Machine vision algorithms applied to dynamic traffic light control
This paper presents a fuzzy traffic controller that in an autonomous, centralized and efficient way, manages vehicular traffic flow in a group of intersections. The system uses a computer vision algorithm to detect the number of cars in images captured by a set of strategically placed cameras at eve...
- Autores:
-
Espinosa Valcárcel, Fabio Andrés
Gordillo Chaves, Camilo Andrés
Jimenez Moreno, Robinson
Avilés Sánchez, Oscar Fernando
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/39608
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/39608
http://bdigital.unal.edu.co/29705/
- Palabra clave:
- Traffic control
computer vision
optimization
fuzzy control
object detection
- 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_abf2Espinosa Valcárcel, Fabio Andrés889d3859-169a-42a6-8e93-f5c0d42f18fa300Gordillo Chaves, Camilo Andrésf6eeef3c-b6e3-49b6-9aaf-57bc4f07f4b0300Jimenez Moreno, Robinson2c23dbe9-4bec-4080-bbd7-b7593f8a3eb1300Avilés Sánchez, Oscar Fernandoae65a784-0537-4c6a-958b-757fbc2ea6d53002019-06-28T04:08:57Z2019-06-28T04:08:57Z2013https://repositorio.unal.edu.co/handle/unal/39608http://bdigital.unal.edu.co/29705/This paper presents a fuzzy traffic controller that in an autonomous, centralized and efficient way, manages vehicular traffic flow in a group of intersections. The system uses a computer vision algorithm to detect the number of cars in images captured by a set of strategically placed cameras at every intersection. Using this information, the system selects the sequence of actions that optimize traffic flow within the control area, in a simulated scenario. The results obtained show that the system reduces the delay times for each vehicle by 20% and that the controller is able to adapt smoothly to different flow changes.application/pdfspaUniversidad Nacional de Colombia Sede Medellínhttp://revistas.unal.edu.co/index.php/dyna/article/view/28332Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaDyna; Vol. 80, núm. 178 (2013); 132-140 DYNA; Vol. 80, núm. 178 (2013); 132-140 2346-2183 0012-7353Espinosa Valcárcel, Fabio Andrés and Gordillo Chaves, Camilo Andrés and Jimenez Moreno, Robinson and Avilés Sánchez, Oscar Fernando (2013) Machine vision algorithms applied to dynamic traffic light control. Dyna; Vol. 80, núm. 178 (2013); 132-140 DYNA; Vol. 80, núm. 178 (2013); 132-140 2346-2183 0012-7353 .Machine vision algorithms applied to dynamic traffic light controlArtículo 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/ARTTraffic controlcomputer visionoptimizationfuzzy controlobject detectionORIGINAL28332-167442-1-PB.pdfapplication/pdf1855819https://repositorio.unal.edu.co/bitstream/unal/39608/1/28332-167442-1-PB.pdfe5c2e6aebbf84567c030c057e2faa231MD5128332-197936-1-PB.htmltext/html38444https://repositorio.unal.edu.co/bitstream/unal/39608/2/28332-197936-1-PB.html146de097a9ec88dca8124e50056fe94dMD52THUMBNAIL28332-167442-1-PB.pdf.jpg28332-167442-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg9031https://repositorio.unal.edu.co/bitstream/unal/39608/3/28332-167442-1-PB.pdf.jpg2781012e2a5667c487db791c0db7af6dMD53unal/39608oai:repositorio.unal.edu.co:unal/396082023-01-24 23:04:40.229Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |
| dc.title.spa.fl_str_mv |
Machine vision algorithms applied to dynamic traffic light control |
| title |
Machine vision algorithms applied to dynamic traffic light control |
| spellingShingle |
Machine vision algorithms applied to dynamic traffic light control Traffic control computer vision optimization fuzzy control object detection |
| title_short |
Machine vision algorithms applied to dynamic traffic light control |
| title_full |
Machine vision algorithms applied to dynamic traffic light control |
| title_fullStr |
Machine vision algorithms applied to dynamic traffic light control |
| title_full_unstemmed |
Machine vision algorithms applied to dynamic traffic light control |
| title_sort |
Machine vision algorithms applied to dynamic traffic light control |
| dc.creator.fl_str_mv |
Espinosa Valcárcel, Fabio Andrés Gordillo Chaves, Camilo Andrés Jimenez Moreno, Robinson Avilés Sánchez, Oscar Fernando |
| dc.contributor.author.spa.fl_str_mv |
Espinosa Valcárcel, Fabio Andrés Gordillo Chaves, Camilo Andrés Jimenez Moreno, Robinson Avilés Sánchez, Oscar Fernando |
| dc.subject.proposal.spa.fl_str_mv |
Traffic control computer vision optimization fuzzy control object detection |
| topic |
Traffic control computer vision optimization fuzzy control object detection |
| description |
This paper presents a fuzzy traffic controller that in an autonomous, centralized and efficient way, manages vehicular traffic flow in a group of intersections. The system uses a computer vision algorithm to detect the number of cars in images captured by a set of strategically placed cameras at every intersection. Using this information, the system selects the sequence of actions that optimize traffic flow within the control area, in a simulated scenario. The results obtained show that the system reduces the delay times for each vehicle by 20% and that the controller is able to adapt smoothly to different flow changes. |
| publishDate |
2013 |
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2013 |
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2019-06-28T04:08:57Z |
| dc.date.available.spa.fl_str_mv |
2019-06-28T04:08:57Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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Text |
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publishedVersion |
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https://repositorio.unal.edu.co/handle/unal/39608 |
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http://bdigital.unal.edu.co/29705/ |
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https://repositorio.unal.edu.co/handle/unal/39608 http://bdigital.unal.edu.co/29705/ |
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spa |
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spa |
| dc.relation.spa.fl_str_mv |
http://revistas.unal.edu.co/index.php/dyna/article/view/28332 |
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Universidad Nacional de Colombia Revistas electrónicas UN Dyna Dyna |
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Dyna; Vol. 80, núm. 178 (2013); 132-140 DYNA; Vol. 80, núm. 178 (2013); 132-140 2346-2183 0012-7353 |
| dc.relation.references.spa.fl_str_mv |
Espinosa Valcárcel, Fabio Andrés and Gordillo Chaves, Camilo Andrés and Jimenez Moreno, Robinson and Avilés Sánchez, Oscar Fernando (2013) Machine vision algorithms applied to dynamic traffic light control. Dyna; Vol. 80, núm. 178 (2013); 132-140 DYNA; Vol. 80, núm. 178 (2013); 132-140 2346-2183 0012-7353 . |
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Derechos reservados - Universidad Nacional de Colombia |
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http://purl.org/coar/access_right/c_abf2 |
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Atribución-NoComercial 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc/4.0/ |
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info:eu-repo/semantics/openAccess |
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Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
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Universidad Nacional de Colombia Sede Medellín |
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