Public transportation ridership has grown significantly over the past decades and this growth is expected to continue into the future. Crowding at train and metro stations is therefore experienced more frequently, resulting in safety issues, decreased comfort levels, increased total travel times and modality shifts. On the long term large infrastructural changes can be considered to increase the capacity but for the short term more flexible and cheaper crowd management measures can be applied. Little scientific research has been dedicated to study
the effects of crowd management measures or when to apply them. The aim of this thesis is to design a method to systematically select and assess effective crowd management measures to increase the safety and throughput in train and metro stations.

A list of 29 crowd management measures, their field of application, possible effect, characteristics and indication of costs is composed based on literature, experts or previous applications. A framework is developed to provide a means to select crowd management measures to apply at a particular train or metro station. This framework includes an applicability check, problem analysis, measure selection, assessment method and evaluation. The framework is applied on a fictional metro station, with many similarities to the Amsterdam metro. The measures that are selected using the framework have a positive effect on the safety and throughput, as indicated by the level of service and travel times. The framework is believed to help guide towards suitable measures in the multi-disciplinary decision making process.