The transportation landscape is witnessing profound changes due to technological advancements, necessitating proactive policy responses to harness innovation and avert urban mobility disruption. The sharing economy has already transformed ridesharing, bicycle-sharing, and electric scooters, with shared autonomous vehicles (SAVs) poised to reshape car ownership. This study pursues two objectives: firstly, to establish a market segmentation for shared ride services and secondly, to evaluate the environmental impact of ridesharing in different contexts. To mitigate potential biases linked to stated preference data, we analysed the navette service, utilized by a research institute in Europe, closely resembling future SAVs. The market segmentation relied on hierarchical cluster analysis using employee survey responses, while the environmental analysis was grounded in the 2019 navette service data. Our analysis revealed four unique employee clusters: Cluster 1, emphasizing active transportation and environmental awareness; Cluster 2, showing openness towards SAVs given reliable alternatives are available; Cluster 3, the largest segment, highlighting a demand for policy support and superior service quality; and Cluster 4, which places a premium on time, suggesting a potential need for strategies to make the service more efficient and, consequently, discourage private car use. These findings highlight a general willingness to adopt shared transport modes, signalling a promising transition to shared vehicle ownership with significant environmental benefits achievable through service design and policy measures.

Advancement in the fields of electrification, automation, and digitalisation and emerging social trends are fuelling the transformation of road transport resulting in the introduction of various innovative mobility solutions. Yet the reaction of people to many of the new solutions is still vastly unknown. This creates an unprecedented quandary for transport planners who are requested to design future transport systems and create the related investment plans without fully validated models to base the assessment upon. As some evidence on citizens’ behaviour concerning new mobility solutions starts to be progressively made available, first attempts to update the existing models begin to emerge. Nevertheless, a lot more is needed as some of the transpiring mobility solutions have not yet reached the market, making the corresponding behaviour changes imponderable. In this context, the main purpose of this paper is to provide a review on how travel behaviour changes linked to the deployment of new mobility solutions have been considered in travel demand models. The new mobility solutions studied include carsharing, dynamic ridesharing, micromobility sharing services, and personal and shared autonomous vehicles. An overview and comparison of relevant studies implementing activity or trip-based demand models and other methodologies are presented. The analysis shows that the results of the different studies heavily depend on the extent to which behavioural changes are considered. The results of the review thus point to the need for holistic demand models that carefully mimic the urban reality with everything it has to offer and account for the importance of individual traits in the decision-making processes. Such models need an in-depth understanding of the microscopic mechanisms leading to the travel behaviour shifts linked to the most innovative mobility solutions. To achieve this level of detail, mobility living labs and their real-life experiments and experience with citizens, which are flourishing in Europe, are suggested to play a crucial role in the years to come.

Mobility needs, expectations, and concerns vary across age groups and are closely linked to users’ views on the future of the road transport system. Automated vehicles are expected to have a significant impact on the future of the road transport system, and pilot deployments are increasingly being tested in Europe and beyond, which is also thanks to the evolving regulatory landscape. As a result, several studies have started to analyse citizens’ attitudes towards this technology. However, very few studies have focused on teenagers’ views on automated vehicles, although today’s children and teenagers could be among the first users of such vehicles. Studying teenagers and the way they envisage automated vehicles in the future is of particular significance in defining transport planning strategies and supporting upcoming policy orientations. To cover this gap, the present study aims to explore teenagers’ views about automated vehicles and whether and how they could fit into their future transport setting. A series of on-line and face-to-face focus groups, a demonstration of an automated vehicle prototype, supporting engagement activities, and a post-pre survey were used to collect their views on the topic. The results show that even though the teenagers acknowledged the potential advantages, they also expressed concerns in relation to the interactions with other road users, to automated driving systems’ reliability, to safety, and to data privacy. In particular, these safety concerns revealed an unwillingness on the part of the teenagers to be among the first users of automated vehicles.

This paper investigates the spatiotemporal patterns and accessibility implications of shared e-scooter use in Tel Aviv, drawing on a complete year (2024) of trip-level data from all licensed providers. Shared micromobility services are often promoted as tools for reducing car dependency and improving urban accessibility, yet their actual usage patterns and equity outcomes remain underexplored, especially outside North America and Western Europe. This study aims to address this gap by integrating over 9 million reconstructed scooter trips with public transport accessibility data, local weather records, and institutional calendar effects. Multivariate regression was applied to quantify temporal and environmental determinants of demand, seasonal-trend decomposition to reveal cyclical usage patterns, and spatial analysis to assess whether scooters extend or reinforce existing mobility hierarchies. Findings indicate that scooter use in Tel Aviv is highly structured, peaking during afternoon hours, dropping during holidays and rain, and reflecting the weekly rhythms of the workweek in Tel Aviv. However, spatial patterns show a strong concentration of usage within already well-connected central areas, with limited activity in low-accessibility zones. These results suggest that shared e-scooters are not currently fulfilling their potential as first- or last-mile connectors; instead, they primarily serve as short-range, intra-core alternatives to walking.