Optimal operation for rail transit systems under advanced information

Jia Ming Cao, Wei Hua Lin

Research output: Contribution to journalArticle

Abstract

Rail transit is normally operated on a fixed train schedule (timetable), designed based on data from typical days. In practice, however, unexpected fluctuations in passenger flow and/or in facilities may occur, making the original schedule unrealizable or non-optimal. This calls for a real-time Decision Support System (DSS) which can assist transit operators to effectively adjust the train schedule on the real-time basis when the operation environment changes markedly. Such a system can be made possible by the latest developments in intelligent transportation technologies. As the theoretical part of an operational DSS, this paper presents an optimization model, based on information available from the advanced surveillance technologies (e.g. the current situation of facilities, the short-term prediction of passenger flow, etc.), to optimize the real-time train schedule for a specific time horizon. An approximation algorithm for this model is proposed and some computational results are reported.

Original languageEnglish (US)
Pages (from-to)109-123
Number of pages15
JournalTransportation Planning and Technology
Volume22
Issue number2
StatePublished - 1998
Externally publishedYes

Fingerprint

Decision support systems
train
Rails
decision support system
Approximation algorithms
transportation technology
optimization model
available information
fluctuation
surveillance
prediction
time

Keywords

  • Advanced transportation information
  • Intelligent transportation system
  • Nonlinear programming
  • Optimization
  • Rail transit
  • Scheduling

ASJC Scopus subject areas

  • Transportation

Cite this

Optimal operation for rail transit systems under advanced information. / Cao, Jia Ming; Lin, Wei Hua.

In: Transportation Planning and Technology, Vol. 22, No. 2, 1998, p. 109-123.

Research output: Contribution to journalArticle

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