MyCorridor mission is to facilitate sustainable travel in urban and interurban areas and across borders by replacing private vehicle ownership by private vehicle use, as just one element in an integrated/multi-modal MaaS chain, through the provision of an innovative platform, based on mature ITS technology, that will combine connected traffic management and multi modal services and thus facilitate modal shift. It will propose a technological and business MaaS solution, which will cater for interoperability, open data sharing, as well as tackling the legislative, business related and travel-behavior adaptation barriers enabling the emergence of a new business actor across Europe; the one of a Mobility Services Aggregator. MyCorridor will prove this paradigm change through a number of European sites, which are performing long distance and cross border Pilots in a corridor of 6 European countries; from the South (Greece, Italy) through to Central (Austria, Germany, the Netherlands) and Eastern Europe (Czech Republic). Those sites will develop Mobility Package tokens, purchased through one-stop-shop and will incorporate the following services: a) Traffic management services b) Services related to MaaS PT interface c) MaaS vehicle related services and d) Horizontal (business related) services. MyCorridor tasks will be undertaken by a balanced consortium that encompasses all key actors, namely 2 key industrial Partners (SWARCO, Tom-Tom), 7 dynamic SME’s in the mobility market (INFOTRIP, CHAPS, WINGS, MAPTM, AMCO, VivaWallet, HaCon), 1 mobility agency (RSM), 1 ITS association (TTS), 4 Research performers (UNEW, CERTH, UPAT, SRFG), 1 multinational Legal Firm with specialisation in novel mobility scheme structuring (OC) and IRU which will act as the liaison to MaaS Alliance. Also, 11 Letter of Supports have been signed by external to MyCorridor service providers, that commit to allow their services integration in MyCorridor platform.

Connected and Cooperative Automotive Mobility (CCAM) solutions have emerged thanks to novel Artificial Intelligence (AI) which can be trained with huge amounts of data to produce driving functions with better-than-human performance under certain conditions. The race on AI keeps on building HW/SW frameworks to manage and process even larger real and synthetic datasets to train increasingly accurate AI models. However, AI remains largely unexplored with respect to explainability (interpretability of model functioning), privacy preservation (exposure of sensitive data), ethics (bias and wanted/unwanted behaviour), and accountability (responsibilities of AI outputs). These features will establish the basis of trustworthy AI, as a novel paradigm to fully understand and trust AI in operation, while using it at its full capabilities for the benefit of society. AITHENA will contribute to build Explainable AI (XAI) in CCAM development and testing frameworks, researching three main AI pillars: data (real/synthetic data management), models (data fusion, hybrid AI approaches), and testing (physical/virtual XiL set-ups with scalable MLOps). A human-centric methodology will be created to derive trustworthy AI dimensions from user identified group needs in CCAM applications. AITHENA will innovate proposing a set of Key Performance Indicators (KPI) on XAI, and an analysis to explore trade-offs between these dimensions. Demonstrators will show the AITHENA methodology in four critical use cases: perception (what does the AI perceive, and why), situational awareness (what is the AI understanding about the current driving environment, including the driver state), decision (why a certain decision is taken), and traffic management (how transport-level applications interoperate with AI-enabled systems operating at vehicle-level). Created data and tools will be made available via European data sharing initiatives (OpenData and OpenTools) to foster research on trustworthy AI for CCAM.

FAME will develop and validate common methodologies and tools to facilitate the sharing of best practices and lessons learned to support the collaboration within the community of CCAM stakeholders across the complex cross-sectorial value chain needed for the organisation and evaluation of large-scale demonstration and future scale-up to the impacts of complete CCAM solutions. The mission of FAME supports the commitment of the European Commission and the CCAM Partnership to provide a long-term coordination framework for R&I and large-scale testing and evaluation activities in Europe. The establishment of a stakeholder-validated European framework for testing on public roads, including a CCAM test data space (TDS), a common evaluation methodology (CEM), and of means for exchange of knowledge on CCAM activities will improve cooperation, consensus building and data sharing. It will enable comparability and complementarity of the results of all testing and large-scale demonstration activities in Europe. FAME builds on a strong legacy of EU-funded Coordination and Support Actions which have developed harmonised methodologies and federated large networks of stakeholders to drive consensus building on challenges, needs and requirements for CCAM and Field Operational Tests. FAME involves 23 partners and over 2000 subscribers of the current Joint CAD network which has collaborated with the European Partnership on CCAM Partnership since its inception. The development of the European Framework for testing on public roads is at the core of FAME. The overall approach is built around three main building blocks and aims to engage with and enable (in terms of capacity building) stakeholders from the CCAM area, as well as capitalise knowledge about CCAM through an integrated approach including stakeholder engagement (WP3), research and innovation on the evaluation methodology and testing framework (WP 4 and 5) and communication and knowledge sharing (WPs 1 and 2) to maximise impact.

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.

As the introduction of automated vehicles becomes feasible, even in urban areas, it will be necessary to investigate their impacts on traffic safety and efficiency. This is particularly true during the early stages of market introduction, where automated vehicles of all SAE levels, connected vehicles (able to communicate via V2X) and conventional vehicles will share the same roads with varying penetration rates. There will be zones and situations on the roads where high automation can be granted, and others where it is not allowed or not possible due to missing sensor inputs, high complexity situations, etc. In the areas where those zones merge many automated vehicles will change their activated level of automation. Therefore, we refer to these areas as “Transition Areas”. TransAID will develop and demonstrate traffic management procedures and protocols to enable smooth coexistence of automated, connected and conventional vehicles especially at Transition Areas. A hierarchical approach will be followed wh