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Examining impacts of time-based pricing strategies in public transportation: A study of Singapore

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  • Adnan, Muhammad
  • Nahmias Biran, Bat-hen
  • Baburajan, Vishnu
  • Basak, Kakali
  • Ben-Akiva, Moshe

Abstract

Peak and off-peak pricing strategies are an important policy tool used to spread peak demand in public transportation systems. This study uses an agent-based simulator (SimMobility Mid-term) to examine the impact of pricing (off-peak fare discounts) strategies used in Singapore. The aim of the paper is to demonstrate the capabilities of the simulator, and types of detailed performance indicators it can provide, in order to examine the effects of complex public transport pricing policies. Behavioral models within the simulator are calibrated with relevant datasets such as household travel survey, smart card, GPS probe data from taxis and traffic counts for the Singapore network. Nine (09) time-based pricing strategies are examined that consist of a combination of free pre-peak travel on Mass Rapid Transit (MRT) and an off-peak discount for integrated transit (public buses, MRT and Light Rail Transit (LRT)).

Suggested Citation

  • Adnan, Muhammad & Nahmias Biran, Bat-hen & Baburajan, Vishnu & Basak, Kakali & Ben-Akiva, Moshe, 2020. "Examining impacts of time-based pricing strategies in public transportation: A study of Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 127-141.
    • Handle: RePEc:eee:transa:v:140:y:2020:i:c:p:127-141
    DOI: 10.1016/j.tra.2020.08.010
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    Cited by:

    1. Yaping Li & Zheng Liu & Shiqing Zhang, 2023. "Joint Impacts of Pricing Strategies and Persuasive Information on Habitual Automobile Commuters’ Travel Mode Shift Responses," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    2. Yunji Cho & Jaein Song & Minhee Kang & Keeyeon Hwang, 2021. "An Application of a Deep Q-Network Based Dynamic Fare Bidding System to Improve the Use of Taxi Services during Off-Peak Hours in Seoul," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    3. Li, Mengya & Kwan, Mei-Po & Hu, Wenyan & Li, Rui & Wang, Jun, 2023. "Examining the effects of station-level factors on metro ridership using multiscale geographically weighted regression," Journal of Transport Geography, Elsevier, vol. 113(C).
    4. Ayesha Khan & Haroon Gulzar & Hafsa Shoaib & Hamza Saleem & Asra Hafeez, 2022. "Urban Transport: A Proposal of Light Rail Transit (LRT) System in Lahore," International Journal of World Policy and Development Studies, Academic Research Publishing Group, vol. 8(1), pages 1-20, 06-2022.

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