In this chapter, light rail will be explained and discussed. Based on literature and research, this chapter describes light rail as a mode of transport and examines what its impacts are. Finally, this chapter explains how light rail could be implemented.

Mobility-as-a-Service, known simply under the acronym of MaaS, can be described as an integration of information, reservation and payment for a wide variety of transport modes into a single service. In that respect, MaaS is not a transport mode in a traditional sense. Through technological innovation, it became a viable solution in the 2010s, capturing the attention and interest of entrepreneurs, policymakers and researchers alike. Through research and trials, we now have a much clearer understanding of what MaaS is, what it can do for us and what are potential difficulties that need to be addressed or pitfalls to watch out for. Results on what would encourage travellers to use MaaS are often inconsistent, largely dependent on the specific national/regional context or the design of the service itself. Perhaps the most conclusive outcome is that effective and efficient public transport is essential for any MaaS scheme. It can and should be seen as a baseline, to which other (shared) services can then be coupled. Given the strong impact of context and design, it is not surprising that the implications are highly variable, with multiple studies stating what may or may not occur under specific circumstances. The novelty and lack of real applications beyond trials also means governance issues tend to be hypothetical, with papers generally echoing the need for collaboration among stakeholders and finding a balance between overregulation and laissez-faire policymaking. This uncertainty on various fronts also makes the future evolution of MaaS difficult to predict. Closer cooperation with public transport is a viable path forward, especially given the necessity of its inclusion in any MaaS scheme. Another approach may be integration of MaaS with non-mobility offerings.

The escalating demand for urban mobility has significantly contributed to increased CO₂ emissions, necessitating a shift towards sustainable, low-carbon transportation solutions. Emerging modes and concepts such as micro-mobility, shared mobility, electric mobility and mobility hubs offer promising pathways to reduce vehicle CO₂ emissions. This review explores the role of these modes in emission reduction, with particular attention to the integrative function of mobility hubs. This review synthesized current knowledge on the role of emerging transport modes in reducing urban CO₂ emissions. Our analysis through the Life-Cycle Assessment framework and Dynamic Mitigation Model demonstrates that while these modes can lower emissions by facilitating a shift away from private cars, their success is not a guaranteed outcome. Instead, their environmental benefit depends on managing the balance between modal substitution, operational logistics, and vehicle life-cycles. Mobility hubs are a pivotal strategy for mitigating the life cycle emissions associated with shared transport modes by enhancing integration and minimizing indirect emissions. Therefore, the review argues that advancing shared mobility from a niche option to a mainstream solution, supported by strategically implemented mobility hubs, is essential for achieving significant climate benefits. Prioritizing the coordinated deployment of emerging modes and hubs can capture their synergistic advantages, minimizing life-cycle CO₂ emissions and advancing the transition toward sustainable urban transport.

Shared micromobility (SMM), including bicycles, e-bikes, scooters, etc., is often cited as a solution to the first and especially the last mile problem of public transport (PT), yet when implemented, they often do not get adopted by a broader travelling public. As behavioural adaption is largely related to peoples’ attitudes and perceptions, we develop a behavioural framework based on the UTAUT2 framework to gain better understanding why individuals may (not) be willing to use SMM. Through an exploratory factor analysis (EFA) and a latent class cluster analysis (LCCA), we study the adoption potential of SMM and assess drivers and barriers as perceived by different user groups. Our findings uncover six user groups; Shared mobility positives, Car-oriented sharing neutrals, Older apprehensive sharers, Young eager adopters, (Shared) Mobility avoiders and Skilled sharing sceptics. The Young eager adopters and Shared mobility positives tend to be the most open to adopting SMM and able to do so. Older apprehensive sharers would like to, but find it difficult or dangerous to use, while Skilled sharing sceptics are capable and confident, but have limited intention of using it. Car-oriented sharing neutrals and (Shared) Mobility avoiders are most negative about SMM, finding it difficult to use and dangerous. Factors relating to technological savviness, ease-of-use, physical safety and societal perception seem to be the strongest adoption predictors. Younger, high-educated males are the group most likely and open to using SMM, while older individuals with lower incomes and a lower level of education tend to be the least likely.

