Aggelos Soteropoulos

Urban road transport faces growing challenges from population growth and increased vehicle density, exacerbating congestion, accidents, and environmental impacts. Digital technologies, including Cooperative Intelligent Transport Systems (C-ITS), predictive traffic analytics, and Digital Twins promise to improve traffic flow and safety by enabling real-time information exchange between vehicles, infrastructure, and road users. However, the effectiveness of such systems depends not only on technical capabilities but also on how information is perceived, prioritized, and delivered to different user groups. Drawing on a standardized questionnaire survey of 171 car drivers and 121 pedestrians across ten European countries, this study investigates which information on traffic events as well as infrastructure and environmental conditions are considered most important by car drivers and pedestrians, and through which communication channels they prefer to receive such information. The findings reveal clear distinctions in how safety- and road condition-related events are perceived, as well as in preferred delivery methods, highlighting the need for adaptive, user centered communication strategies. Based on these results, the study derives empirically grounded recommendations on how to communicate traffic information in ways that maximize effectiveness and acceptance while reducing cognitive overload.

After the initial hype, recent years have seen markedly more restrained assessments of how connected and automated vehicle technology will develop. A revolutionary scenario that sees a single IT company suddenly launch a successful automated driving system capable of handling every driving task as well as a human (Beiker 2015) is now widely considered unlikely, at least in the medium term. Instead of this presumed revolution, we are currently facing the challenge of a decades-long period of transition – a “Long Level 4” – during which only certain parts of the road network will be accessible to automated vehicles (Mitteregger et al. 2022, Soteropoulos et al. 2020).

Automated vehicles will have a significant impact on our mobility and the way we travel. Already over the next few years, highly dynamic developments can be expected in the mobility sector, with fundamental changes and upheavals that will present both opportunities and risks. From the point of view of transport, infrastructure and urban planning, strategies are therefore required as to where and how automated vehicles can be best deployed.

Urban freight transport is assuming an increasingly important role in the field of urban mobility as well as in urban transport policy, as e-commerce is booming: with the advance of digitalization, goods are increasingly being ordered via the internet, with a resulting sharp increase in delivery transport volumes (cf. Muschkiet/Schückhaus 2019: 358; German Federal Government 2019: 44f.). New sustainable solutions and concepts are therefore needed in urban logistics, with the last mile in particular posing a major challenge due to a lack of bundling and the great effort involved (cf. Gerdes/Heinemann 2019: 399; Buthe et al. 2018: 30; Lierow/Wisotzky 2019). At the same time, new delivery media are emerging, such as delivery robots (cf. Baum et al. 2019: 2455; Jennings/ Figliozzi 2019: 317), which are seen as having great potential for the last mile.

Connected and automated driving is one of several emerging mobility trends that will fundamentally impact the use and design of public spaces in the coming decades. The uptake of transportation network companies (TNCs), such as Uber, has shown that a greater use of shared modes adds more vehicles to the road and shifts pick-up and drop-off locations onto the street, i.e. increasing activity at the kerb (Larco 2018: 50; Erhardt et al. 2019). Similar effects were caused by recent waves of dockless micromobility options, such as free-floating bikes or e-scooters, which temporarily led to congested pavements and increased spatial demands in public space (Polis 2019).

The articles in this volume deal with effects on spaces and with control and planning approaches at municipal and regional level. It is essential to distinguish here between the spatial conditions of rural communities and regions and those of urban centres and major cities. Neither rural nor urban areas are homogeneous, but are complex areas with a wide variety of settlement structures, natural spaces and infrastructures, functions and challenges (VCÖ 2019: 9).

The potential rise of automated vehicles (AVs) may significantly impact future traffic volumes, in turn affecting urban street designs and adjacent land use. While integrated studies on potential traffic and land-use changes due to AVs largely concern issues of location choice and changing settlement patterns, assessments of how AVs may influence the quality of streets depending on the requirements of adjacent land use remain scarce. This paper presents an integrated assessment of the urban effect of AVs on traffic and neighborhoods in Vienna. It provides a methodology to assess whether changing traffic volumes are compatible with the land use of a given neighborhood to approximate street space requirements for shared automated shuttles and to visualize possible trajectories of spatial transformation by considering local development goals. The results show that the opportunities to convert street space and the risks of environmental harm due to AVs will vary across neighborhoods and street typologies. It is crucial for policymakers and planners to consider such contextual differences to gain better insight into the functional requirements and urban consequences of AVs. This assessment aims to shed light on the possible trade-offs of a system change in favor of AVs to help evaluate adequate operational conditions and inform proactive traffic and urban design policies to harness possible implications.

Developments in the field of automated mobility will greatly change our mobility and the possibilities to get from one place to another. This paper presents different scenarios for personal mobility in Austria, anticipating the possibilities and developments in the field of automated vehicles (AVs). The scenarios were developed using a systematically formalized scenario technique and expand the social and political discourse on automated mobility, which is currently characterized by a lack of experience and visibility as an established transport service. Using system dynamics modeling techniques, i.e., the Metropolitan Activity Relocation Simulator (MARS), impacts of the scenarios on the Austrian transportation system are estimated. The simulations show that, without suitable transport policy measures, automated mobility will lead to a significant increase in the volume of individual traffic and to modal shift effects with lower traffic volumes for public transport, walking and cycling. In addition, without a link between AVs and post-fossil propulsion systems, increases in pollutant emissions can also be expected. In contrast, the simulation results of an increased use of AVs in public transport show positive effects for the support of a more sustainable mobility. Hence, transport policy measures accompanying the introduction and development of automated vehicles will be needed in the future to reach a sustainable development.

Zusammenfassung: Connected and automated driving is one of several emerging mobility trends that will fundamentally impact the use and design of public spaces in the coming decades. The uptake of transportation network companies (TNCs), such as Uber, has shown that a greater use of shared modes adds more vehicles to the road and shifts pickup and drop-off locations onto the street, i.e., increasing activity at the curb (Larco 2018: 50; Erhardt et al. 2019). Similar effects were caused by recent waves of dockless micromobility options, such as free-floating bikes or e-scooters, which temporarily led to congested sidewalks and increased spatial demands in public space (Polis 2019).