Development of High-Speed Railway Travel Assignment Algorithm based on Station Choice Probability

Young Hyun Seo, Jiyoung Song, Ho Chan Kwak, Seunghee Ryu, Seungmo Kang

Research output: Contribution to journalArticlepeer-review

Abstract

The travel assignment is a step of loading inter-zonal trips in the traditional travel demand forecasting model, and the optimal strategy algorithm is used the most to assign railway trips. The algorithm has a limitation that trips are con¬centrated from one zone to one station. Therefore, this study aims to develop a high-speed rail travel assignment algorithm considering station choice probabilities by high-speed railway station using O/D and network data from the Korea Trans¬port Database (KTDB). The distance between the centroid and high-speed railway stations and the train frequency at the stations are considered as independent variables, and the algorithm is developed to estimate station choice probability and high-speed railway travel volume. The prediction results are superior to those of the existing optimal strategy algorithm for major stations. The proposed algorithm will be used to predict high-speed railway travel in regions influenced by several high-speed railway stations.

Original languageEnglish
Pages (from-to)818-827
Number of pages10
JournalJournal of the Korean Society for Railway
Volume24
Issue number9
DOIs
Publication statusPublished - 2021 Sep

Keywords

  • Demand forecasting
  • High-speed rail
  • Ktdb
  • Station choice probability
  • Travel assignment

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Automotive Engineering
  • Transportation
  • Energy Engineering and Power Technology
  • Strategy and Management

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