A strategy-based recursive path choice model for public transit smart card data

Neema Nassir, Mark Hickman and Zhen-Liang Ma

Transportation Research Part B: Methodological, 2019, vol. 126, issue C, 528-548

Abstract: A recursive logit model is proposed for path choice modeling with transit smart card data in higher-frequency bus and rail services. In such circumstances, it is commonly assumed that passengers may arrive randomly to a stop and may behave according to a “strategy”; such a strategy is associated with a so-called “attractive” set of routes: a passenger selects a set of routes departing from the stop, and will board the next vehicle to depart from among that set of routes. We extend the conventional notion of attractive sets by introducing a measure of “attractiveness” that allows for randomness in the choice of attractive routes.

Keywords: Public transit smart card data; Public transit path choice; Optimal strategy transit assignment; Recursive path choice model (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (10)

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DOI: 10.1016/j.trb.2018.01.002

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