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.

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.

Multimodal hubs connect different modes, allowing people to switch from one mode to another and seamlessly access/egress to/from their origin/destinations. However, there are limited methods to estimate the impact of future measures on the accessibility of multimodal hubs. These future measures could be wide reaching, among others, introduction of different schemes in the planning of the hub or introduction of new modes at multimodal hubs. This study provides interdisciplinary cross-cutting method including transport and urbanism literatures, by using Space Syntax method. This method allows the transport planners to analyse and compare the current situation and the proposed development plan. In this research, we show how changes made in urban spatial configuration can impact the accessibility of intermodal hubs. To learn about the impacts of the spatial configuration of a city on station design, we performed a case study at Delft Campus train station in the Netherlands, which is under construction to become a multimodal hub. Firstly, we analyse the current situation and then the proposed development plan in terms of, integration, choice, accessibility and intelligibility, using segment analyses. Furthermore, the immediate surrounding areas of the station have been analysed by Visual Graphic Analysis to find visual accessibility within the hub. Although the municipality proposed plans claim that the station’s accessibility would be enhanced, our method indicate otherwise and the proposed changes are not highly effective in increasing accessibility. Finally, some design recommendations for multimodal hubs are proposed. This study is a prerequisite for designing the multimodal hubs considering emerging modes.

Emerging access/egress transport modes to and from railway stations may play a vital role in the future performance and usage of public transport. To learn about these modes, their acceptability, and attractiveness, we performed a case study at Delft Campus train station in the Netherlands, using a stated preference experiment. We investigated travellers’ preferences towards shared bicycles, shared e-steps, shared e-scooters, automated vehicles (individuals and shuttles), and the importance of time, costs, and availability of these modes to access or egress this small-sized hub. Furthermore, we studied the impacts of two contextual situations: weather conditions and carrying luggage, affecting mode choice. The results indicate that travel costs have much higher importance than travel time for accessing or egressing from a small hub, and Autonomous Vehicles (AVs) usage is positively valued as first/last mile transport modes compared to other alternatives. Increasing 10% time and cost of all modes indicate that the demand for individual and collective AVs falls sharply, whereas the change in demands of shared bikes is negligible. A significant impact of context effect variables in the utility of travellers was also observed when these variables interacted with the leading travel attributes. The potential market share of the modes indicates that shared bike usage will continue to be strong, and automated vehicles will find their position at future stations. These findings could provide critical criteria for designing future small/medium multimodal hubs.