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Passenger-oriented Railway Traffic Re-scheduling: A Review of Alternative Strategies utilizing Passenger Flow Data
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2017 (English)Conference paper, (Refereed)
Abstract [en]

Developing and operating seamless, attractive and efficient public transport services in a liberalized market requires significant coordination between involved actors, which is both an organizational and technical challenge. During a journey, passengers often transfer between different transport services. A delay of one train or a bus service can potentially cause the passenger to miss the transfer to the subsequent service. If those services are provided by different operators and those are not coordinated and the information about the services are scattered, the passengers will suffer. In order to incorporate the passenger perspective in the re-scheduling of railway traffic and associated public transport services, the passenger flow needs to be assessed and quantified. We therefore perform a survey of previous research studies that propose and apply computational re-scheduling support for railway traffic disturbance management with a passenger-oriented objective. The analysis shows that there are many different ways to represent and quantify the effects of delays on passengers, i.e.“passenger inconvenience”. In the majority of the studies, re-scheduling approaches rely on historic data on aggregated passenger flows, which are independent of how the public transport services are re-scheduled. Few studies incorporate a dynamic passenger flow model that reacts based on how the transport services are re-scheduled. None of the reviewed studies use real-time passenger flow data in the decision-making process. Good estimations of the passenger flows based on historic data are argued to be sufficient since access to large amounts of passenger flow data and accurate prediction models is available today.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Train re-scheduling, Passenger satisfaction, Passenger flow dynamics, Delay management
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:bth-14114OAI: oai:DiVA.org:bth-14114DiVA: diva2:1089297
Conference
7th International Conference on Railway Operations Modelling and Analysis, Lille
Projects
TRANS-FORMFLOAT
Available from: 2017-04-19 Created: 2017-04-19 Last updated: 2017-04-21Bibliographically approved

Open Access in DiVA

fulltext(489 kB)91 downloads
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Josyula, Sai PrashanthTörnquist Krasemann, Johanna
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf