Public transport path choice estimation based on trip data from dedicated smartphone app survey

Abstract

Having access to realistic and empirically grounded passenger valuations of public transport trip components facilitate the undertaking of necessary trade-offs during planning of transport networks. Discrete choice estimation of path choice preferences is a practical way to obtain such preferences. This paper proposes a new take on the empirical foundation of path choice estimation based on revealed choices by introducing trip data for full activity-based ‘door-to-door’ public transport trips collected from a dedicated survey application for smartphones. Choice probabilities were modelled based on an explicitly generated choice set, where the public transport trip parts were generated using a branch-and-bound approach. Results in terms of estimated preferences are comparable to those based on conventional surveying methods and suggest significant premiums for paths involving public transport stops with an elevated level of passenger service as well as differences in preferences across population groups.