Shared micromobility may enhance accessibility as part of a comprehensive public transport network. A qualitative stakeholder perspective is needed to reflect the practical opportunities and challenges for integrating shared micromobility and public transport. This research synthesizes literature alongside 25 interviews with professionals across North America and Europe to answer: 1) what challenges and opportunities do different integration approaches offer? And 2) what should be prioritized when integrating shared micromobility and public transport? We frame integration efforts in three pillars: 1) institutional, 2) physical, and 3) digital integration. Findings show that integration efforts are effective only when foundational preconditions are met including high-quality public transport, dedicated micromobility infrastructure, supportive land uses, and issue framing. Institutional and physical integration are both necessary to facilitate multimodal travel and create cohesive regional travel networks. Digital tools can support integration but often requires substantial resources, and faces data sharing and privacy, feasibility, and scaling challenges.

Car dominance in urban landscapes poses environmental, health, and congestion challenges. This comprehensive study examines the potential of shared mobility in car-free areas. Specifically, it investigates the mobility behaviour of inner-city older adult residents (50 + ), traditionally heavy car users through a case study of small-medium-sized Dutch cities and a stated preference experiment. This study applies a Latent Class model to analyse the heterogeneity in passengers’ preferences, identifying four distinct groups: Price Sensitive & Private Car Enthusiasts, Time-Conscious Travellers, Pro-Cycling & Conventional travellers, and Micromobility Enthusiasts. The model predicts class membership based on travel behaviour data from the stated choice experiment and examines the role of key factors such as travel cost, travel time, and walking distance in shaping mode choices across five transport options: bike, e-bike, e-scooter, e-Brommobiel, and e-car. The findings reveal that a significant portion of travellers recognise the value of shared mobility options in reducing private car dependency, underscoring the need for targeted interventions to address barriers and enhance accessibility to promote shared mobility adoption. Based on these distinct passenger segments, the study proposes specific policy measures that not only enhance transport planning but also address existing challenges and user concerns in sustainable urban mobility.

Passenger railway demand fluctuates daily, peaking at the start and end of the workday due to commuting to school and work. During the off-peak the volumes drop and most people travel for other purposes, like leisure and social visits, which results in different travel destinations. Despite this, many European Railways use fixed line plans and cyclic timetables that remain constant throughout the day. While this approach makes schedules easy to remember and provides ample off-peak travel options, it is primarily designed for peak-hour demand, making it less efficient for the off-peak. Furthermore, due to the different mix of travel purposes, a schedule based on peak-hour demand is not necessarily optimal for off-peak demand. This paper aims to combine the benefits of a cyclic timetable with the flexibility of an acyclic timetable in order to follow the time-dependent demand more closely. We propose a mixed-integer linear programming model that finds a timetable for a day consisting of several periods which each have its own line plan. The resulting timetable is required to be cyclic within each period and provide a good transition between the periods. The model is successfully tested on a case study with changing stopping patterns using data from the Dutch railway network, for which an optimal timetable is found. In this timetable, the transition between cyclic schedules can be done without cancelling trains or shifting trains from the new cyclic times.

Offering shared mobility options at transit stops can potentially increase the service area of a stop and consequently, possible detours in transit lines can be eliminated to decrease in-vehicle travel times for through-passengers and reduce operational costs. However, current research mostly focusses on shared mobility options and expected behaviour only, whilst not looking at this integrated transit network design problem. Additionally, most focus of current studies is on the integration of shared mobility in urban areas and/or around train stations, leaving a gap on suburban areas and transit lines with lower demand. In order to answer our research question “what the effects are of increased route directness for low-demand transit lines in conjunction with offering shared mobility at transit stops”, we developed a mesoscopic model extension for the aggregated four-step transport model to model changes in travel behaviour as a result of straightened transit lines and the simultaneous integration of shared modes. Discrete choice models are used to accurately model first and last mile preferences of people, based on the access and egress distance, demographics and available (shared) modes. Finally, the probability of passengers cancelling their complete trip as a result of increased first and last mile distances is also explored. This model framework was applied to nine case studies in the Netherlands. The synthesis of the case studies resulted in key factors contributing to a promising redesign of the transit network. The main factor is that through-passengers should significantly outnumber local passengers, by at least 75%-25%. Additionally, the increase in access and egress times should not be significantly larger than in-vehicle time savings of through-passengers. Moreover, it is found that the mode share of micromobility in the first and last mile is approximately 15% across the different cases, whereby the highest usage can be seen for people under the age of 25 and for distances greater than 1 km. Finally, it is concluded that the additional costs of shared mobility are on average only 10% of the savings in operational costs.

