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...

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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/1/8124
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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, alternatives to current traffic signal plans, might be of great assistance to the control center operators. With this in view, an optimization proposal of traffic signal plans was studied and analyzed for a specific region of Curitiba (in Rebou¸cas neighborhood). This project aims 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 traffic situations, in terms of the average delay, travel time and throughput metrics.