In response to pressing climate issues, Europe is transitioning towards more sustainable transportation. Despite the potential environmental benefits, train travel often loses out to other modes of transportation in long-distance journeys (300+ km). Based on previous research, transfers seem to have a great impact on the attractiveness of train journeys. This study investigates the effects of different transfer attributes on travel choice behaviour in long-distance leisure trips. Through a combination of a literature review and focus groups, key attributes influencing travellers' itinerary choices were identified and incorporated in a stated choice experiment. The experiment, involving 431 respondents, used a Latent Class Choice Model (LCCM) to analyze preferences and willingness to pay for improvements in transfer attributes. The study finds that travel cost and travel time are of the most importance. The number of transfers and transfer time are less critical but still impactful. The service level has a small impact. When the transfer occurs in the journey is insignificant. Four distinct classes of travellers were identified: Time-Valuing Eco-Advocates (44\%), Cost-Sensitive Train Travellers (25\%), Train Dislikers (18\%), and Transfer-Averse Train Sceptics (13\%). The results indicate that reducing travel costs and time should be prioritized over improving transfers to maximize the attractiveness of train travel. However, optimizing transfer time and minimizing the number of transfers will still enhance the appeal for specific traveller classes. By analysing the results, it was found that although direct train services are generally preferred, well-designed transfer options can improve market potential. This does however require significant improvements in the European railway network design and regulations.

The integration of air and rail travel has been increasingly adopted by major European airlines such as Air France-KLM and Lufthansa, as part of their efforts to reduce short-haul flights within Europe. This in order to improve local air quality, reduce greenhouse gas emissions, and contribute to the European Commission's goal of achieving Net Zero emissions by 2050. While much of the existing literature has focused on the substitution of short-haul flights with high-speed rail for direct origin-destination travel, this study explores the integration of air and rail transport in multi-legged journeys. Specifically, it examines the incorporation of high-speed rail as spokes in the hub-and-spoke model used by major airlines.

This study aims to quantify the preferences of potential air/rail travellers in order to provide airlines, airports, and other stakeholders with insights into the key features such as service, comfort and operational factors of an integrated air/rail service. A stated preference survey, distributed among the Dutch Railways (NS) panel, was used to collect data, with a total of 541 respondents. The data is analysed using linear regression analyses and a multinomial logit model to estimate coefficients for the included parameters. Additionally, a latent class choice model was used to capture heterogeneity among the respondents in order to identify several consumer segments.

This study found that integrated ticketing was the most attractive service attribute, while priority lanes provided the highest comfort. Travel cost emerged as the most crucial determinant for choosing air/rail over air/air journeys, followed closely by the spend at the airport and train station in an air/rail journey. The latent class choice model revealed that younger, less experienced travellers were most likely to switch from air/air to air/rail, particularly in scenarios involving high levels of service and comfort integration.

This latent class choice model identified three customer groups: waiting time disfavourites (young, less experienced travellers), plane lovers (middle-aged, experienced travellers), and air/rail service admirers (mostly elderly, retired). Waiting time disfavourites, who prioritize minimizing waiting time at airports and stations, choose air/rail in 53.0% of cases. Plane lovers strongly prefer air/air, with 85.1% favouring it. Air/rail service admirers, valuing service highly, choose air/rail in 97.9% of cases.

According to a real-life scenario analysis about the introduction of an air/rail terminal at Frankfurt Airport, the current offered services and comfort features increases the share of air/rail from 31.4% (102 passengers) to 45.7% (148 passengers), which equals a substitution rate of 14.3%. With further integration, the air/rail share could be increased to 76.4% (249 passengers) among the first group of young, less experienced, travellers. However, the impact on plane lovers is minimal, with a maximum substitution rate of 19.7%. The third group already favours air/rail over air/air, so a maximum substitution rate of 2.7% can be achieved. However, overall, a maximum air/rail share of 67.7% can be reached, equal to 173 additional passengers choosing for air/rail.

