Urban mobility is becoming an issue of great importance in today’s society due to the increasing population movements towards big cities and the exponential growth of cities in developing countries. Today, urban mobility schemes are evolving faster than ever mainly due to social, economic and technological changes. The traditional choice between walking, taking public transport or else buying a car is being extended with a wide range of new flexible mobility services, such as vehicle sharing and ride-hailing. Those shared mobility services are blurring the lines between private and public transport, with the potential of displacing car ownership but also traditional transit systems. And the adoption of autonomous vehicles will only accelerate this trend. There's the need for Public Transport Authorities, operators and industrial providers to prepare for this change and adopt the necessary tools to manage the mobility services of the future in a more flexible and efficient way. EGNSS has the potential to enhance the quality of public transportation, by reducing operational costs, reducing traffic and providing savings in time and fuel, while fostering the development a wide range of new shared mobility services. ARIADNA aims at supporting the adoption of EGNSS for Public Transport and urban mobility, by raising awareness on GALILEO and EGNOS benefits among the different stakeholders involved and supporting the introduction of new solutions provided by SMEs and start-ups. The project builds up on experience gained from previous R&D related projects and the extensive network of stakeholders that can be reached through UITP and EIT Urban Mobility networks.

Safer urban environments are needed for all road users to ensure the European targets to halve road deaths and injuries by 2030 are met. Vulnerable road users require specific attention in an urban environment that is subject to constant change as new forms of transport and micro-mobility enter the system. Existing traffic simulation models allow changes in traffic conditions to be tested but are often vehicle and travel time focused and do not measure detailed outcomes specific to vulnerable road users and road safety. City administrations and transport managers will benefit from predictive tools that allow these changes and their implications for road safety, mobility, and sustainable transport to be anticipated, and support the associated policy, regulatory and consumer response. The Predictive Approaches for Safer Urban Environments project (PHOEBE) will move beyond the state of the art and deliver an interdisciplinary solution that will integrate traffic simulation, road safety assessment, human behaviour, mode shift and induced demand modelling and new and emerging mobility and telematics data into a harmonised, prospective assessment framework for road safety. New conditions and mobility solutions will be able to be assessed and safe system solutions tested. The PHOEBE framework, software module and knowledge products will allow dynamic safety prediction and socioeconomic evaluation that is evidence-based and simulates future scenarios and impacts. Simple and effective visualisation and socioeconomic modelling will provide the confidence for policy decisions and investment. City administrations across EU will be consulted as the framework is developed and deployed. The feasibility of the framework will be demonstrated in three use cases in Athens (GR), Valencia (ES) and West Midlands (UK), which have been selected to maximise the use of existing base traffic models, potential impact and to ensure the future scalability and transferability of the solution.

The mobility ecosystem is rapidly evolving, whereby we see the rise of new stakeholders and services. Examples of these are the presence of connected and automated vehicles, a large group of organisations that rally to establish various forms of share mobility, with the pinnacle being all of these incorporated into a large Maas ecosystem. As these new forms of mobility offerings start to appear within cities, so do the new ways in which data are being generated, collected, and stored. Analysing this (Big) data with suitable (artificial intelligence) techniques becomes more paramount, as it leads to insights in the performance of certain mobility solutions, and is able to highlight (mobility) needs of citizens in a broader context, in addition to a rise in new risks and various socio-economic impacts. Successfully integrating all these disruptive technologies and solutions with the designs of policy makers remains a challenge at current. let alone being able to analyse, monitor and, assess mobility solutions and their potential socio-economic impacts. nuMIDAS bridges this (knowledge) gap, by providing insights into what methodological tools, databases, and models are required, and how existing ones need to be adapted or augmented with new data. To this end, it starts from insights obtained through (market) research and stakeholders, as well as quantitative modelling. A wider applicability of the project’s results across the whole EU is guaranteed as all the research is validated within a selection of case studies in pilot cities, with varying characteristics, thereby giving more credibility to these results. Finally, through an iterative approach, nuMIDAS creates a tangible and readily available toolkit that can be deployed elsewhere, including a set of transferability guidelines, thus thereby contributing to the further adoption and exploitation of the project’s results.

Railway stations hold a unique position in the urban landscape: they not only act as complex nodes of mobility and transport, but also as public places that can be seen as integral elements of the city. Consequently, stations have a decisive impact on their urban surroundings as places of everyday life, affecting all stakeholders including citizens and the environment. The central ambition of RAIL4CITIES is to develop a new operational, readily available and highly applicable model of stations (SCP model), combined with a common European methodology and tool for its effective implementation. The project takes inter-dependent impediments (profit-orientated business model, complex web of agents and stakeholders, policy gaps) into account and provides decision makers with the tools to transform stations into promoters of sustainable cities. The model will be applied to 5 living labs addressing the stations’ transformation into hubs of green and active mobility (FR), energy hubs (IT), towards Transit Oriented Development (DE), into a socially-inclusive services hub with using Nature Based Solutions (PL) and services hubs enabling the 15-minute city and circular economy (BE). This will be enhanced by 3 case-studies from the high-speed rail line from Lisbon to Oporto (PT) to study the resilience of infrastructures for both adaptation of spaces to new future uses, and adaptation to climate-change issues and health crises. With 14 partners from 7 European countries, further supported by 9 institutions through letters of support, the RAIL4CITIES consortium and ecosystem integrates the relevant stakeholders from universities, industry, government and the public, and is therefore in the position to design, evaluate and publish a EU-wide model for transforming existing stations or designing new ones into socio-technical systems operating as city’s greening engines for the surrounding environment, and new urban hubs aggregating multiple services for the users and its citizens

Until now, the approach to road safety has primarily focused on analyzing the most common types of injuries based on road user types and crash characteristics. There is a growing consensus to shift the paradigm towards a user-centric approach that considers the specific needs (incl. their diversity) and the behaviours of road users. IMPROVA project will focus on current knowledge regarding the conditions and mechanisms leading to serious injuries of all road user types, and both physical and psychological long-term consequences as well as future scenarios regarding the overall crash occurrence considering changes due to vehicle automatization. IMPROVA will introduce a formula that will predict a likelihood of sustaining LTC. This will allow stakeholders to estimate physical and psychological long-term consequences due to road traffic accidents in a compact manner directly after the crash. HBMs will be specifically upgraded in their capabilities to depict LTC-relevant injury mechanisms. It will be achieved through validation of mode responses against experimental tests and through the development and tailoring of risk curves, using the latest available biomechanical data. Virtual Testing procedures will be developed and demonstrated for future application environments, specifically through the involvement of industrial partners and NCAP labs. IMPROVA network consisting of NCAPs, US, Australian and Asian entities and medical and psychological expert panel group will help the harmonization not only of the knowledge of the long-term consequences but also to harmonize the data collection, evaluation of such injuries leading to LTC and to use appropriate tools validated for this purpose. The communication with regulatory authorities, NCAPs, rescue team and end-user will enable the awareness of the topic and implementation of appropriate countermeasures.