Railway station choice modelling: a review of methods and evidence
mode - rail, infrastructure - station, ridership - demand, ridership - forecasting, ridership - behaviour, ridership - growth, planning - methods
Railway station choice, passenger demand forecasting, rail access mode, train user behaviour, discrete choice models
Since the first railway station choice studies of the 1970s, a substantial body of research on the topic has been completed, primarily in North America, the U.K. and the Netherlands. With many countries seeing sustained growth in rail passenger numbers, which is forecast to continue, station choice models have an important role to play in assessing proposals for new stations or service changes. This paper reviews the modelling approaches adopted, the factors found to influence station choice and the application of models to real-world demand forecasting scenarios. A consensus has formed around using the closed-form multinomial logit and nested logit models, with limited use of more advanced simulation-based models, and the direction effects of a range of factors have been consistently reported. However, there are questions over the validity of applying non-spatial discrete choice models to a context where spatial correlation will be present, in particular with regard to the models’ ability to adequately represent the abstraction behaviours resulting from competition between stations. Furthermore, there has been limited progress towards developing a methodology to integrate a station choice element into the aggregate models typically used to forecast passenger demand for new stations.
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Young, M., & Blainey, S. (2018). Railway station choice modelling: a review of methods and evidence. Transport Reviews, Vol. 38, pp. 232-251.