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A Hybrid Short-Term Forecasting Model of Passenger Flow on High-Speed Rail considering the Impact of Train Service Frequency

Author

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  • Qingying Lai
  • Jun Liu
  • Yongji Luo
  • Minshu Ma

Abstract

Short-term forecasting of OD (origin to destination) passenger flow on high-speed rail (HSR) is one of the critical tasks in rail traffic management. This paper proposes a hybrid model to explore the impact of the train service frequency (TSF) of the HSR on the passenger flow. The model is composed of two parts. One is the Holt-Winters model, which takes advantage of time series characteristics of passenger flow. The other part considers the changes of TSF for the OD in different time during a day. The two models are integrated by the minimum absolute value method to generate the final hybrid model. The operational data of Beijing-Shanghai high-speed railway from 2012 to 2016 are used to verify the effectiveness of the model. In addition to the forecasting ability, with a definite formation, the proposed model can be further used to forecast the effects of the TSF.

Suggested Citation

  • Qingying Lai & Jun Liu & Yongji Luo & Minshu Ma, 2017. "A Hybrid Short-Term Forecasting Model of Passenger Flow on High-Speed Rail considering the Impact of Train Service Frequency," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-9, December.
    • Handle: RePEc:hin:jnlmpe:1828102
    DOI: 10.1155/2017/1828102
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