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ANFIS traffic signal controller for an isolated intersection

conference contribution
posted on 2014-01-01, 00:00 authored by Sahar Araghi, Abbas KhosraviAbbas Khosravi, Douglas CreightonDouglas Creighton
Traffic signal controlling is one of the solutions to reduce the traffic congestion in cities. To set appropriate green times for traffic signal lights, we have applied Adaptive Neuro-Fuzzy Inference System (ANFIS) method in traffic signal controllers. ANFIS traffic signal controller is used for controlling traffic congestion of a single intersection with the purpose of minimizing travel delay time. The ANFIS traffic controller is an intelligent controller that learns to set an appropriate green time for each phase of traffic signal lights at the start of the phase and based on the traffic information. The controller uses genetic algorithm to tune ANFIS parameters during learning time. The results of the experiments show higher performance of the ANFIS traffic signal controller compared to three other traffic controllers that are developed as benchmarks. One of the benchmarks is GA-FLC (Araghi et al., 2014), next one is a fixed-FLC, and a fixed-time controller with three different values for green phase. Results show the higher performance of ANFIS controller.

History

Event

Fuzzy Computation Theory and Applications. Conference (2014: Rome, Italy)

Pagination

175 - 180

Publisher

INSTICC Press

Location

Rome, Italy

Place of publication

[Rome, Italy]

Start date

2014-10-22

End date

2014-10-24

ISBN-13

9789897580536

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2014, INSTICC Press

Editor/Contributor(s)

A Dourado, J Cadenas, J Filipe

Title of proceedings

FCTA 2014 : Proceedings of the International Conference on Fuzzy Computation Theory and Applications

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