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Relevance of detailed transfer attributes in large-scale multimodal route choice models for metropolitan public transport passengers

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  • Nielsen, Otto Anker
  • Eltved, Morten
  • Anderson, Marie Karen
  • Prato, Carlo Giacomo

Abstract

Given the aim of increasing public transport patronage, it is important to understand how passengers perceive different trip characteristics. Most of the existing studies about public transport demand and route choice assigned a higher value of time to transfers than in-vehicle time and used a general transfer penalty to capture an average increase in the travel disutility because of the amount of transfers. However, it is likely that there are nuances to the transfer behaviour depending on specific transfer conditions that existing models do not capture and hence it is difficult to evaluate measures aimed at improving transfers to make public transport more attractive.

Suggested Citation

  • Nielsen, Otto Anker & Eltved, Morten & Anderson, Marie Karen & Prato, Carlo Giacomo, 2021. "Relevance of detailed transfer attributes in large-scale multimodal route choice models for metropolitan public transport passengers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 76-92.
    • Handle: RePEc:eee:transa:v:147:y:2021:i:c:p:76-92
    DOI: 10.1016/j.tra.2021.02.010
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    Cited by:

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    2. Chen, Enhui & Stathopoulos, Amanda & Nie, Yu (Marco), 2022. "Transfer station choice in a multimodal transit system: An empirical study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 337-355.
    3. Danica Babić & Milica Kalić & Milan Janić & Slavica Dožić & Katarina Kukić, 2022. "Integrated Door-to-Door Transport Services for Air Passengers: From Intermodality to Multimodality," Sustainability, MDPI, vol. 14(11), pages 1-20, May.
    4. Chen, Tiantian & Fu, Xiaowen & Hensher, David A. & Li, Zhi-Chun & Sze, N.N., 2024. "Effects of proactive and reactive health control measures on public transport preferences of passengers – A stated preference study during the COVID-19 pandemic," Transport Policy, Elsevier, vol. 146(C), pages 175-192.
    5. Yan Yang & Qiang Zhou, 2023. "Modeling and Simulation of Crude Oil Sea–River Transshipment System in China’s Yangtze River Basin," Energies, MDPI, vol. 16(6), pages 1-16, March.
    6. Ingvardson, Jesper Bláfoss & Thorhauge, Mikkel & Nielsen, Otto Anker & Eltved, Morten, 2024. "Public transport route choice modelling: Reducing estimation bias when using smart card data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    7. Marra, Alessio D. & Sun, Linghang & Corman, Francesco, 2022. "The impact of COVID-19 pandemic on public transport usage and route choice: Evidences from a long-term tracking study in urban area," Transport Policy, Elsevier, vol. 116(C), pages 258-268.

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