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A Passenger Flow Analysis Method Through Ride Behaviors on Massive Smart Card Data

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2017)

Abstract

In transportation business, the passenger flow analysis counts the ridership of given bus stops on given time duration. On the smart card data from the card readers of buses, the calculation of passenger flow faces challenges: the accuracy or the latency is blamed, and the scalability is poor on large volume data. In this paper, we propose an effective method on massive smart card data, in which ride behaviors are modeled and the passenger flow can be achieved and efficiently. Our method is implemented by Hadoop MapReduce, and proves minute-level latencies on weekly historical data with nearly linear scalability.

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Acknowledgments

This work was supported by the Youth Program of National Natural Science Foundation of China (Nos. 61702014, 61602437), Beijing Natural Science Foundation (No. 4162021), R&D General Program of Beijing Education Commission (No. KM2015_10009007), the Key Young Scholars Foundation for the Excellent Talents of Beijing (No. 2014000020124G011), Top Young Innovative Talents of North China University of Technology (Nos. XN018022, XN072-001) and Youth Innovation Foundation of North China University of Technology (No. 1473-1743028).

Author information

Authors and Affiliations

  1. Data Engineering Institute, North China University of Technology, Beijing, 100144, China

    Weilong Ding, Zhuofeng Zhao & Han Li

  2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing, 100144, China

    Weilong Ding, Zhuofeng Zhao & Han Li

  3. Laboratory of Parallel Software and Computational Science, Institute of Software, Chinese Academy of Sciences, Beijing, 100080, China

    Yaqi Cao

  4. Beijing E-Hualu Information Technology Co., Ltd., Beijing, 100043, China

    Yang Xu

Authors
  1. Weilong Ding
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  2. Zhuofeng Zhao
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  3. Han Li
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  4. Yaqi Cao
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  5. Yang Xu
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Corresponding author

Correspondence to Weilong Ding .

Editor information

Editors and Affiliations

  1. Edinburgh Napier University, Edinburgh, UK

    Imed Romdhani

  2. Guangdong University of Petrochemical Technology, Maoming, China

    Lei Shu

  3. Osaka University, Osaka, Japan

    Hara Takahiro

  4. China University of Geosciences, Beijing, China

    Zhangbing Zhou

  5. University of Nebraska–Lincoln, Lincoln, UK

    Timothy Gordon

  6. School of Computer Science, China University of Geosciences, Wuhan, Hubei, China

    Deze Zeng

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Ding, W., Zhao, Z., Li, H., Cao, Y., Xu, Y. (2018). A Passenger Flow Analysis Method Through Ride Behaviors on Massive Smart Card Data. In: Romdhani, I., Shu, L., Takahiro, H., Zhou, Z., Gordon, T., Zeng, D. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 252. Springer, Cham. https://doi.org/10.1007/978-3-030-00916-8_35

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  • DOI: https://doi.org/10.1007/978-3-030-00916-8_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00915-1

  • Online ISBN: 978-3-030-00916-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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