Transfer demand prediction for timed transfer coordination in public transport operational control

L.M. Kieu, A. Bhaskar, P.E.M. Almeida, N.R. Sabar, Edward Chin Shin Chung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

Copyright © 2017 John Wiley & Sons, Ltd.Timed transfer coordination in public transit reduces passenger transfer time by providing seamless interconnected transfers. The problem arises when a Receiving Vehicle (RV) arrives to the transfer stop before a Feeding Vehicle (FV) carrying transferring passengers. Timed transfer coordination in operational control dynamically decides whether a RV is held at the transfer stop to allow transfers, or departs as scheduled. While transfer demand is essential for implementing timed transfer coordination, this variable is generally not available in public transit because of the lack of passenger transfer plans. The problem of acquiring this variable in real-time has also received limited attention in the related literature. This paper proposes a new method to dynamically predict the transfer demand. We anticipate the transferring probability from each individual passenger by examining historical travel itineraries. Three different types of models (simple analytical, statistical, and computation intelligence model) are developed to forecast the number of transferring passengers. Numerical experiments using observed Automatic Vehicle Location and Automatic Fare Collection data from South East Queensland, Australia show the accuracy and applicability of the proposed models in timed transfer coordination. Copyright © 2017 John Wiley & Sons, Ltd.
Original languageEnglish
Pages (from-to)1972-1989
Number of pages18
JournalJournal of Advanced Transportation
Volume50
Issue number8
DOIs
Publication statusPublished - 1 Dec 2016
Externally publishedYes

Keywords

  • control
  • public transport
  • transfer coordination
  • Transfer demand prediction

ASJC Scopus subject areas

  • Automotive Engineering
  • Economics and Econometrics
  • Mechanical Engineering
  • Computer Science Applications
  • Strategy and Management

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