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)