A GA-Based Fuzzy Traffic Controller for an Intersection with Time-Varying Flow Rate

Nam-Chul HUH  Byeong Man KIM  Jong Wan KIM  Seung Ryul MAENG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E86-D   No.7   pp.1270-1279
Publication Date: 2003/07/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Artificial Intelligence, Cognitive Science
Keyword: 
fuzzy traffic controller,  genetic algorithm,  traffic volume,  automatic generation of membership functions,  

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Summary: 
Many fuzzy traffic controllers adjust the extension time of the green phase with the fuzzy input variables, arrival and queue. However, in our experiments, we found that the two input variables are not sufficient for an intersection where traffic flow rates change and thus, in this paper, traffic volume is used as an additional variable. Traffic volume is defined as the number of vehicles entering an intersection every second. In designing a fuzzy traffic controller, an ad-hoc approach is usually used to find membership functions and fuzzy control rules showing good performance. That is, initial ones are generated by human operators and modified many times based on the results of simulation. To partially overcome the limitations of the ad-hoc approach, we use genetic algorithms to automatically determine the membership functions for terms of each fuzzy variable when fuzzy control rules are given by hand. The experimental results indicate that a fuzzy logic controller with volume variable outperforms conventional ones with no volume variable in terms of the average delay and the average velocity. Also, the controller shows better performance when membership functions generated by a genetic algorithms instead of ones generated by hand are used.