DocumentCode
3728259
Title
Design of an Optimal ANFIS Traffic Signal Controller by Using Cuckoo Search for an Isolated Intersection
Author
Sahar Araghi;Abbas Khosravi;Doug Creighton
Author_Institution
Center for Intell. Syst. Res., Deakin Univ., Waurn ponds, VIC, Australia
fYear
2015
Firstpage
2078
Lastpage
2083
Abstract
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.
Keywords
"Delays","Vehicles","Adaptation models","Genetic algorithms","Detectors","Decision making"
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
Type
conf
DOI
10.1109/SMC.2015.363
Filename
7379495
Link To Document