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This paper presents a rail network vulnerability analysis to identify which links within the Dutch rail network are most vulnerable to winter weather. A vulnerability index was developed to measure rail vulnerability during winter weather based on switch-related disruptions, integrating both node and link components into a probabilistic measure of vulnerability. The analysis looked at disruption data for 379 Dutch stations during the years 2007-2017. Links in dense population areas, which operate a high number of switches, are most susceptible to winter disturbances. Particularly, three main railway stations (Utrecht, Amersfoort and Zwolle) are the most critical locations within the network in terms of extreme winter conditions and disruptions. In addition, we developed two scenarios to analyse implications of different railway switch reduction strategies on rail vulnerability. The proposed rail vulnerability index can be a useful tool to define operational strategies to reduce the vulnerability of the Dutch railway network. Decreasing the number of switches at station areas appears to be more effective for reducing railway vulnerability than decreasing the number of switches throughout the entire network. [ABSTRACT FROM AUTHOR]

Typically, mode choice behaviour is studied as a function of observed travel factors. Given the importance of unobservable factors on choice behaviour, this paper deviates from this approach. We analysed cycling as mode choice to access railway stations, incorporating latent variables and psychometric data to capture relatively intangible factors that influence mode choice. Such factors are not observable, but can manifest themselves through adjustable indicators. The database used for this paper contains 12000 observations of journeys carried out in the Rotterdam - The Hague area in the Netherlands, covering thirty-five railway stations. In addition to using a traditional binary logit model, we estimated three hybrid choice models for access mode choice. These hybrid choice models represented observed and unobserved factors simultaneously, including the train users' perception of connectivity, attitude towards station environment and perceived quality of bicycle facilities. The results show that both attitudes and observable travelrelated elements are important in the decision to cycle to the station or not. Variations in these perceptions and attitudes significantly affect the bicycle-train share. At the same time, improvements in unguarded bicycle parking facilities may increase the number of people who cycle to the train station more than improvements in guarded bicycle parking would. Moreover, the availability of the parking facilities is crucial during rush hours. Another conclusion is that transport strategies to encourage bicycle-train use must be implemented by station type, i.e. measures to encourage bicycle access at larger stations. Further research would develop a hybrid choice model for egress, and a stated choice experiment would compare these results. [ABSTRACT FROM AUTHOR]