Bi-level optimization for eco-traffic signal system

Author(s):  
Hojin Jung ◽  
Saerona Choi ◽  
Byungkyu Brian Park ◽  
Haengju Lee ◽  
Sang Hyuk Son
Keyword(s):  
Author(s):  
S.U. Dampage ◽  
T.D. Munasingha ◽  
W.D.K Gunathilake ◽  
A.G. Weerasundara ◽  
D.P.D Udugahapattuwa
Keyword(s):  

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
S. M. Odeh ◽  
A. M. Mora ◽  
M. N. Moreno ◽  
J. J. Merelo

This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC) and Genetic Algorithms (GAs) and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecasting. They are, essentially, rule-based systems, in which the definition of these rules and fuzzy membership functions is generally based on verbally formulated rules that overlap through the parameter space. They have a great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a robust search in complex spaces. In this work, it has been used to adapt the decision rules of FLCs that define an intelligent traffic signal system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid algorithm show an improvement of up to 34% in the performance with respect to a standard traffic signal controller, Conventional Traffic Signal Controller (CTC), and up to 31% in the comparison with a traditional logic controller, FLC.


Author(s):  
Manoel Mendonca de Castro-Neto ◽  
Thomas Urbanik ◽  
Lee D. Han
Keyword(s):  

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