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This paper describes a methodology and a Decision Support Tool (DST) for the assessment of the impacts of future scenarios of public electric mobility on the electric Distribution Network (DN) of a city, aimed to support the implementation strategies of the electric charging network for the Local Public Transport (LPT).The objective of the proposed tool is supporting the decision makers in estimating the effect of the future development of electromobility on the urban electric grid considering the evolution of both electric buses and their charging infrastructure.Some scenarios for the development of electric charging infrastructure for LPT were identified together with the local public transport operator and the energy provider. The results, which are of interest to both the local Public Transport Operator (PTO) and the local Distribution System Operator (DSO), have been quantified for the city of Turin (Italy), but the methodology can be adopted in any urban context: DSOs and PTOs of each city can use the proposed tool as a support to define their public transport electrification strategies.Some results from the case study examined in this paper (Turin, Italy) show that the energy demand related to the electrification of LPT on a typical weekday is about 45 MWh in 2030 (corresponding to 40 % e-bus), and about 90 MWh when the entire bus fleet is electric. It is also shown how more distributed recharging during the day (with intermediate recharging at the terminus) can dampen the energy/power peaks required at the depot compared to overnight recharging alone: a reduction of up to 27 % of energy demand at the depot is observed due to opportunity charging.

The interest in operating autonomous vehicles is growing and several demonstration sites using automated shuttles have been established all over the world. Major work is involved in setting up an automated shuttle operation that involves more than identifying the relevant site, including adhering to current regulations and obtaining approval, as well as a considerable amount of preparation and commissioning required at the site. The shuttle must pass relevant national vehicle regulations, and the operation site has to undergo a site assessment. This paper is based on lessons learned achieved from setting up automated shuttle operations in three different areas in Europe: Brussel (Belgium), Linköping (Sweden) and Turin (Italy). The focus is on the practical aspects of operation. Through the experience we have gained of setting up demonstration sites at three locations in Europe, we have identified the need to summarise the lessons learned from preparing AV shuttle operation sites in order to facilitate the implementation of other operation sites. Hence, this paper aims to consolidate lessons learned during preparation and implementation of automated shuttle operations in near urban environments and to identify the path toward future implementation The three sites operate different brands and number of shuttles, different types of infrastructure and varying local conditions. The focus here was on generic lessons learned and not to understand differences between brands and operators. It is clear that further development of the AV shuttles is vital to ensure that they operate smoothly in complex traffic situations considering lane and road width, shared spaces, snow, dust, rain, leaves, birds, etc. Adapting the road infrastructure to enable the shuttles to run in the autonomous mode should be avoided, instead the shuttle development should prioritise fitting into the existing traffic environment and eco system. Mitigation areas have been identified covering: road infrastructure, weather dependant operation, season dependent operation, improvement of localisation, digital infrastructure, design and working conditions, and citizens’ user experience.

The development and the diffusion of the electromobility is crucial for reducing air pollution and increase sustainable transport. In particular, electrification of private mobility has a significantly role in the energy transition within urban areas, since the progressive substitution of conventional passenger cars by electric vehicles (EVs) leads to the decarbonisation of transport sector without direct emissions. However, increasing EV penetration in the market forces an expansion of the existing charging infrastructure with potential negative impacts on the distribution grid. In this context, a simplified approach is proposed to estimate the energy and power demand owing to the recharge of electric passenger cars within the city of Turin in Italy. This novel approach is based on the usage of floating car data (FCD) to identify the travel behaviour and parking habits of a non-EV passenger car in the city. Mobility data were then used to evaluate EVs energy consumption and charging needs considering different charging options (public or domestic) and range anxiety in different scenarios of EV diffusion. Aggregated load profiles and demand were finally evaluated both for the whole and for each zone of the city as possible resource for city planner or distribution system operators (DSO).

The present paper proposes a model for evaluating environmental, social, and economic impacts exerted by the diffusion of electric vehicles (EVs), which is a phenomenon that can significantly affect the achievement of some of the objectives set by the Sustainable Development Agenda. The impact evaluation is carried out through the System Dynamics methodology, combined with scenario analysis. Considering the Piedmont region (Italy) as a case study, the model forecasts the impacts of EV diffusion using a simulation timeframe of 12 years and leveraging eight EV diffusion scenarios. According to the model, an increase in the number of EVs results in less air pollution and, therefore, minor public health expenditure. These cost savings can be turned into incentives for purchasing new EVs, which make the fleet increasingly greener as part of a self-reinforcing loop. Despite the fact that the model could be improved through additional research on some variables’ definitions, this ex ante evaluation tool represents a valuable instrument for policy-makers. In fact, it provides a comprehensive picture of EV diffusion in view of the triple sustainability principles: System Dynamics, in particular, allows singling out causal relationships among variables, thus anticipating possible effects of planned policy actions.

Urban areas can be considered the ground for the challenges related to the UN’s Sustainable Development Goals (SDGs). The objective of shaping cities as human settlement that will see a more inclusive, safe, resilient, and sustainable future is often argued in literature as an issue dependent on behavioral change of inhabitants in urban areas. In this paper, the authors question if experimental applications based on gamification can co-produce more sustainable neighborhoods through an impact evaluation method that departs from individual choices within the complex of urban mobility. This investigation is carried out within MUV (Mobility Urban Values), an EU research and innovation project, which aims to trigger more sustainable urban mobility in six pilot cities. This article describes the critical method of validation, an impact assessment of the MUV experimental gamification in the pilot cities, in order to represent a proof for future urban strategies. This methodological approach is based on an evaluation structured on indicators of both impact and process suitable for urban contexts. As based on six pilot cities, with possibilities for transferability to other contexts and scalability to other cities, the method represents a reference work for the evaluation of similar experimental applications.