Estimation method for railway passengers' train choice behavior with smart card transaction data
Estimation method for railway passengers' train choice behavior with smart card transaction data
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DOI：
10.1007/s11116-010-9290-0
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发表时间：
2010-09-01
期刊：
影响因子：
4.3
通讯作者：
Asakura, Yasuo
中科院分区：
文献类型：
--
作者：
Kusakabe, Takahiko;Iryo, Takamasa;Asakura, Yasuo
智能卡系统已成为日本收取公共交通费用的主要方法。通过智能卡获得的交易数据产生了大量关于乘客如何使用公共交通的存档信息。这些数据有可能用于建模乘客行为和公共交通需求。本研究的重点是铁路乘客的列车选择。如果能够在很长一段时间内确定每个乘客的列车选择，则该信息将有助于改善铁路公司的客户关系管理和改进列车时刻表。本研究的目的是开发一种方法来估计每个智能卡保持器登上哪列火车。本文提出了一种方法和算法，估计使用长期的交易数据。为了验证估计的计算时间和准确性，使用日本铁路公司提供的实际交易数据进行了实证分析。结果表明，所提出的方法是能够估计乘客的使用模式，从智能卡交易数据收集了很长一段时间。
Smart card systems have become the predominant method of collecting public transport fares in Japan. Transaction data obtained through smart cards have resulted in a large amount of archived information on how passengers use public transportation. The data have the potential to be used for modeling passenger behavior and demand for public transportation. This study focused on train choices made by railway passengers. If each passenger's train choice can be identified over a long period of time, this information would be useful for improving the customer relationship management of the railway company and for improving train timetables. The aim of this study was to develop a methodology for estimating which train is boarded by each smart card holder. This paper presents a methodology and an algorithm for estimation using long-term transaction data. To validate the computation time and accuracy of the estimation, an empirical analysis is carried out using actual transaction data provided by a railway company in Japan. The results show that the proposed method is capable of estimating passenger usage patterns from smart card transaction data collected over a long time period.