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

Lookup NU author(s): Vishnu Baburajan


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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)).Changes in public transport ridership, mode shares, operator's revenue and denied boarding are used as indicators to examine the impacts of pricing strategies. The effects of these policies are also examined on segments of the population in terms of income level, person type and gender. Results indicate that off-peak discounts spread PM peak demand and attract individuals to public transportation. However, the availability of fare discounts in all off-peak periods results in adverse impacts during the AM peak because many commuters shift the return leg rather than the initial leg of their journey. The study concludes with suggestions on how to explore more effective pricing strategies, i.e. providing fare discounts only during off-peak periods that surround AM peak.

Publication metadata

Author(s): Adnan M, Biran BN, Baburajan V, Basak K, Ben-Akiva M

Publication type: Article

Publication status: Published

Journal: Transportation Research Part A: Policy and Practice

Year: 2020

Volume: 140

Pages: 127-141

Print publication date: 01/10/2020

Online publication date: 29/08/2020

Acceptance date: 17/08/2020

ISSN (print): 0965-8564

ISSN (electronic): 1879-2375

Publisher: Elsevier Ltd


DOI: 10.1016/j.tra.2020.08.010


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