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Type-2 fuzzy multi-intersection traffic signal control with differential evolution optimization

delete2014-11-01
delete70
PRE
AI
D
Dipti Srinivasan
X
Xiaobo Lu *
Z
Zhe Sun
W
Weili Zeng
DOI:10.1016/j.eswa.2014.06.022delete
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摘要

摘要

En 中文
This paper proposes a multi-agent type-2 fuzzy logic control (FLC) method optimized by differential evolution (DE) for multi-intersection traffic signal control. Type-2 fuzzy sets can deal with models' uncertainties efficiently because of its three-dimensional membership functions, but selecting suitable parameters of membership functions and rule base is not easy. DE is adopted to decide the parameters in the type-2 fuzzy system, as it is easy to understand, simple to implement and possesses low space complexity. In order to avoid the computational complexity, the expert rule base and the parameters of membership functions (MF) are optimized by turns. An eleven-intersection traffic network is studied in which each intersection is governed by the proposed controller. A secondary layer controller is set in every intersection to select the proper phase sequence. Furthermore, the communication among the adjacent intersections is implemented using multi-agent system. Simulation experiments are designed to compare communicative type-2 FLC optimized by DE with type-1 FLC, fixed-time signal control, etc. Experimental results indicate that our proposed method can enhance the vehicular throughput rate and reduce delay, queue length and parking rate efficiently. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
Type-2 fuzzy logic control
Differential evolution (DE)
Multi-agent system
Traffic signal control
Phase sequence
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期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
3.0W
被引数:
10.2W

机构

S
southeast university - china
学者数:
5.3W
论文数: 4.9W
被引数: 57
N
National University of Singapore
学者数:
7.6W
论文数: 6.5W
被引数: 11.4W
Z
zhejiang university
学者数:
17.7W
论文数: 12.1W
被引数: 152
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