Research of traffic signal control strategy based on the fuzzy control

被引：0

作者：

Yan, Xuebo ^{[1
]}

机构：

[1] Nanjing Commun Inst Technol, Nanjing, Jiangsu, Peoples R China

来源：

MATERIAL SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY II | 2014年 / 651-653卷

关键词：

Traffic lights; Green split; Intelligent transportation system;

D O I：

10.4028/www.scientific.net/AMM.651-653.486

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

To ease the traffic pressure on urban traffic signal control strategy research started. Dynamic change prediction analysis of traffic flow through the flow of information as a basis for fuzzy reasoning, automatically adjust the signal cycle, green ratio and phase control parameters, real-time signal timing to generate optimal solutions for optimal control effect. The results show that this method can effectively alleviate traffic congestion, meet the design expectations.

引用

页码：486 / 490

页数：5

共 6 条

[1]

Arel, 2010, IEEE T INTELL TRANSP, V4, P128

[2] Multi-agent model predictive control of signaling split in urban traffic networks [J].

de Oliveira, Lucas Barcelos ;

Camponogara, Eduardo .

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2010, 18 (01) :120-139

[3] Development and Evaluation of a Cooperative Vehicle Intersection Control Algorithm Under the Connected Vehicles Environment [J].

Lee, Joyoung ;

Park, Byungkyu .

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2012, 13 (01) :81-90

[4] Development of FPGA-based digital signal processing system for radiation spectroscopy [J].

Lee, Pil Soo ;

Lee, Chun Sik ;

Lee, Ju Hahn .

RADIATION MEASUREMENTS, 2013, 48 :12-17

[5]

Menouar Hamid., 2006, ITS WORLD C, P1

[6]

Zhou Binbin, 2014, J ZHENJIANG SHOREN U, V14, P1

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