Journal of Transportation Systems Engineering and Information Technology ›› 2018, Vol. 18 ›› Issue (3): 108-112.

• Systems Engineering Theory and Methods • Previous Articles     Next Articles

An Approach to Classify the Public Transit Users Based on Macro & Micro Nested Data

SUN Shi-chao   

  1. Transportation Engineering College, Dalian Maritime University, Dalian 116026, Liaoning, China
  • Received:2017-12-28 Revised:2018-03-03 Online:2018-06-25 Published:2018-06-25

一种基于宏微观数据嵌套的公交用户细分方法

孙世超*   

  1. 大连海事大学 交通运输工程学院,辽宁 大连 116026
  • 作者简介:孙世超(1988-),男,辽宁大连人,讲师,博士.
  • 基金资助:

    国家自然科学基金/National Natural Science Foundation of China(51478350);中央高校基本科研业务费专项资金/ The Fundamental Research Funds for the Central Universities(3132016301).

Abstract:

This paper proposes an approach to classify the transit users based on macro & micro nested data. The approach can link the interviewee in survey data and the cardholder in smartcard database, by the use of card number recognition and the trip chain matching method. So we can simultaneously access to the travel behavior of cardholders and also the microcosmic social attribute and the willingness of individual information, remedying the lack of a single data source analysis. In the empirical analysis in Xiamen, China, the success rate of data link is 70.5%. Finally, combined with this data, the two dimensions of transit travel behavior and attitude will be crossanalyzed to realize the classification of different groups of transit users.

Key words: urban traffic, classification method, macro &, micro nested data, public transit users, multi-source data

摘要:

针对公交用户管理,本文提出一种基于宏微观数据嵌套的公交用户细分方法.该方法能够通过卡号识别及公交出行链信息对照等手段,建立问卷调查受访者与数据库中公交IC卡持卡者之间的匹配链接,即同时获取持卡者公交使用行为在刷卡数据样本总体中的宏观聚类情况,以及问卷调查数据中微观个体的社会属性与意愿信息,形成宏微观数据的互补嵌套,弥补单一数据源分析所面临的不足.在厦门市的实证分析中,数据链接的成功率达到70.5%.最终,结合该融合数据,从公交使用行为模式及态度意愿两个维度对公交用户进行交叉分类,实现公交用户不同组群的细分.

关键词: 城市交通, 人群细分方法, 宏微观数据嵌套, 公交用户, 多源数据

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