5D-AeroSafe is a 36-month project that will develop a set of drone-based services to increase the safety and security of airport and waterway, while reducing operational costs through the offering of five services, namely: CNS/GNSS equipment inspection and calibration, security checks in the airport perimeter and approaches, runways and taxiways inspections, aircraft inspections, waterways operation and inspections. The challenge is to integrate the flight of drones in restricted areas where they will co-exist with numerous commercial flights without increasing risks. The integration UTM/ATM is thus studied in detail in the project to propose these efficient solutions. The services are based on the use of several drones (fixed wings for large area monitoring, and VTOLs for detailed inspections and calibrations) integrated in a generic ground station equipped with innovative ITC capabilities, connected to the airport legacy systems. The 5D-AeroSafe modules will be connected, via SWIM, to airport maintenance systems for infrastructure inspection and calibration aspects, operations systems for the aircraft inspections, and finally with the local ATM for the ATM/UTM integration aspects. The project will be implemented under the control of relevant end-users’ stakeholders (airport and water airport operators), and authorities (Civil Aviation Authorities). The tests and validation of the system will be performed through three operational test pilots at different stages of the project as the implementation will be incremental, and will take place in real locations and in as much as possible real conditions. As the technological and operational innovations are multiple, the project will target a final TRL of 6-7. The consortium and the advisory board encompass a large set of end-users and authorities which is a guaranty of the operationality of the project outcomes, and the industry and research partners have been involved for a long time in drone services development.

Improving the CI capacities at preparedness, detection and response phases requires the attention to the human factor as well as the collaboration of heterogeneous organisations involved in the CI development and operation, ensuring a continuum of care, just as it is done for other ICT systems with the adoption of SecDevOps approaches. DYNABIC Consortium believes that the adoption of defensive AI and novel approaches to continuous business risk management based on enhanced SecDevOps can drastically improve critical services resilience. Furthermore, AI-based self-healing and autonomous response automation can greatly help to achieve fast and efficient recovery and enable the provision of fully resilient critical services to European citizens. The strategic objective of DYNABIC is to increase the resilience and business continuity capabilities of European critical services in the face of advanced cyber-physical threats. This objective will be pursued by delivering new socio-technical methods, models and tools to support resilience through holistic business continuity risk management and control in operation, and dynamic adaptation of responses at system, human and organization planes. DYNABIC will deliver the DYNABIC Framework that will enable OES to predict, quantitatively assess and mitigate in real-time business continuity risks and their potential cascading effects. Furthermore, it will enable the dynamic autonomous adaptation of critical infrastructures to meet Resilience goals by the automatic optimization and orchestration of response strategies. The DYNABIC framework will be validated in two types of demonstrations: i) Smart Preparedness, prevention and Response to Business Disruption risks in 4 critical infrastructures and supply chains (EV charging stations, Critical transport services, Telco services, and Hospital services), and i) Smart Preparedness and Response to Cascading Business Disruption risks in interconnected CIs.

The rapid advancement of autonomous vehicle technology promises enhanced efficiency and safety in transportation. However, operational constraints within Operational Design Domains (ODDs), including issues in sensing, behaviour prediction, and reliability, limit the potential of automated vehicles. Expanding the ODD framework is critical to enable these vehicles to navigate challenging scenarios like construction zones, unmarked roads, and adverse weather conditions. This expansion involves robust perception and decision-making algorithms, reducing the need for human intervention and facilitating integration with human-driven vehicles. While the benefits are substantial, challenges like data collection, sensor technology, and regulatory frameworks must be addressed through interdisciplinary collaboration. The iEXODDUS project is at the forefront of advancing digital technologies and navigation services, aligning with goals for increased safety, security, and sustainability in the mobility sector, ultimately paving the way for safer and more reliable automated transportation. iEXODDUS shall meticulously assess existing ODDs to unveil limitations and areas for improvement, fostering a deep understanding of ODD challenges and opportunities. This analysis serves as the foundation for a framework to assess and categorize ODDs across diverse automated driving scenarios. A key focus area is the enhancement of sensor technologies and perception capabilities through cutting-edge data fusion methods, expanding ODDs beyond current limits while considering environmental factors like weather conditions and road infrastructure. iEXODDUS envisions autonomous vehicles travelling across Europe, resolving harmonization and legal issues, and making policy recommendations. Collaboration with industry stakeholders and aiming for real-world demonstrations will enable an industry-tailored approach towards automated driving systems with extended ODDs.