This study explores the potential role of e-scooters in supporting “first-mile” travel to train stations in the Netherlands, a critical stage in daily commuting for many Dutch travellers. In a nation where bicycles are a primary mode of transport—especially for trips under 5 kilometres—the introduction of e-scooters offers an alternative with similar benefits: environmental friendliness, cost-effectiveness, and ease of manoeuvrability. With their compact size and accessibility through sharing services, e-scooters can complement the existing bicycle culture, promising an appealing option for urban mobility.

The research focused on examining the role of e-scooters in “first-mile” travel through a stated preference choice experiment, given that e-scooters were newly legalised. A sample of 156 participants responded to six hypothetical travel scenarios, where they chose between familiar modes like walking, cycling, e-bikes, and e-scooters based on different factors such as carry-on ticket costs, parking times, and travel times. These scenarios were designed to reflect typical Dutch commuting choices while testing the appeal of e-scooters as a new transport option.

Analysis of the data using a Multinomial Logit (MNL) model yielded several insights into travel behaviour. There was a clear baseline preference for familiar modes, with participants showing a higher likelihood of choosing options like cycling or walking. Travel cost and time emerged as significant decision-making factors, with higher costs and longer times deterring mode choice. Notably, gender differences surfaced in this context, with males displaying greater tolerance for longer bike trips than females, indicating variations in time-cost sensitivities across demographics.

Experience with transport modes also influenced choices; prior e-scooter use was positively correlated with selecting this option again, suggesting that familiarity can increase comfort and confidence in choosing new modes. Established travel habits showed a strong impact on choice consistency, with individuals who typically walked or cycled to stations likely to maintain these habits, reinforcing the role of routine in travel preferences.

To illustrate the findings, a simulation modelled two scenarios. In the “Extreme Low” scenario, where e-scooter costs were low and parking time was minimal, walking was favoured for short distances (under 0.5 km), while cycling became dominant as distance increased. In contrast, the “Extreme High” scenario, with no fees and longer parking times, significantly boosted e-scooter attractiveness, particularly beyond 1.5 km, where it surpassed both walking and cycling. This outcome underscored the sensitivity of user preferences to economic factors, with e-scooters emerging as a highly competitive option when cost barriers were removed.

Overall, this study highlights the substantial potential for e-scooters to influence first-mile travel choices, particularly when costs are favourable and convenience is enhanced. By offering a viable alternative for medium-distance trips, e-scooters could reshape first-mile mobility in the Netherlands, complementing the well-established cycling culture and contributing to sustainable urban transport.

This research aims to understand the influencing attributes of passengers and station layout elements on transfer walking times for metro transfers. Little research has been performed to include passenger-related attributes to model transfer walking time besides station layout elements. Through a literature review, the effect of gender, luggage size, group size and level of crowding are potential attributes. Furthermore, the vertical transport mode choice, including the lift, the waiting condition to board a vertical transport mode and the alighting location, are also part of the influential attributes besides the transfer length. The walking time and passenger characteristics have been collected through a covert observation. In the data analysis, the effect of group size, vertical transport mode choice, waiting condition to board and the alighting location significantly impact the transfer walking time and the walking time on a transfer segment level. These attributes have been captured in walking time and passing speed models for various transfer segment types. The walking time models can predict a lower, mean and upper bound of the walking time for each combination of attributes. The case study for the walking time collection was metro station Beurs, Rotterdam.

Short-haul flights, known for their high carbon intensity relative to distance, are increasingly challenged by high-speed rail (HSR), a viable and environmentally friendly alternative. This study develops a model adapting the “Transit Network Design and Frequency Setting Problem” to high-speed rail, focusing on optimizing existing networks rather than designing new ones. Two sequential algorithms are developed and integrated in the model, which initially generate the optimal paths in the network, and subsequently, set the appropriate frequencies to the existing and new lines. The model is applied to two scenarios within the European rail network, to assess the impact of network modifications on demand distribution, operational costs, and infrastructure development. The findings reveal that the impact of network modifications varies depending on the size and development level of the area. In smaller, well-developed networks, modifications mainly involve adjusting frequencies of existing services, while larger areas with diverse infrastructure levels necessitate new lines and modified configurations. The model offers varying implementation options, balancing capacity utilization and cost minimization, aiding stakeholders in making informed decisions. The potential of utilizing existing infrastructure for sustainable mobility is highlighted, suggesting that future endeavors should include diverse case studies and incorporate user and social cost perspectives, along with timetabling and operational factors for a more comprehensive evaluation

