Design of an optimal ANFIS traffic signal controller by using cuckoo search for an isolated intersection


Autoria(s): Araghi, Sahar; Khosravi, Abbas; Creighton, Douglas
Data(s)

01/01/2015

Resumo

An optimal design of Adaptive Neuro-Fuzzy Inference System (ANFIS) traffic signal controller is presented in this paper. The proposed controller aims to adjust a set of green times for traffic lights in a single intersection with the purpose of minimizing travel delay time and traffic congestion. The ANFIS controller is trained, to learned how to set green times for each traffic phase. This intelligent controller uses the Cuckoo Search (CS) algorithm to tune its parameters during the learning pried. Evaluating the performance of the proposed controller in comparison with the performance of a FLS controller (FLC) with predefined rules and membership functions, and also three fixed-Time controllers, illustrates the better performance of the optimal ANFIS controller against the other benchmark controllers.

Identificador

http://hdl.handle.net/10536/DRO/DU:30082490

Idioma(s)

eng

Publicador

IEEE

Relação

http://dro.deakin.edu.au/eserv/DU:30082490/araghi-designofanoptimal-2015.pdf

http://dro.deakin.edu.au/eserv/DU:30082490/araghi-designofanoptimal-evid1-2015.pdf

http://dro.deakin.edu.au/eserv/DU:30082490/araghi-designofanoptimal-evid2-2015.pdf

http://www.dx.doi.org/10.1109/SMC.2015.363

Direitos

2015, IEEE

Palavras-Chave #Science & Technology #Technology #Computer Science, Cybernetics #Computer Science, Information Systems #Computer Science, Theory & Methods #Computer Science #FUZZY-LOGIC
Tipo

Conference Paper