A Hybrid Short-Term Forecasting Model of Passenger Flow on High-Speed Rail considering the Impact of Train Service Frequency. (20th December 2017)

• Record Type: Journal Article
• Authors: Lai, Qingying; Liu, Jun; Luo, Yongji; Ma, Minshu
• Other Names: Giorgio Ivan Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2017(2017)
• Publication Date: 2017-12-20
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2017/1828102
• Languages: English
• ISSNs: 1024-123X

Abstract

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.