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Detecting home location and trip purposes for cardholders by mining smart card transaction data in Beijing subway

机译：通过挖掘北京地铁中的智能卡交易数据来检测持卡人的住所位置和出行目的

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摘要

Automatic fare collection (AFC) system archives massive and continuous trip information for each cardholder. Mining the smart card transaction data from AFC system brings new opportunities for travel behavior and demand modeling. This study focuses on detecting the home location and trip purposes for subway passengers (cardholders), based on the internal temporal-spatial relationship within multi-day smart card transaction data. A center-point based algorithm is proposed to infer the home location for each cardholder. In addition, a rule-based approach using the individual properties (home location and card type) of cardholders and the travel information (time and space) of each trip is established for trip purpose identification. The smart card data from Beijing subway in China is used to validate the effectiveness of the proposed approaches. Results show that 88.7% of passengers' home locations and four types of trip purposes (six subtypes) can be detected effectively by mining the card transaction data in one week. The city-wide home location distribution of Beijing subway passengers, and travel behavior with different trip purposes are analyzed. This study provides us a novel and low-cost way for travel behavior and demand research.
机译：自动票价收集（AFC）系统为每个持卡人存档大量连续的旅行信息。从AFC系统中挖掘智能卡交易数据为旅行行为和需求建模带来了新的机会。这项研究的重点是基于多天智能卡交易数据中的内部时空关系，检测地铁乘客（持卡人）的住所位置和出行目的。提出了一种基于中心点的算法来推断每个持卡人的家乡位置。此外，建立了基于规则的方法，利用持卡人的个人属性（家庭位置和卡类型）以及每次行程的行程信息（时间和空间）来识别行程目的。来自中国北京地铁的智能卡数据用于验证所提出方法的有效性。结果表明，通过一周内的卡交易数据挖掘，可以有效地检测出88.7％的乘客家中位置和四种旅行目的（六个子类型）。分析了北京地铁乘客在整个城市的家庭位置分布，以及不同出行目的的出行行为。这项研究为我们提供了一种新颖且低成本的出行行为和需求研究方法。

著录项

  • 来源
    《Transportation》 |2018年第3期|919-944|共26页
  • 作者

    Zou Qingru; Yao Xiangming; Zhao Peng; Wei Heng; Ren Hui;

  • 作者单位

    Beijing Jiaotong Univ, Sch Traff & Transportat, 3 Shangyuancun, Beijing 100044, Peoples R China;

    Beijing Jiaotong Univ, Sch Traff & Transportat, 3 Shangyuancun, Beijing 100044, Peoples R China;

    Beijing Jiaotong Univ, Sch Traff & Transportat, 3 Shangyuancun, Beijing 100044, Peoples R China;

    Univ Cincinnati, Coll Engn & Appl Sci, 2600 Clifton Ave, Cincinnati, OH 45220 USA;

    Univ Cincinnati, Coll Engn & Appl Sci, 2600 Clifton Ave, Cincinnati, OH 45220 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Smart card data; Home location detection; Trip purposes identification; Subway passenger; Data mining;

    机译：智能卡数据;家庭位置检测;出行目的识别;地铁乘客;数据挖掘;

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