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Modeling the effect of real-time crowding information (RTCI) on passenger distribution in trains
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0001-8908-0307
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-4106-3126
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning. Delft Univ Technol, Dept Transport & Planning, Delft, Netherlands..ORCID iD: 0000-0002-4506-0459
2022 (English)In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, E-ISSN 1879-2375, Vol. 166, p. 354-368Article in journal (Refereed) Published
Abstract [en]

Overcrowding has become a big challenge for public transport systems, affecting passengers' travel experience. At the same time, service supply is often underutilized due to large variations in crowding across services, vehicle trips on the same service and different compartments of the same vehicle. Real-time operational measures, such as information provision, can potentially reduce on-board crowding unevenness and its negative effects. In this study, we extend a dynamic public transport simulation model to provide passengers with predictive real-time crowding information (RTCI) concerning individual train cars. Passengers utilize this information when choosing a specific train car to board. It is demonstrated through a case study for the Stockholm metro network area that in the presence of car-specific crowding information, passengers alter their car boarding choices to avoid on-board crowding, leading to a more even passenger distribution inside trains. We find that passengers' travel experience improves with the provisioning of RTCI, which is a result of the lower on-board crowding unevenness. Moreover, this improvement increases with increased demand levels but only up to a certain point beyond which passengers do not gain from switching train cars.

Place, publisher, year, edition, pages
Elsevier BV , 2022. Vol. 166, p. 354-368
Keywords [en]
Public transport, Real-time crowding information, Passenger distribution
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-322306DOI: 10.1016/j.tra.2022.10.011ISI: 000886627200005Scopus ID: 2-s2.0-85141912721OAI: oai:DiVA.org:kth-322306DiVA, id: diva2:1718212
Note

QC 20221212

Available from: 2022-12-12 Created: 2022-12-12 Last updated: 2022-12-15Bibliographically approved

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Peftitsi, SoumelaJenelius, ErikCats, Oded

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