Following the European Green Deal, transport- related emissions must be reduced by 90% in 2050. While aviation contributes to a significant share of these emissions, the substitution of flights for rail travel is often considered to achieve a reduction in emissions of greenhouse gasses. Mostly, travelers consider this option when the full trip can be substituted directly. However, possibilities also lie in intermodal travel, where specific journey parts are substituted. To promote this way of travel, the two modes should have a strong level of service, and there should be a significant level of integration between the two modes.
In this thesis, a method is presented to assess the position of airports’ in a European intermodal network. This tool helps identify airports with the potential to facilitate intermodal travel in Europe. The service levels in both the air and the rail network, the physical integration between the modes, and the geographical location of airports are considered in different variables to assess the network. A Principle Component Analysis identifies the shared information between the different variables. The Principle Components are then clustered using an Agglomerative Hierarchical Clustering. With this clustering, airports are grouped based on their characteristics of intermodal factors, and different roles in an intermodal network can be identified. Comparing the descriptive statistics of each cluster helps assign qualitative labels to the cluster to classify the airports’ roles. After creating the benchmark with data from the current network situation, scenarios are constructed to assess the effects of implementing different policies regarding intermodality. Extending rail services and/or reducing short-haul flights are policies formed into scenarios in which the underlying data is modified. The change of clustering and classifications caused by the data modification helps identify potentially interesting airports in the network.
The results show that 20 to 30 of the 113 considered airports show a substantial role in intermodality. Also, the findings identify airports that change their position due to the scenario implementations and offer the potential for a significant role in an intermodal network. Finally, comparing the classifications in the different scenarios shows that the constructed scenarios can enable up to 14.3% extra passengers to travel intermodal.

High-speed rail (HSR) is frequently seen as a promising alternative for long-distance travel by air and road, given its environmental advantages whilst offering a competitive level of service. However, due to a lack of knowledge on the design of HSR specific line configurations and the prioritisation of national and railway company interests, no real European HSR network has been realised yet. Together, these lead to a sub-optimal performance from a user, operator and societal perspective. This research is the first attempt to apply the more frequently used ‘Transit Network Design and Frequency Setting Problem’ (TNDFSP) in an HSR setting, which searches the ideal set of lines and associated frequencies in a given network. To do so, this study developed a novel HSR generic model and solution algorithm, which were then parameterised for the European case. By benchmarking the current situation; analysing the relative importance of vehicle, passenger path and line design variables; evaluating pricing and governance strategies; and finally proposing improved settings; it was possible to assess the impacts of improved design. The experiments showed that benefits for all stakeholders could be simultaneously enhanced when implementing a centralised governance and internalisation of external costs. This allowed the HSR market share to evolve from 14.7% to 29.9%, whilst also improving the societal cost-benefit ratio by 20.0%. The governmental investment which is required to fill the gap from the most economical to the most extensive solution equals AC 2.2 billion per year, but also provides a positive rate of return of 1.8 for the combined user and societal benefits. Additionally, the model demonstrated the necessity of spilling unprofitable passengers and the importance of improved cooperation. These followed from the strong network integration with overlapping and border crossing lines of substantial lengths, the contradiction between national and international interests and the high number of critical infrastructural elements. All in all, this study demonstrated the possibility of using the TNDFSP in an HSR setting, which opens ways for further understanding of HSR network design. For this specific research, it allowed the identification of substantial opportunities for mobility and sustainability. These can be reached by improved design choices, internalisation of external costs and by relaxation of the desires for a competitive railway market and national sovereignty; all newly underpinned arguments for the discussion on how to design a successful (European) HSR system. Future research could greatly contribute by incorporating the construction of infrastructure, including timetabling or operational aspects, assessing different case studies in size and geography or introducing new technologies.