Data-driven estimation of transfer walking time distribution in multimodal public transport systems based on smart card data
Transfers and connections between lines in a public transport network are a major part of the planning of good and reliable timetables. But it is difficult to observe whether the planned connections can be reached with the planned walking time between stops. This research focuses on transfers from busses to trains and utilises data from Rejsekort and automatic vehicle location data to estimate the walking times at these transfers. By applying Bayesian inference for estimation of walking time distributions it is furthermore possible to quantify the uncertainty of a transfers planned by the traffic planners. The method is applicable to all bus to train transfers and is a convenient way to obtain robust walking times, which take into account extra time used for walking due to stairs and waiting at traffic signals.