Modelos de controle semafórico Fuzzy adaptativo para cruzamentos isolados

Detalhes bibliográficos
Ano de defesa: 2018
Autor(a) principal: SOARES, Ana Caroline Meireles lattes
Orientador(a): FONSECA NETO, João Viana da lattes
Banca de defesa: SERRA, Ginalber Luiz de Oliveira lattes, FREIRE, Raimundo Carlos Silvério lattes
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal do Maranhão
Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
Departamento: DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://tedebc.ufma.br/jspui/handle/tede/2132
Resumo: The traffic of people and goods has direct influence and vital importance in the social and economic development of modern society, and so, its negative consequences originated from the out of order growth deserve attention in the planning of cities. Such mobility demand generates an increase in the flow of vehicles in circulation and consequently, the occurrence of frequent traffic jams, accidents, delays, pollution increase, among others. Several improvements in the traffic control systems have been proposed, and many methodologies have been presented aiming at reducing the effects triggered by those problems. In this work, models are proposed for urban traffic control in isolated crossings through strategiestraced to the timers using fuzzy control and cluster analysis. The objective is to control, adaptively, the flow of vehicles at a crossing by means of a timing plan applied to traffic lights, avoiding or decreasing traffic jams. The proposed models take into account crossings that present Single Exit Condition (CSU), that is, crossings with at least one origin that has only one permissible destination, in contrast to conventional models, which are applicable only to intersections where each origin is associated with more than one destination. The models are composed of three main parts: the first part consists of the estimation of the OD matrix (origin - destination) which is based on Kalman filtering from the traffic count at the crossroads of the study city. This data is used as input to perform the second part, which consists of using clustering techniques to extract the fuzzy sets, and with that, insert them into the fuzzy controller that represents the third part of the methodology proposed here, where the best time for the traffic light is estimated.