Route and activity location choice behaviour of departing passengers in train stations

In the Netherlands, rail passenger transport has grown considerably during the last decades. Although growth has been seen nationwide, it has concentrated at a few of the largest stations in the country (e.g. Amsterdam Central and Utrecht Central station). As a result, these stations are being redeveloped. Furthermore, this growth trend is expected to continue into the future. This also means that (temporary) overcrowding can arise at these stations. These trends have triggered a need for more insights into the behaviour of passengers inside train stations. With these insights, existing stations can be better managed, and redevelopments can be better designed and planned.

This paper presents quantitative research results regarding the factors that influence route and activity location choice behaviour of departing passengers at train stations. For this study, SMART Station data has been used. This automated data collection system is based on Bluetooth, Wi-Fi and infrared sensors. It generates revealed preference data on passenger routes and activities in train stations. Estimated discrete choice models based on these data show which factors influence the choice of departing passengers for vertical infrastructure facilities (i.e. escalators and stairways; route choice) and the choice of retail outlets in the station building (activity location choice).

The factors significantly influencing route choice behaviour of departing passengers are: travel time, walking distance, train stop location alongside the platform and right side orientation of the vertical infrastructure facility which provides access to the platforms. Travel time and walking distance appeared to be highly correlated. To get a better model fit, only the first has been included in the final model, together with train stop location and orientation. Travel time is the most important factor.

In the activity location choice model, also four factors turned out to be of significant influence: travel time from station entrance to the retail outlet, total distance (from entrance via outlet to the platform), the requirement to make a detour for a shop visit, and right side orientation. Distance is the most important factor in this model.

To the best of our knowledge, before this study there has been no empirical, quantitative evidence of the factors which contribute to route and activity location choices inside a train station. Due to the large amount of revealed preference data which has been collected by Bluetooth/Wi-Fi-sensors, this study can be considered as first of its kind in the field of train passenger route and activity choice behaviour in train stations.