Date of Award
1996
Document Type
Thesis
Publisher
Edith Cowan University
Degree Name
Master of Science
School
School of Mathematics, Information Technology and Engineering
Faculty
Faculty of Science, Technology and Engineering
First Supervisor
Masoud Mohammadian
Second Supervisor
Dr Jim Millar
Abstract
In this thesis, we present a fuzzy logic control scheme to regulate the flow of traffic approaching a set of intersections. An adaptive Fuzzy Logic Traffic Controller (FLTC) is used to adjust the green phase split of the north-south and east-west approaches of a set of traffic signals based on the actual traffic approaching the intersection. Each intersection is coordinated with its neighbouring intersections by adjusting the offset of the local intersection. The offset is adjusted by a local fuzzy logic controller loacted at each intersection. A new fuzzy control scheme, using a supervisory Fuzzy Logic Controller, is also proposed for adjusting the offset. The fuzzy knowledge base of the supervisory Fuzzy Logic Controller is automatically generated by Genetic Algorithms (GAs). The fuzzy rules generated by the integrated Fuzzy Logic and Genetic Algorithm architecture is found to be effective in optimising the traffic flow. The effectiveness of the above fuzzy control scheme is established through simulations of the traffic flow approaching an isolated intersection, two adjacent intersections, and a set of three intersections. The superiority of adjusting offset using a supervisory fuzzy logic controller is established through simulations.
Recommended Citation
Nainar, I. (1996). An adaptive fuzzy logic controller for intelligent networking and control. Edith Cowan University. Retrieved from https://ro.ecu.edu.au/theses/1466