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基于GIS的城市交通网络数据模型研究
引用本文:隋东,任刚,邵进达.基于GIS的城市交通网络数据模型研究[J].公路交通科技,2006,23(9):94-97.
作者姓名:隋东  任刚  邵进达
作者单位:1. 东南大学,交通学院,江苏,南京,210096;南京航空航天大学,民航学院,江苏,南京,210016
2. 东南大学,交通学院,江苏,南京,210096
基金项目:江苏省自然科学基金重点资助项目(BK2005205),东南大学科技基金资助项目(XJ0621246)
摘    要:针对城市交通需求预测中交通网络数据建模的特点和难度,提出了一个基于GIS的交通网络数据模型,并设计了模型的具体内容包括数据库表结构、交通网络拓扑结构表示法等。数据库表按节点、路段、转向、OD对以及交通区这5种网络基本要素分类设计。城市交通网络拓扑结构包括节点-路段和路段-转向两部分,前者采用邻接表来表示,后者则采用邻接表的拓展形式-路段邻接表。该模型集拓扑数据、空间数据和属性数据于一体,充分发挥了GIS和数据库技术的优点,并可表示出完整的节点-路段-转向拓扑关系,为计算机辅助城市交通需求预测奠定有效、详细的数据基础。

关 键 词:城市交通网络  数据模型  地理信息系统  交通需求预测
文章编号:1002-0268(2006)09-0094-04
收稿时间:2005-05-16
修稿时间:2005年5月16日

Study on GIS-based Data Model for Urban Transport Networks
SUI Dong,REN Gang,SHAO Jin-da.Study on GIS-based Data Model for Urban Transport Networks[J].Journal of Highway and Transportation Research and Development,2006,23(9):94-97.
Authors:SUI Dong  REN Gang  SHAO Jin-da
Institution:1. Transportation College, Southeast University, Jiangsu Nanjing 210096, China; 2. Civil Aviation College, Nanjing University of Aeronautics and Astronautics, Jiangsu Nanjing 210016, China
Abstract:Aiming at the characteristics and difficulties in modeling transport network data in urban travel demand forecast,a geographical information systems(GIS) based data model for urban transport networks is proposed,and then its contents including the structures of the database tables and the representations of the transport network topologies are designed.The database tables are designed for network elements of five types,i.e.node,link,turn,OD(origin-destination) pair,and traffic zone.The topologies of urban transport networks include the node-link relationship and the link-turn relationship,of which the former is represented by adjacency list and the latter is represented by link adjacency list,an extension to adjacency list.This model integrates the topological data,the spatial data and the attribute data,utilizes the advantages of GIS and database technologies,and is able to describe the complete node-link-turn topological relationships.Thus it establishes an efficient and detailed data foundation for the computer-aided urban travel demand forecast.
Keywords:urban transport network  data model  Geographic Information System(GIS)  travel demand forecast
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