Real-time traffic signal control for optimization of traffic jam probability

被引：2

作者：

Cui, Cheng-You ^{[1
]}

Shin, Ji-Sun ^{[1
]}

Miyazaki, Michio ^{[2
]}

Lee, Hee-Hyol ^{[1
]}

机构：

[1] Waseda Univ, Tokyo, Japan

[2] Kanto Gakuin Univ, Yokohama, Kanagawa, Japan

来源：

ELECTRONICS AND COMMUNICATIONS IN JAPAN | 2013年 / 96卷 / 01期

关键词：

traffic jam; traffic signal control; Bayesian network; predicted probabilistic distribution; particle swarm optimization; cellular automaton traffic model; CELLULAR-AUTOMATON MODEL;

D O I：

10.1002/ecj.11436

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Real-time traffic signal control is an integral part of an urban traffic control system. It can control traffic signals online according to variations of traffic flow. In this paper we propose a new method for a real-time traffic signal control system. The system uses a cellular automaton model and a Bayesian network model to predict probabilistic distributions of standing vehicles, and uses particle swarm optimization to calculate the optimal traffic signals. A simulation based on real traffic data was carried out to show the effectiveness of the proposed CAPSOBN real-time traffic signal control system using a micro traffic simulator. (c) 2012 Wiley Periodicals, Inc. Electron Comm Jpn, 96(1): 113, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ecj.11436

引用

页码：1 / 13

页数：13

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