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The simulation of passengers' time-space characteristics using ticket sales records with insufficient data

机译：使用数据不足的机票销售记录模拟乘客的时空特征

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摘要

It is a very common approach for any business to analyze their historical sales records to adjust operation strategy. Recently, Taiwan Railway Administration, a government-owned railway operator, faces serious competitions from other transportation systems. It becomes very urgent for the operator to modify its timetables to meet demand patterns for increasing revenue. The key issue is how to estimate passengers' time-space characteristics. For railroads with advanced automatic fare collection systems and simple service patterns, the estimation of passenger flow may not be difficult since detailed travel information is available. However, for systems with mixed traffic and insufficient ticket sales records, it requires a scientific method to deduce actual travel patterns from limited information. This study tried to establish such a model to reconstruct the time-space distribution of passenger flow. The model has been applied to Taiwan Railway Administration to estimate passenger flow. The result is very useful for decision makers to assess the utilization of train capacities and to adjust service plans, such as adding/deleting train services, changing stopping patterns, or modifying service termini. The proposed model can be applied to other railroads with mixed traffic operations and insufficient ticket sales records.
机译：对于任何企业来说，分析其历史销售记录以调整运营策略都是一种非常普遍的方法。最近，国有铁路运营商台湾铁道管理局面临来自其他运输系统的严峻竞争。对于运营商来说，更改时间表以满足增加收入的需求模式变得非常紧迫。关键问题是如何估计乘客的时空特征。对于具有先进的自动票价收集系统和简单服务模式的铁路，由于可以获得详细的旅行信息，因此对客流的估计可能并不困难。但是，对于流量混合且票证销售记录不足的系统，需要一种科学的方法来从有限的信息中推断出实际的出行方式。本研究试图建立这样一种模型来重建客流的时空分布。该模型已应用于台湾铁路局以估算客流。该结果对于决策者评估火车容量的利用并调整服务计划（例如添加/删除火车服务，更改停车方式或修改服务终点）非常有用。所提出的模型可以应用于交通运营混合且售票记录不足的其他铁路。

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