Urban mobility poses various challenges to CCAM systems. Timely and reliable detection of occluded objects and especially vulnerable road users (VRUs) is a major one. To tackle this challenge, HIDDEN is developing advanced collective awareness (CA) and decision-making algorithms, with or without road infrastructure support. The CA system is focusing on the detecting occluded objects, including VRUs, while predicting their short-term trajectories using advanced behavioural models. In parallel, a novel driver gaze tracking and status monitoring system, is developed. The output of the CA and the driver gaze tracking is utilised by the real-time decision-making algorithms, which are designed to be explainable and aligned with human driving styles and ethical principles. HIDDEN deploys Hybrid Intelligence techniques across the whole chain, from perception till decision, to benefit from the combination of human with machine intelligence. During this process AI-related ethical and legal aspects are carefully considered via the development of a dedicated framework. HIDDEN developments will be evaluated both in real-world and in simulation. Real-world tests will be conducted with the AVs owned by the consortium (8 in total) in the respective testing facilities or on public roads, while for virtual tests novel co-simulation environments will be deployed. HIDDEN consortium has pre-selected four main use cases that drive the technical developments of the project. HIDDEN is developing CCAM systems which are not just technologically advanced but also deeply aligned with human driving styles, ethical principles and regulations, setting a new benchmark for the future of AVs technology. To increase HIDDEN’s impact, the consortium intends to reach out to CCAM stakeholders, in EU and beyond, engage in a continuous discussion with EU type approval authorities and UNECE working groups and promote mature results to standardisation.

The frequency and intensity of climate and weather extremes associated with anthropogenic climate change are increasing and will challenge us in terms of adaptation strategies at the local level. The project “Climate Resilient Development Pathways in Metropolitan Regions of Europe (CARMINE)” bridges the local and regional scales by providing impact-based decision support services and multi-level climate governance supporting local adaptation, including both traditional and Nature-Based Solutions. CARMINE’s overarching goal is to help the metropolitan communities of Europe become more climate resilient, by co-producing knowledge-based tools, strategies, and plans for enhanced adaptation and mitigation actions in line with the Charter of the EU Mission on Adaptation to Climate Change by 2030. To achieve this goal, focusing on the 2030-2035 timeframe and with longer perspectives up to 2050, CARMINE proposes an interdisciplinary approach aiming at (1) co-creation and co-development of decision-support services and guidelines for enhanced resilience and adaptive capacity, including early warning and disaster risk management systems; (2) cooperating closely with local to regional communities (stakeholders and users), decision-, and policy-makers (local authorities) to co-develop cross-sectoral frameworks for adaptation and mitigation actions; (3) delivering science-based R&I roadmaps for multi-level climate governance supporting local adaptation assessments and plans. The CARMINE methodology will be implemented in eight selected Case Study Areas to demonstrate proof of concept and project methodology will be demonstrated through the digital replication of climate and socio-economic characteristics of each area. The co-created knowledge and transferable development pathways from CARMINE will be shared widely via project networks in order to drive adaptation in other metropolitan regions of Europe, and beyond.

Networks are present in our lives in numerous different environments: to name just a few, networks can model social relationships, they can model the Internet and links between web pages, they might model the spread of a virus infection between people, and they might represent computer processors/sensors that have to exchange information. This project aims to obtain new insights into the behaviour of networks, which are studied from a geometric and computational perspective. Thereto, the project brings together researchers from different areas such as computational geometry, discrete mathematics, graph drawing, and probability. Among of the topics of research are enumerative problems on geometric networks, crossing numbers, random networks, imprecise models of data, restricted orientation geometry. Combinatorial approaches are combined with algorithms. Algorithmic applications of networks are also studied in the context of unmanned aerial vehicles (UAVs) and in the context of musical information retrieval (MIR). The project contains the work packages: “Geometric networks”, "Stochastic Geometry and Networks", “Restricted orientation geometry”, “Graph-based algorithms for UAVs and for MIR”, and “Dissemination and gender equality promotion”. The project connects researchers from 14 universities located in Austria, Belgium, Canada, Chile, Czech Republic, Italy, Mexico, and Spain, who will collaborate and share their different expertise in order to obtain new knowledge on the combinatorics of networks and applications.

Modal logics are a family of formal systems based on classical logic which aim at improving the expressive power of the classical calculus allowing to reason about “modes of truth”. The aim of the present proposal is to put forward a systematic study of substructural modal logics, understood as those modal logics in which the modal operators are based upon the general ground of substructural logics, weaker deductive systems than classical logic. Our aim is also to explore the applications of substructural modal logics outside the bounds of mathematical logic and, in particular, in the areas of knowledge representation; legal reasoning; data privacy and security; logical analysis of natural language.