交通运输系统工程与信息

交通运输系统工程与信息 ›› 2012, Vol. 12 ›› Issue (6): 164-169.

• 系统工程理论与方法 • 上一篇    下一篇

基于社区发现的交通控制子区优化方法研究

王力*，陈智，刘小明，李正熙   

  1. 北方工业大学 城市道路交通智能控制技术北京市重点实验室，北京 100144
  • 收稿日期:2012-06-26 修回日期:2012-09-02 出版日期:2012-12-25 发布日期:2012-12-29
  • 作者简介:王力（1978-），男，安徽肥东人，副教授，博士后.
  • 基金资助:

    “863”国家高技术研究发展计划项目(2012AA112401).

Sub Control Area Division Optimization of Traffic Network Based on Community Discovery

WANG Li, CHEN Zhi, LIU Xiao-ming, LI Zheng-xi   

  1. Beijing Key Lab of Urban Traffic Control Technology, North China University of China, Beijing 100144, China
  • Received:2012-06-26 Revised:2012-09-02 Online:2012-12-25 Published:2012-12-29

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被引次数

4

摘要：

传统区域交通信号控制系统对控制子区的划分未充分考虑交通网络拓扑结构的复杂特性，由工程师根据交叉口物理距离及现场交通流特性来确定，难以保证其客观性和统一性.本文以社区模块度为评价指标，利用凝聚社区发现算法实现了区域交通信号控制系统的控制子区划分；进而，以北京市望京地区为实验案例进行应用测试，利用VISSIM仿真平台比较了本文方法和传统方法在SCOOT系统控制条件下的控制效果.仿真结果表明，在高峰、平峰、低峰等不同交通需求下，区域主干道的平均旅行时间有明显下降，区域内车均停车延误、车均停车次数、车均延误、平均车速等指标均有改善，验证了方法的有效性和可行性，为区域交通信号控制系统结构优化提供了新方法.

关键词: 智能交通, 信号系统优化；社区发现, 子区划分, 复杂网络

Abstract:

Urban traffic control network is typical complex network. Traditional regional traffic signal control system such as SCOOT, SCATS are normally divided into subcontrol areas according to link length between nodes and traffic flow. However, it does not take full consideration of the complex network topology characteristics. In this paper, with the community module degree as evaluation indexes, traffic signal control subareas of urban traffic signal network are divided using the community discovery algorithm. Then the PCSCOOT system and VISSIM simulation platform are used as testbed based on Wangjing District in Beijing, China. Traditional method and the proposed method are both used to compare traffic indexes of some main urban road and the whole region. Simulation results show that the proposed method could improve average stop delay, average stops, average delay and the average speed per vehicle.

Key words: intelligent transportation, traffic control system optimization, community discovery, subcontrolarea division, complex network

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