Modeling the impacts of public transport reliability and travel information on passengers’ waiting-time uncertainty

Oded Cats () and Zafeira Gkioulou
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Oded Cats: Delft University of Technology
Zafeira Gkioulou: KTH Royal Institute of Technology

EURO Journal on Transportation and Logistics, 2017, vol. 6, issue 3, No 3, 247-270

Abstract: Abstract Public transport systems are subject to uncertainties related to traffic dynamic, operations, and passenger demand. Passenger waiting time is thus a random variable subject to day-to-day variations and the interaction between vehicle and passenger stochastic arrival processes. While the provision of real-time information could potentially reduce travel uncertainty, its impacts depend on the underlying service reliability, the performance of the prognosis scheme, and its perceived credibility. This paper presents a modeling framework for analyzing passengers’ learning process and adaptation with respect to waiting-time uncertainty and travel information. The model consists of a within-day network loading procedure and a day-to-day learning process, which are implemented in an agent-based simulation model. Each loop of within-day dynamics assigns travelers to paths by simulating the progress of individual travelers and vehicles as well as the generation and dissemination of travel information. The day-to-day learning model updates the accumulated memory of each traveler and updates consequently the credibility attributed to each information source based on the experienced waiting time. A case study in Stockholm demonstrates model capabilities and emphasizes the importance of behavioral adaptation when evaluating alternative measures which aim to improve service reliability.

Keywords: Public transport; Assignment model; Waiting time; Reliability; Real-time information; Learning (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s13676-014-0070-4

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