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After the awareness-raising of recent years for coping with the global societal, economic and environmental challenges, the need for sustainable planning in the transport sector has become even more evident. Initiatives aiming at promoting sustainable and innovative mobility solutions, especially in urban areas where mobility needs are higher and transport problems are more intense, have been launched by different organizations around the world. In this context, autonomous electric vehicles are emerging as a promising solution; however, they are accompanied by new infrastructure requirements, along with safety concerns. Policymakers will be confronted with an array of choices, such as plug-in or wireless, dynamic or stationary charging and mixed flow with conventional vehicles or dedicated lanes, taking into account the uncertain impacts of innovation on safety and sustainability. Within this scope, these infrastructure alternatives are evaluated and prioritized, for the first time, in the present study, through the combined application of two hybrid multi-criteria analysis models, with the participation of experts. The analysis is based on a set of safety and sustainability criteria. Road safety and exposure to electromagnetic radiation emerge as the most important criteria, with the optimum solution—based on current data—consisting of plug-in charging and the circulation of autonomous electric vehicles in dedicated lanes.

Public Transport (PT) is supposed to be probably the most up-to-date answer to the growing need for relieving traffic congestion, the associated environmental problems and the continuously increasing cost for transferring passengers. The expansion of urban centres cannot support a PT system that would serve the passenger directly from the origin to the destination point. The combination of various modes of transport between trip ends represents the new reality. The aim of this paper is to present general guidelines for securing safe and comfortable transfers between different transport modes.

In recent years, the use of roundabouts in road networks has reflected a sustainable and modern solution for traffic intersections. Their implementation, integrated design, and proper evaluation are a necessity to achieve their beneficial results. According to the latest edition of the Highway Capacity Manual (HCM) and the Highway Capacity and Quality Service (HCQS), a comprehensive evaluation of a roundabout is based on the interchangeable use of the LOS (level of service) and QOS (quality of service). Both manuals describe the LOS criteria, which are the same as those currently used for unsignalized at-grade intersections, while the QOS methodological description and criteria are not specifically defined. The quality of service, which corresponds to road users’ perceived satisfaction, is determined by identifying and evaluating certain factors that have an impact on users. While the previous work on evaluating the quality of roundabouts is limited, this work aimed to present and evaluate the concept of QOS for urban roundabouts in Greece and to assess the factors that affect drivers’ perceived feeling of comfort. The methodology used for the research, included data collection via an on-line questionnaire addressed to the users of the Greek road network and a statistical analysis based on the performance of six latent variables named quality components (exploratory factor analysis). A structural equation model (SEM) was used to determine the causal relationship between primary factors and quality components. It was noted that the SEM cannot predict the travel behavior but it has ability to express relationships between unobserved and observed variables. The results of the revealed model are of great value for the development of: (a) a comprehensive conceptual framework of the QOS and (b) a critical analysis of the parameters that should be considered for the assessment of the QOS of a roundabout. Identifying the factors that influence road users’ perception in terms of safety and comfort (quality of service) leads to a better knowledge and understanding of the road network characteristics that are important to road users and that influence their behavior and level of satisfaction.

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