Simulação e otimização da programação semafórica de uma região de Curitiba
The traffic light control in Curitiba is currently held by the Municipal Operational Control Center. The city is divided into 33 different semaphoric regions, each with one specific timing table. In the Control Center, many aspects of traffic signal plans are determined manually, with a heavy load o...
| Principais autores: | Pando, Luciano Urgal, Fuchs, Stefan Campana |
|---|---|
| Formato: | Trabalho de Conclusão de Curso (Graduação) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2020
|
| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/9298 |
| Tags: |
Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
|
| Resumo: |
The traffic light control in Curitiba is currently held by the Municipal Operational Control Center. The city is divided into 33 different semaphoric regions, each with one specific timing table. In the Control Center, many aspects of traffic signal plans are determined manually, with a heavy load of engineers’ and technicians’ experience. A computer system capable of processing the traffic sensors data available and to propose, for example, alter- natives to current traffic signal plans, might be of great assistance to the control center perators. With this in view, an optimization proposal of traffic signal plans was studied and analyzed for a specific region of Curitiba (in Rebou ̧as neighborhood). This project caims to develop a strategy of optimization with simulation for adjustment of traffic signal plans, from real data collected from the roads of that city region. For this, existing technological tools are used (simulators, optimization libraries, among others), as well as algorithms from the literature, adapting them to real needs and situations of the traffic. A realistic simulation model using the SUMO software was created from the data yielded by SETRAN. The traffic signal plan optimization was developed from the Particle Swarm Optimization algorithm. In various tests, improvements were observed over the current timing plan for specific tr ffic situations, in terms of the average delay, travel time and throughput metrics. |
|---|