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
| Summary: | 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. |
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