Statistical Inference of Transit Passenger Boarding Strategies from Farecard Data
Abstract
This research considers how one might deduce the set of attractive routes for public transit passengers, as part of a boarding strategy, from passengers’ daily choices of which path to take. From the set of attractive routes (attractive set), a public transit passenger may be assumed to board the first service that arrives at the origin stop. To determine the attractive set, a statistical inference algorithm was developed and tested using a public transit farecard data set. The proposed algorithm was developed from an exact method that investigates the distribution of repeated boarding transactions in a farecard data set and infers the so-called steady-state strategies over the observation period. The advantage of the proposed method is in identifying and eliminating occasional and tried-but-rejected path alternatives recorded during the study period. The method was tested in a case study using 6 months of farecard transactions of regular passengers for multiple major origin–destination pairs in the transit network of Brisbane, Australia. Some behavioral aspects of passengers’ attractive routes are also reported and discussed.
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