交通运输系统工程与信息 ›› 2008, Vol. 8 ›› Issue (5): 44-49 .

• 智能交通系统与信息技术 • 上一篇    下一篇

非集计模型在交通方式结构预测中的应用

张浩然;任 刚;王 炜*   

  1. 东南大学 交通学院 江苏 南京 210096
  • 收稿日期:2008-05-14 修回日期:2008-08-12 出版日期:2008-10-25 发布日期:2008-10-25
  • 通讯作者: 王 炜
  • 作者简介:张浩然(1974-),男,河南洛阳人,博士生。
  • 基金资助:

    国家“973”计划项目(2006CB705500);国家自然科学基金项目(50608018)。

Application of Discrete Choice Model in Traffic Mode Structure Forecasting

ZHANG Hao-ran;REN Gang;WANG Wei   

  1. School of Transportation, Southeast University, Nanjing 210096, China
  • Received:2008-05-14 Revised:2008-08-12 Online:2008-10-25 Published:2008-10-25
  • Contact: WANG Wei

摘要: 建立出行者基本属性与交通方式选择的关系模型,研究影响和引导城市交通方式结构的有效措施。采用非集计模型建立出行者个人属性、家庭属性和出行属性与个体出行方式选择的函数关系,从城市统计资料中获取城市居民个人属性、家庭属性和出行属性数据,应用非集计模型来推算和预测交通方式结构。居民出行交通方式选择与个人属性、家庭属性和出行属性之间有较稳定的关系,其随着时间的推移变化甚微。非集计模型所推算的交通方式结构较为精确,用于交通方式结构的预测是可行的。所建立的模型亦用于研究影响交通方式选择的关键因素。非集计模型可用于交通方式结构的调整和优化,通过对可控影响因素的引导和调整,达到优化交通方式结构的目的。

关键词: 交通方式划分, 交通方式结构, 非集计模型, 预测

Abstract: To build the relational model between fundamental characteristics of travelers and trip mode choice, effective measures that impact and guide urban trip mode structure have been studied. Besides, the discrete choice model has been used to build the functional relationship between trip mode choice and personal characteristics, family characteristics and travel characteristics of travelers. Personal characteristics, family characteristics and travel characteristics from statistics data of urban residents have also been obtained. What’s more, the discrete choice model has been used to deduce the trip mode structure. There are stable relations between trip mode split and personal characteristics, family characteristics and trip characteristics, which change little with the change of time. The trip model split deduced by the discrete choice model is relatively accurate, which is used to forecast whether the trip mode structure is feasible. The model built can also be used to study the key factors that influence traffic model choice. The discrete choice model can be used to restructure and optimize the urban trip mode structure. Through the guidance and adjustment of controllable factors, the purpose of optimizing urban trip mode structure can be achieved.

Key words: trip mode split, trip mode structure, discrete choice model, forecasting

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