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Estimation of rail passenger flow and system utilization with ticket transaction and gate data

Author

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  • Yung-Cheng (Rex) Lai
  • Chung-Wei Huang
  • Yu-Ting Hsu

Abstract

Capturing the dynamics in passenger flow and system utilization over time and space is extremely important for railway operators. Previous studies usually estimated passenger flow using automatic fare collection data, and their applications are limited to a single stopping pattern and/or a single type of ticket. However, the conventional railway in Taiwan provides four types of ticket and five types of train service with a number of stopping patterns. This study develops a comprehensive framework and corresponding algorithms to map passenger flow and evaluate system utilization. A multinomial logit model is constructed and incorporated in the algorithms to estimate passenger train selection behavior. Results from the empirical studies demonstrate that the developed framework and algorithms can successfully match passengers with train services. With this tool, operators can efficiently examine passenger flow and service utilization, thereby quickly adjusting their service strategies accordingly to improve system performance.

Suggested Citation

  • Yung-Cheng (Rex) Lai & Chung-Wei Huang & Yu-Ting Hsu, 2018. "Estimation of rail passenger flow and system utilization with ticket transaction and gate data," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(7), pages 752-778, October.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:7:p:752-778
    DOI: 10.1080/03081060.2018.1504184
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    Cited by:

    1. Wang, Ying & Zhao, Ou & Zhang, Limao, 2024. "Modeling urban rail transit system resilience under natural disasters: A two-layer network framework based on link flow," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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