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Walking and cycling, as active modes of transportation, play a vital role in advancing sustainable urban mobility by reducing emissions and improving public health. However, widespread adoption faces challenges such as inadequate infrastructure, safety concerns, socio-cultural barriers, and policy limitations. This study systematically reviewed 56 peer-reviewed articles from 2004 to 2024, across 30 countries across five continents, employing the Capability, Opportunity and Motivation-Behaviour (COM-B) framework to identify the main drivers of walking and cycling behaviours. Findings highlight that the lack of dedicated infrastructure, inadequate enforcement of road safety measures, personal and traffic safety concerns, and social stigmas collectively hinder active mobility. Strategic interventions such as developing integrated cycling networks, financial incentives, urban planning initiatives, and behavioural change programs have promoted increased engagement in walking and cycling. Enhancing urban mobility further requires investment in pedestrian and cycling infrastructure, improved integration with public transportation, the implementation of traffic-calming measures, and public education campaigns. Post-pandemic initiatives to establish new pedestrian and cycling spaces offer a unique opportunity to establish enduring changes that support active transportation. The study suggests expanding protected cycling lanes and integrating pedestrian pathways with public transit systems to strengthen safety and accessibility. Additionally, leveraging digital tools can enhance mobility planning and coordination. Future research is needed to explore the potential of artificial intelligence in enhancing mobility analysis, supporting the development of climate-resilient infrastructure, and informing transport policies that integrate gender perspectives to better understand long-term behavioural changes. Coordinated policy efforts and targeted investments can lead to more equitable transportation access, support sustainability goals, and alleviate urban traffic congestion. 

Among urban public transport systems, light rail, mass transit, and tram systems offer sustainable travel options. However, many of these systems, particularly in developed countries, fail to meet user needs and the expectations of transport authorities. Increasing the demand for urban rail systems as an alternative to private cars is essential for achieving net zero targets and Sustainable Development Goals. This study investigates the factors influencing urban rail demand using qualitative data analysis, with a focus on thematic analysis. A systematic review of 53 studies from the UK, Europe, and worldwide, including journal articles and transport research reports, was conducted and coded using NVivo Version 15 software. Six main categories emerged: land use and accessibility, service quality, user benefits, governance, sustainability aspects, and user-focused elements. These categories, along with their themes and sub-themes, were analysed using cross-tabulations to compare attributes across domains. The key findings indicate that accessibility and intermodal connectivity are crucial for encouraging urban rail use, while ticketing, station facilities, walkability, travel costs, ventilation, and security also moderately influence user preferences. This study provides essential guidelines for policymakers and transport providers to improve urban rail systems and informed the development of a questionnaire to explore the interrelationships of these factors, discussed in a forthcoming paper. 

Autonomous vehicles (AVs) aim to improve safety and comfort of road users while contributing to the reduction of traffic congestion, air pollution, fuel consumption, and enabling mobility and accessibility of disabled and older people. As AV technology is rapidly advancing, there is an urgent need to explore how those new mobility services will impact urban transport systems, including the users, the infrastructure, and the design of future urban areas. This paper applies a systematic review to assess the role of AVs in urban areas. It reviews 41 articles published between 2003 and 2023, and uses inductive and deductive coding approaches to identify seven themes and thirty sub-themes within the literature. The seven include: benefits, attitudes, and behaviours and user perception, climate adaptation, climate mitigation, legislation and regulations, sustainability, and infrastructure. Studies related to benefits accounted for 25% of the sample, followed by behaviours and user perception (24%) and sustainability (22%). The least amount of research has been undertaken on the role of AVs to support climate adaptation. Geographically, almost half (#22) of the papers originate within Europe, followed by America (#10) and Asia (#7). There is only limited research originating from the Global South. This systematic review sets the scene for considering how AVs in public transport can be implemented in urban areas by establishing the current state of knowledge on user attitudes, perceptions, and behaviour, the benefits of AVs, the infrastructure and legislation and regulations required for AVs, and the role AVs have in climate mitigation, adaptation, and sustainability. 

Abstract Electric shared mobility hubs, called eHUBs, offer users access to a range of shared electric vehicles, including e‐bikes, e‐cargobikes, and e‐cars. Through the diversity of modes offered, eHUBs provide mobility solutions for different target groups and trip purposes. In this study, potential users’ willingness to use shared electric vehicles from eHUBs as either a commute or food shopping trip alternative was analysed using logistic regression methods. Results indicated that half of respondents were willing to use shared electric vehicles for at least a few of their regular commute or food shopping trips, although this proportion dropped substantially if considering the use of shared vehicles in combination with public transport. Across modes and trip purposes, holding a pro‐shared mobility attitude and belonging to the youngest age group strongly increased the willingness to use shared modes. Yet, while eHUBS may offer a potential alternative for at least some of people's regular commute or food shopping trips, cross‐mode shifts may be limited. That is, car drivers show a greater interest in shared e‐cars, whereas cyclists show a greater interest in e‐bikes and e‐cargobikes with public transport. Further influential factors, as well as implications for both shared mobility providers and local authorities, are discussed. 

ABSTRACT Traffic accidents have become a major concern for governments, organizations and individuals worldwide due to the material and moral losses they cause. It is possible to reduce this concern by taking into account the research conducted by relevant institutions and organizations in this field. The main objective of this study is to categorize traffic accidents according to driver violation types and analyse them using machine learning algorithms and feature sensitivity to identify the most influential variables in each category. For this purpose, traffic accident reports that occurred in Erzurum province in the last 1 year were used to categorize and classify driver violation behaviour types. Five different machine learning algorithms, namely k‐nearest neighbour, support vector machines, naive Bayes, multilayer perception and random forest, were used to examine the success performance of the classification. Among these, 91% successful classification was obtained with the random forest algorithm. Based on the classification obtained from this algorithm, sensitivity analysis was used to reveal the variables that most affect each violation category. The results of the analysis revealed that driver age and vehicle type were the most influential variables for many types of violations. Thanks to this study, the problems were clearly identified by going into the details of driver violation behaviours. At the end of the study, measures to reduce driver violation behaviours were proposed. If the recommendations that can reduce driver behaviour are taken into consideration by transportation authorities and policy makers, traffic accidents can be significantly reduced.