Skip to main navigation Skip to search Skip to main content

Train schedule optimization based on schedule-based stochastic passenger assignment

  • J. Xie
  • , S.C. Wong*
  • , S. Zhan
  • , S.M. Lo
  • , Anthony Chen
    • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

29   Link opens in a new tab Citations (Scopus)

Abstract

In this study, we propose a new schedule-based itinerary-choice model, the mixed itinerary-size weibit model, to address the independently and identically distributed assumptions that are typically used in random utility models and heterogeneity of passengers’ perceptions. Specifically, the Weibull distributed random error term resolves the perception variance with respect to various itinerary lengths, an itinerary-size factor term is suggested to solve the itinerary overlapping problem, and random coefficients are used to model heterogeneity of passengers. We also apply the mixed itinerary-size weibit model to a train-scheduling model to generate a passenger-oriented schedule plan. We test the efficiency and applicability of the train-scheduling model in the south China high-speed railway network, and we find that it works well and can be applied to large real-world problems.
Original languageEnglish
Article number101882
JournalTransportation Research Part E: Logistics and Transportation Review
Volume136
Online published18 Feb 2020
DOIs
Publication statusPublished - Apr 2020

Research Keywords

  • Mixed itinerary-size weibit model
  • Schedule-based
  • Train scheduling

Access Output

Other Access Options

Check CityUHK Library

Permanent Link

Other Files and Links

Fingerprint

Dive into the research topics of 'Train schedule optimization based on schedule-based stochastic passenger assignment'. Together they form a unique fingerprint.
View full fingerprint

  • TBRS: Safety, Reliability, and Disruption Management of High Speed Rail and Metro Systems

    XIE, M. (Principal Investigator / Project Coordinator), BENSOUSSAN, A. (Co-Principal Investigator), LO, S. M. (Co-Principal Investigator), SHOU, B. (Co-Principal Investigator), SINGPURWALLA, N. D. (Co-Principal Investigator), TSE, W. T. P. (Co-Principal Investigator), TSUI, K. L. (Co-Principal Investigator), YU, Y. (Co-Principal Investigator), YUEN, K. K. R. (Co-Principal Investigator), CHAN, A. B. (Co-Investigator), CHAN, N.-H. (Co-Investigator), CHIN, K. S. (Co-Investigator), CHOW, H. A. (Co-Investigator), Chow, W. K. (Co-Investigator), EDESESS, M. (Co-Investigator), GOLDSMAN, D. M. (Co-Investigator), Huang, J. (Co-Investigator), LEE, W. M. (Co-Investigator), LI, L. (Co-Investigator), LI, C. L. (Co-Investigator), LING, M. H. A. (Co-Investigator), LIU, S. (Co-Investigator), MURAKAMI, J. (Co-Investigator), NG, S. Y. S. (Co-Investigator), NI, M. C. (Co-Investigator), TAN, M.H.-Y. (Co-Investigator), Wang, W. (Co-Investigator), Wang, J. (Co-Investigator), WONG, C. K. (Co-Investigator), WONG, S. Y. Z. (Co-Investigator), WONG, S. C. (Co-Investigator), Xu, Z. (Co-Investigator), ZHANG, Z. (Co-Investigator), Zhang, D. (Co-Investigator), ZHAO, J. L. (Co-Investigator) & Zhou, Q. (Co-Investigator)

    1/01/16 → 31/12/21

    Project: Research

Cite this