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

Version 2 2024-06-04, 02:17
Version 1 2016-03-31, 10:20
conference contribution
posted on 2024-06-04, 02:17 authored by S Araghi, Abbas KhosraviAbbas Khosravi, Douglas CreightonDouglas Creighton
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.

History

Pagination

2078-2083

Location

Hong Kong, China

Start date

2015-10-09

End date

2015-10-12

ISBN-13

9781479986965

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2015, IEEE

Title of proceedings

SMC 2015 : Big Data Analytics for Human-Centric Systems. Proceedings of the 2015 IEEE International Conference on Systems, Man, and Cybernetics

Event

IEEE International Conference on Systems, Man, and Cybernetics (2015 : Hong Kong, China)

Publisher

IEEE

Place of publication

Piscataway, N.J.

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