The preference and the development of electromobility are included among the priorities of transport policies in many European countries. This article deals with the issue of electric vehicle operation from the point of view of the environmental impact of electric power production, specifically the energy effectiveness of its production by utilizing primary power production sources. Differences in the effectiveness of the conversion of mixed forms of energy into electricity and their share in the process directly affect the final level of greenhouse gases (GHG) production, and thus the ecological footprint of electric vehicle operations. The specification of energy consumption and GHG production is based on the principles of the EN 16 258: 2012 standard, which considers legislative-regulated power plant effectiveness values, statistical values of GHG emissions from electricity production, and real energy consumption values of an electric vehicle fleet. The calculation takes into account the share of primary sources and the efficiency of electricity production and effectiveness of electricity distribution in each of the evaluated countries. The specific research study is performed by comparing measured parameters for individual countries chosen from the Central Europe region. The results of the study show that the quantification of the positive environmental consequences of increasing electromobility varies greatly in different countries, which means full-scale deployment of electromobility does necessarily deliver the sustainability of transport that was expected from it.

Emerging info-communication and vehicle technologies (especially vehicle automation) facilitate evolvement of autonomous road freight transportation. The entire transport system and its operation undergo a major change. New service concepts are growing and the existing ones are being transformed. The changing is particularly significant in city logistics. However, there are debates about the ways of automation of processes targeting improvement of capacity utilisation and decrease of expenditures. The main research questions of the paper are therefore: what properties of the future autonomous freight transportation are presumed; what system structure is to be constructed and how the system is to be operated? After introducing the basic notions and reviews of the current systems and developments, the shifting from traditional freight transportation to autonomous system is investigated by several aspects. A system- and process-oriented analytical modelling method has been applied. The main system constituents and their connections are modelled. Finally, we elaborate the operational model of road freight transportation, which is applicable principally in metropolitan areas. In conclusion, the presentedresults appoint the research and innovation trends towards the automation of freight transportation.

The use of autonomous vehicles (AVs) has the potential to transform users’ behaviour and urban space management. Quantitative and qualitative analyses of impacts require a scenario building method. We considered the fleet size, modal share, car ownership, parking preferences, and urban space repurposing during the elaboration of a novel method. Existing scenarios and results of a questionnaire survey have been used as sources. The method was applied to build scenarios in a case study in Budapest, Hungary. The results were used to calculate the impacts on urban space management, including environmental savings. The key findings are: scenarios with significant shared AV use show that parking demand may be minimised (almost 83%) and urban space repurposing has the highest potential; furthermore, AV use and sharing acceptability may decrease the fleet size and alter the type of shared mode to multiple occupancies. The developed scenario building method serves as a base for future studies. The produced scenarios allow the researchers to focus on the analysis of the impacts caused.

Faced promising development of autonomous vehicles, the concept Mobility as a Service embraces AVs. The autonomous delivery has also been arising and tested for last-mile solution. Accordingly, passenger transportation and delivery service are to be jointly coordinated in the future MaaS. The research niche is summarized as how to embed crowdsourced parcel delivery into MaaS based on AVs. Electricity powered vehicles are to be applied considering energy consumption and air emission. Research questions are identified as what this novel service is and how it works, especially focusing on task coordination and the related information management. The system engineering process-oriented approaches, matching theory, and numerical method have been applied. The service concept has been elaborated, which contains information system architecture model and functional model. The matching condition of this service is summarized. As the embedded delivery can partially share the demand of traditional delivery service, the calculation scenarios of energy savings and emission decrease per parcel delivery are presented. The results facilitate service planning and development.

Due to changing expectations of characteristics of mobility demands, public transportation users increasingly require a reduction of both the preparation and travel time, an easier and more pleasant travelling experience as well as route plans based on reliable data. Both international and domestic research is widely concerned with route planning optimization. Exemplary assistance applications are already in operation, but they are only semi-occasionally and slightly personalized. Consequently, there is potential for significant research and development in this area. Our developed method and algorithm evaluates the routes based on the personalised user settings and in this way, the ideal routes can be determined. User preferences are represented in evaluation criteria. The algorithm also manages network modifications and often-changing user preferences. The novelty of our algorithm lies in the more realistic evaluation of the routes appreciably considering both the exact physical properties of the infrastructure and the users’ detailed personal preferences.