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Monitoring Public Transport Demand Using Data From Automated Fare Collection System

机译:使用自动票价系列系统的数据监控公共交通需求

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The paper considers the methodology of determining the public transport demand using the data from the non-cash fare collection system. The passenger's trip from the origin stop to the destination stop is determined by analyzing the sequence of payment transactions, which were recorded and stored by an automated fare collection system. In earlier works the task of determining the trips' boarding and alighting stops was not discussed for transportation vehicles with an exit-only AFC system - the passenger taps off or uses his/her smart card only when he/she gets off the vehicle - which is used in Russia. In addition, the determination of trips' boarding and alighting stops was based on the analysis of AFC data of one day only. In this case, the last trip's alighting stop is determined, based on the assumption that the passenger returns to the first trip's boarding stop of the day. In this paper, the task of determining passenger trips is based on the analysis of smart card transactions data not only for one day but also during the subsequent periods (up to 5 days). The analysis of the efficiency of the proposed algorithm was carried out with the use of 6.2 million non-cash transactions (for October, 2016), provided by the Municipal Public Institution of Krasnoyarsk city (MSE) "Krasnoyarskcltytrans".
机译:本文考虑使用来自非现金票价收集系统的数据确定公共交通需求的方法。通过分析由自动票价收集系统记录和存储的付款交易序列来确定乘客从原点停止到目标停止。在早期的工作中,没有讨论确定旅行和上升停止的任务,仅对仅用于退出AFC系统的运输车辆 - 只有当他/她下车时,乘客点击或使用他/她的智能卡 - 这用于俄罗斯。此外,旅行的登机和上升停止的确定是基于仅对一天的AFC数据的分析。在这种情况下,基于乘客返回当天的第一跳的登机停止的假设,最后确定最后一次行程的随天停止。在本文中,确定乘客旅行的任务是基于对智能卡交易数据的分析,不仅是一天,而且在随后的期间(最多5天)。通过克拉斯诺伊尔斯克市(MSE)“Krasnoyarskcltytrans”提供的620万次非现金交易(2016年10月),进行了拟议算法效率的分析。

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