›› 2010, Vol. 49 ›› Issue (增刊01): 43-47.

• 论文 • 上一篇    下一篇

基于GIS支持的出行行为时间、空间及序列特征研究

赵一斌1, 石心怡2, 关志超1   

  1. (1.深圳市城市交通规划研究中心, 广东 深圳 518034;2.长安大学公路学院, 陕西 西安 710064)
  • 收稿日期:2010-03-25 修回日期:1900-01-01
  • 通讯作者: 关志超

An Analytical Framework for Travelactivity Pattern AnalysisA GIS Approach

ZHAO Yibin1, SHI Xinyi2, GUAN Zhichao1   

  1. (1.Shenzhen Urban Transport Planning Center,Shenzhen 518040,China;2.School of Highway, Chang'an University,Xian 710064,China)
  • Received:2010-03-25 Revised:1900-01-01

摘要: 1970年代以来,西方学者逐渐认识到传统的四步骤交通需求分析模型(Fourstep Traffic Analysis)在微观尺度上的不足,开始关注基于行为的交通需求分析模型(Behavioral Traffic Analysis Model)。基于个人出行行为(Activitybased approach)的研究方法因其能很好的描述个人特征、表达各类人群之间在出行需求、模式等方面的区别而逐渐被学术和各生产部门所关注,基于行为的出行行为调查也逐渐成为对于一个区域交通规划的重要信息依据和决策支持基础。但是,在对于获取到的出行数据分析方面,一直没有一个完整的框架。文中在人类活动需求的理论分析基础上,提出一个基于时间、空间和序列特征的出行行为分析理论框架,并以此为基础设计出相应的分析功能。


关键词: 出行行为特征分析, 时空特征, 序列特征, 时态GIS

Abstract: Transportation studies have experienced a paradigm shift in the 1970s. Researchers started to take an activitybased approach to transportation studies, as the distributions of activities in space and time can determine where and when people travel. More studies focus on individual activities because the relationships between activities and travels can be clearly examined at the individual level. There was not a general accepted model to represent the complex temporal, spatial and tabular attribute of travelactivity before Time Geography was adopted to depict travelactivity in space and time. Recent development in travelactivity pattern study reveals that sequential order of travelactivity is another important dimension to depict the travelactivity pattern. However, there is no general accepted analytical framework in the research community that identifies the principal characteristics of travelactivity patterns and provides useful analytical function as well. Based on a conceptual analysis of daily travelactivity scenario, this research identifies three principal dimensions of travelactivity characteristics: spatial, temporal and sequential patterns. Consequently, an analytical framework is formed to help researchers to look at the travelactivity from different perspectives. Some analytical functions/tools are designed and added to the framework to improve the usefulness of the framework. The framework is implemented in a commercial GIS platform by extending the ESRI GeoDatabase and ArcObjects functions. A pilot study is conducted to test the usefulness and effectiveness of the framework.

Key words: travelactivity patterns analysis, spatiotemporal pattern, sequential pattern, temporal GIS

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