Monitoring Public Transport Demand Using Data From Automated Fare Collection System

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Conference on Aviamechanical Engineering and Transport (AVENT); Irkutsk Natl Res Tech Univ, Irkutsk, RUSSIA; Irkutsk Natl Res Tech Univ, Irkutsk, RUSSIA

Год издания: 2018

Ключевые слова: transport demand, passenger flows, passenger trip, passengers' origin-destination trips

Аннотация: 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) "Krasnoyarskcitytrans".

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Издание

Журнал: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE: AVIAMECHANICAL ENGINEERING AND TRANSPORT (AVENT 2018)

Выпуск журнала: Vol. 158

Номера страниц: 5-12

ISSN журнала: 23525401

Место издания: PARIS

Издатель: ATLANTIS PRESS

Авторы

  • Fadeev A. (Siberian Fed Univ SibFU, Krasnoyarsk, Russia)
  • Alhusseini S. (Siberian Fed Univ SibFU, Krasnoyarsk, Russia)
  • Belova E.N. (Siberian Fed Univ SibFU, Krasnoyarsk, Russia)

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