The dependence of road transport on fossil fuels and its contribution to greenhouse gas (GHG) and pollutant emissions are main concerns leading to the need for shifting toward alternative energy sources and, namely, electromobility. The current paper aims to identify the key determinants affecting the consumer adoption of electric vehicles (EVs), focusing on private passenger cars. Toward this purpose, a systematic review of recent international literature is conducted in order to identify motivators and barriers, which are then categorized following the PESTLE (Political–Economic–Social–Technological–Legal–Environmental) approach. Based on the review results, main policy implications and recommendations are discussed. A main conclusion is that the recent literature highlights a wide array of determinants, without converging as to which ones are the most influential regarding EV adoption by consumers. Another conclusion is that the environmental aspects are less important for consumers than anticipated, despite the concerns about climate change and renewable energy transition.

In an era of environmental and socio-economic crisis, sustainable transport planning is vital as ever, especially given that the transport sector is responsible for the greatest part of total air pollution and greenhouse gas emissions. New vehicle technologies, such as autonomous and electric vehicles, emerge as promising alternatives, creating, however, both opportunities and challenges and raising questions relating to their performance. Can these new vehicle technologies really perform better than conventional ones in terms of sustainable mobility? Which one of them constitutes the optimum solution? How does each alternative perform with regard to different evaluation criteria, such as air pollution or road safety? In order to answer such questions, and to select the optimum solution, a comparison between autonomous, electric, autonomous electric and conventional vehicles is executed, based on a set of social, economic and environmental criteria. For this purpose, a new decision-aiding methodology, allowing for a holistic evaluation of the alternatives through a comprehensive literature review and experts’ participation, is applied. It is mainly based on the combined application of two hybrid multi-criteria analysis models, creating a more solid background towards optimum decision-making, thus constituting an important decision support tool for project appraisal and funding within the framework of sustainability in any sector.

Sustainable urban mobility has been the epicenter both at the scientific and administrative level during the last decades, with a high number of relevant research projects, awareness campaigns, and other initiatives taking place at the local, national, and international level. However, many urban areas have so far achieved limited results in this direction because of political, institutional, organizational, technological, infrastructural, and socio-economic barriers as well as unforeseeable (e.g., COVID-19) conditions. The overall aim of the present research study is to support policy-making by proposing a methodology that identifies and prioritizes the sustainable mobility barriers for a specific urban area, with a view to developing effective policies. Towards this purpose, this work provides, in the first phase, a comprehensive inventory of barriers based on a literature review. In the second phase, a methodology using as a basic scientific tool a modified Delphi-AHP is proposed for the adaptation of this inventory to a specific urban area and for both the evaluation and prioritization of sustainable mobility barriers. The whole process is then applied in Thessaloniki, Greece, a European city suffering from many problems related to sustainable mobility. The above pilot application confirms that this approach can be integrated as a supporting tool in the first steps of sustainable urban mobility plans (SUMPs).

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.

The European Union’s policy aims for the wide-scale deployment of automated mobility by 2030, i.e., within the next programming period (2028–2034), with the deployment of autonomous road vehicles (AVs) in cities playing a key role. Researchers suggest that AV deployment will have complex impacts on urban development, which are difficult to quantify due to scarce real-life data. The present research aims to evaluate different policy pathways of AV deployment for sustainable urban development in the next EU programming period. A multicriteria analysis is conducted, combining AHP and VIKOR, with the participation of experts across Europe. Initially, the potential impacts on sustainable urban development are weighted as evaluation criteria. Then, different pathways are evaluated against these criteria, i.e., AV deployment as collective and/or private transport in specific areas and periods or in the whole Functional Urban Area (FUA) on a 24 h basis. An interesting finding is that the effect on the city’s spatial development, not thoroughly examined by literature, is highly ranked by experts. Regarding policy pathways, autonomous collective transport with 24 h service of the FUA emerged as the optimum alternative. The proposed methodology provides a tool for planners, researchers, and policy makers and a framework for an open debate with society.

Despite the significant progress in the last few decades, road safety improvement still constitutes an imperative global need. Especially in urban areas, the improvement of road safety is an even more complicated and multi-factor problem. Every minute, a human life is lost in an urban road network in the world. Given that almost all road accidents are preventable, more effective planning toward improving road safety, as a structural element of sustainable urban mobility, is imperative. The aim of the present research is to provide decision support analysts and policy-makers with a decision-support tool that identifies and prioritizes the factors undermining road safety in an urban area, with a view to developing effective policies. For this purpose, a comprehensive inventory of factors that may undermine road safety in an urban area, as well as an inventory of relevant measures and policies, is provided, based on an international literature review. The most important factors and, subsequently, the most effective measures and policies are identified and prioritized through a multi-criteria approach (modified Delphi–analytical hierarchy process (AHP)–technique for order preference by similarity to ideal solution (TOPSIS)). The Greek urban road networks, starting from the second largest city in Greece (Thessaloniki), are selected as a case study. Problems related to limited resources not allowing for systematic surveillance and policing, making arbitrary decisions instead of adopting a scientific decision-aiding methodology, education and mentality issues, infrastructure planning and maintenance, cooperation and coordination between different authorities, and laxity of penalties are highlighted as the most important factors, based on which four sets of measures and policies are identified and prioritized.