Integrating bike-sharing programs with public transport enhances accessibility and car-independent mobility, yet a comprehensive societal cost-benefit analysis of this integration remains scarce. This study addresses this gap by conducting an ex-durante analysis of the OV-fiets program in the Netherlands, a station-based round-trip bike-sharing system designed to improve last-mile connectivity for train commuters. The analysis reveals that in the average (balanced) scenario, the net present value (NPV) of the OV-fiets scheme is positive, with a benefit-cost ratio (BCR) of 1.5. This indicates that the scheme has benefited the Dutch society over the 20-year period (2004–2023). In the pessimistic scenario, the NPV remains slightly positive with a BCR of 1.1. This implies that even under the least favourable conditions, where high costs and low benefits are assumed, the scheme still slightly exceeds the break-even point. Conversely, in the optimistic scenario, the BCR rises significantly to 2.4. Primary benefits include enhanced accessibility, reduced road congestion, and improved health outcomes. This research underscores the considerable societal value of the OV-fiets program in the Netherlands, warranting continued investment in the program and emphasising the need for ongoing bicycle safety measures and infrastructure improvements. However, OV-fiets might be successful in the Netherlands; our analysis also shows that copying it into other contexts is not straightforward. The seamless integration of bikes with trains is crucial, and the operators should be able and willing to accept operational losses.

This literature review examines 58 studies on equity in transit fare policy, addressing developments since the last comprehensive review in 1990. It divides the literature into seven categories: (1) fare equity calculation methods; (2) flat versus distance based fares (3) equity impacts of fare changes; (4) differentiated fares; (5) creating equitable fare policy for people with low incomes; (6) fare capping; and (7) free fare public transport. For each category, the review outlines the key findings and suggests areas for future research. Overall, the current literature shows that fare equity outcomes are highly context-dependent and shaped by system design, demographic patterns, and policy implementation. The literature suggests that direct subsidies to low income people result in better equity outcomes than subsidies to groups that collectively have a lower than average income. Additionally, free fare public transport has received considerable attention even as the literature suggests its benefits may be quite limited. In contrast, the limited attention given to fare capping has suggested that it has the potential to significantly improve equity outcomes with limited cost burdens to transit providers. Future research should focus on methods for identifying low-income users, best practices for implementing new payment structures such as fare capping, and different ways of using fares to increase transit accessibility.

Access/egress travel to train stations poses a significant barrier to increasing the number of train travellers. The last mile is challenging for travellers, given the lack of private modes to reach the destination, strongly limiting the egress range from the station. An often-cited solution is shared micromobility (SMM): bicycles, e-bikes, e-scooters and e-mopeds. Through a stated preference survey, we analyse activity-end mode-choice preferences for SMM, walking and public transport (PT) among the Dutch population. Using a latent class choice model, we uncover three user groups: Multimodal SMM enthusiast (58%), who choose based on the trade-offs between various travel characteristics, while not having strong modal preferences. They are the most open, ready and able to use SMM. SMM hesitant cyclists (16%) have a strong preference for cycling and while they are open to using SMM, they may not feel themselves ready, stating that use of SMM can be difficult and dangerous. SMM-averse PT users (27%) are most likely to use PT and avoid SMM as they find it too difficult and dangerous to use. For policymakers, the high preference to walking over short egress distances reaffirms the need for continued focus on transit-oriented development. For longer distances, policymakers should focus on improving PT service in high-density high-demand areas, as high frequencies and dense PT networks can be justified, while stations in low-demand areas are better served by SMM. Policymakers should also prioritise SMM modes that are cheaper and that travellers are familiar and comfortable with, such as bicycles.