Modelling Random Taste Variations on Level Changes in Passenger Route Choice in a Public Transport Station

In large stations of public transportation high crowd densities can lead to potential safety risks and to unnecessary delays. To assess the actual capacity of potential bottlenecks a deeper understanding on the route choice of pedestrians is of great importance. This paper investigates the factors that influence the route choice of pedestrians when facing a stair/escalator combination in a major Austrian train station. We employ random utility models on data sets of revealed and stated preferences. In particular we investigate the potential for heterogeneities in taste by employing mixed logit models. The results show that, first, crowding is an important factor for route choice, second, that the application of mixed logit models is appropriate and, last, that the use of both revealed and stated preference data adds valuable information.