Intelligent Traffic Signal Control Approach Based on Fuzzy-Genetic Algorithm

2008 ◽  
Author(s):  
Xiangjun Cheng ◽  
Zhaoxia Yang
Keyword(s):  
Genetic Algorithm ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Control Approach ◽  
Fuzzy Genetic Algorithm ◽  
Fuzzy Genetic

scholarly journals A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
S. M. Odeh ◽  
A. M. Mora ◽  
M. N. Moreno ◽  
J. J. Merelo
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Algorithm ◽  
Fuzzy Logic Controller ◽  
Decision Rules ◽  
Great Influence ◽  
Traffic Signal ◽  
Signal System ◽  
Fuzzy Genetic Algorithm ◽  
Definition Of ◽  
Fuzzy Genetic

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.

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