交通运输系统工程与信息 ›› 2011, Vol. 11 ›› Issue (2): 84-90.

• 系统工程理论与方法 • 上一篇    下一篇

城市群区域公路网节点重要度评估方法研究

宋新生*a, b,王啸啸a, b,李爱增a, b,张蕾a,b   

  1. 河南城建学院a. 交通工程系; b.城市交通研究中心,河南 平顶山 467036
  • 收稿日期:2010-11-09 修回日期:2011-02-21 出版日期:2011-04-28 发布日期:2011-05-10
  • 通讯作者: 宋新生
  • 作者简介:宋新生(1970-),男,河南郑州人,副教授,博士.

Node Importance Evaluation Method for Highway Network of Urban Agglomeration

SONG Xin-shenga,b, WANG Xiao-xiao a,b, LI Ai-zeng a,b , ZHANG Leia, b   

  1. a. Department of Traffic Engineering; b. Urban Transportation Research Center,Henan University of Urban Construction, Pingdingshan 467036, Henan, China
  • Received:2010-11-09 Revised:2011-02-21 Online:2011-04-28 Published:2011-05-10
  • Contact: SONG Xin-sheng

摘要: 城市群是区域城市大系统中具有较强活力的子系统,区域优势显著,在空间联系上具有网络性特点. 客观准确地评价各节点的重要度,是城市群区域公路网布局规划中的一个重要环节. 针对城市群的特点,在公路网节点重要度评估中增加了城市流强度评价指标,节点重要度计算中采用了因子分析法进行客观赋权以避免各指标主观赋权的随意性,为进一步更好区分各节点的重要度等级,采用K-Means聚类方法客观划分了城市节点重要度的类别. 最后以中原城市群为例进行了节点重要度的实例计算,结果表明本文方法具有较好的应用价值.

关键词: 交通工程, 公路运输, 节点重要度评估, 因子分析, 城市群公路网, 城市流强度, 聚类

Abstract: Urban agglomeration is a strong vitality subsystem of large regional city system with significant regional advantages in space and linked features in network. Objective and accurate assessment of each node importance of highway network is a vital part for regional road network layout planning. Problems in the existing node important evaluation methods are analyzed. And for the characteristics of urban agglomeration, urban flow intensity is included into node importance assessment indexes system. Factor analysis is used as an objective method to avoid random subjective values in node importance calculation. K-Means clustering method is used to distinguish degree level of each node importance for further analysis. Finally, central china city agglomeration is taken as an application example, and the result shows the method proposed in this paper has good practical value in application.

Key words: traffic engineering, highway transportation, node importance evaluation, factor analysis, urban agglomeration highway network, urban flow intensity, cluster

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