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTBayesian Methodaccident-prone sectionshazard rankingroad safetyORIGINAL41333-227065-1-PB.pdfapplication/pdf607729https://repositorio.unal.edu.co/bitstream/unal/50496/1/41333-227065-1-PB.pdf11590817bfe290c598b82e09d62d0e4fMD5141333-186545-1-SP.pdfapplication/pdf221018https://repositorio.unal.edu.co/bitstream/unal/50496/2/41333-186545-1-SP.pdfa509bb6172d2c410684e0dc0816d0e98MD52THUMBNAIL41333-227065-1-PB.pdf.jpg41333-227065-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg9380https://repositorio.unal.edu.co/bitstream/unal/50496/3/41333-227065-1-PB.pdf.jpg5f9ee15012d54b9bb159e8d79a56b6a7MD5341333-186545-1-SP.pdf.jpg41333-186545-1-SP.pdf.jpgGenerated Thumbnailimage/jpeg6710https://repositorio.unal.edu.co/bitstream/unal/50496/4/41333-186545-1-SP.pdf.jpgca1d981b4c8d10d799ea3c7628cd1e8fMD54unal/50496oai:repositorio.unal.edu.co:unal/504962023-12-15 23:06:18.029Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |
| dc.title.spa.fl_str_mv |
Application of bayesian techniques for the identification of accident-prone road sections |
| title |
Application of bayesian techniques for the identification of accident-prone road sections |
| spellingShingle |
Application of bayesian techniques for the identification of accident-prone road sections Bayesian Method accident-prone sections hazard ranking road safety |
| title_short |
Application of bayesian techniques for the identification of accident-prone road sections |
| title_full |
Application of bayesian techniques for the identification of accident-prone road sections |
| title_fullStr |
Application of bayesian techniques for the identification of accident-prone road sections |
| title_full_unstemmed |
Application of bayesian techniques for the identification of accident-prone road sections |
| title_sort |
Application of bayesian techniques for the identification of accident-prone road sections |
| dc.creator.fl_str_mv |
Guerrero-Barbosa, Thomas Edison Amarís-Castro, Gloria Estefany |
| dc.contributor.author.spa.fl_str_mv |
Guerrero-Barbosa, Thomas Edison Amarís-Castro, Gloria Estefany |
| dc.subject.proposal.spa.fl_str_mv |
Bayesian Method accident-prone sections hazard ranking road safety |
| topic |
Bayesian Method accident-prone sections hazard ranking road safety |
| description |
The use of Bayesian techniques for the identification of accident-prone road sections has become very important in recent years. The objective of this investigation consisted of identifying accident-prone road sections in the Municipality of Ocaña (Colombia) using the Bayesian Method (BM); the modeling approach developed involved the creation of a database of accidents that occurred between the years 2007 (January) and 2013 (August) and the application of the methodology on 15 sections of urban road. The final analyses show that the BM is an original and fast tool that is easily implemented, it provides results in which 4 accident-prone or dangerous road sections were identified and ranked them in order of danger, establishing a danger ranking that provides a prioritization for investments and the implementation of preventive and/or corrective policies that will maximize benefits associated with road safety. |
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2014 |
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2014-10-24 |
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2019-06-29T10:21:43Z |
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2019-06-29T10:21:43Z |
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http://bdigital.unal.edu.co/44493/ |
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spa |
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http://revistas.unal.edu.co/index.php/dyna/article/view/41333 |
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Universidad Nacional de Colombia Revistas electrónicas UN Dyna Dyna |
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Dyna; Vol. 81, núm. 187 (2014); 209-214 DYNA; Vol. 81, núm. 187 (2014); 209-214 2346-2183 0012-7353 |
| dc.relation.references.spa.fl_str_mv |
Guerrero-Barbosa, Thomas Edison and Amarís-Castro, Gloria Estefany (2014) Application of bayesian techniques for the identification of accident-prone road sections. Dyna; Vol. 81, núm. 187 (2014); 209-214 DYNA; Vol. 81, núm. 187 (2014); 209-214 2346-2183 0012-7353 . |
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