Research to help shape the future regulatory framework for a DES

The grant opportunity HORIZON-SESAR-2025-DES-ER-03 focuses on regulatory research aimed at shaping the future framework for the Digital European Sky (DES). It is a part of the HORIZON JU Research and Innovation Actions concerning the aviation sector, particularly air traffic management and associated technologies. Eligible applicants include universities, research institutions, small and medium-sized enterprises, and large companies operating within aviation and digital infrastructure. The funding type is a lump-sum grant, which implies that recipients will receive a fixed amount to cover eligible project costs.

The application process is single-stage and open, with a submission deadline set for September 16, 2025. The grant targets EU member states and associated countries. While the funding amount for specific projects within this call may vary, similar actions usually range between 1 million to 5 million euros. A consortium of multiple partners is likely required due to the nature of the research topics, which demand diverse expertise in areas such as safety, legal, regulatory, and technological advancements in air traffic services.

Research projects should explore key areas including the evolution of human roles in automated systems, human operator fatigue, methodologies for ensuring safety of air traffic management systems, and the harmonization of airspace classifications. The projects are intended to collect scientific data that can inform future regulations and practices in air traffic management and navigation services, contributing to innovations in safety, efficiency, and sustainability.

No co-funding is required, and the overall budget for this initiative totals 24 million euros, divided into work areas with varying funding ranges. The maximum project duration is set at 30 months, which includes time for communication and dissemination of results. Grants must adhere to specific dissemination obligations to ensure findings are shared and made accessible for reuse. Proposals are encouraged to align with existing guidelines and documents provided by the funding framework.

In summary, this grant supports exploratory research to develop regulations for the Digital European Sky, inviting applications from a broad range of organizations primarily based in the EU. The goal is to enhance the safety and efficiency of air traffic management through innovative research and the integration of advanced technologies and practices.

This is a call for proposals under the HORIZON Call Digital European Sky Exploratory Research 03 (HORIZON-SESAR-2025-DES-ER-03). It is a HORIZON JU Research and Innovation Action (HORIZON-JU-RIA) with a HORIZON Lump Sum Grant [HORIZON-AG-LS] Multi-annual Grant Agreement. The call is currently open for submission with a single-stage deadline model. The opening date was April 1, 2025, and the deadline for submission is September 16, 2025, at 17:00:00 Brussels time.

The expected outcome of this call is to significantly advance research to help shape the future regulatory framework for a Digital European Sky, specifically addressing development priority AR-1. The intended outcomes include:

Support the evolution of the future regulatory framework by addressing the impact of automation on the human role, and providing insights into the challenges and potential solutions for designing both AI and non-AI based automation tools.

Contribute to a harmonized application of airspace classifications across Europe.

Improve Air Traffic Management (ATM) safety by developing applications of Data4Safety.

There is a specific requirement that research activities carried out under this topic should always duly consider and assess the potential impact of the proposed regulatory evolutions on military aviation, in particular military operations and training.

The scope of the call includes the following research areas:

1. Evolution of the human operator role and automation:

This area focuses on the technological evolution envisioned in the ATM Master Plan and the EASA AI Roadmap, where human operators delegate tasks to automation, forming a human-machine team. The research requires a multidisciplinary approach, involving safety, human performance, legal, insurance, and regulatory expertise, and should be use-case driven. The goal is to assess the evolution of the human operator role and automation, not to develop a fully automated ATM solution. Research should develop a state of the art of the Human Factors (HF) impact on automation and mitigation methods applicable in ATM, and propose standardized measurement methods to quantify adverse impacts.

Specific aims include identifying and analyzing:

The impact of technological evolution on human operators' tasks, competencies, and performance.

Potential safety hazards related to the transition to an evolved human operator role.

The potential loss of sense of control by the human operator due to future technological developments.

Research should also explore solutions to reduce the risk of drowsiness, such as reducing or increasing automation, and consider meta-analyses, assessment of mitigation methods, and standardizing procedures. The research should complement the EASA ATCO Fatigue study and the EASA AI Roadmap, and aim to provide factual scientific data for intervention strategies related to human operator training, competence, and fatigue management. The output of the research will support impact assessment and future decision-making by EASA on regulatory needs.

2. Research on human operator fatigue and rostering practices:

This area aims to increase knowledge and scientific evidence on human operator fatigue prevalence, causes, effects, and effective prevention and mitigation, supporting future decision-making by EASA. The research should consider the "Study on the Analysis, Prevention and Management of Air Traffic Controller Fatigue" published by EASA in May 2024.

Specific research topics include:

Extending scientific knowledge about the prevalence, causes, and impact of human operator fatigue through human-in-the-loop experiments.

Identifying and proposing recommended bracket values of roster elements to maintain the risk of human operator critical fatigue at a low to moderate level, considering traffic volumes, complexity, and seasonal activities.

Further research into the correlation and cross effects of mandatory parameters and the time needed to reduce critical fatigue risks.

Research on various national labor laws in the EU and their impact on rostering practices.

Identification of a methodology to calculate human operator staffing levels in ATSPs.

Investigating the impact of rostering schemes on work-life balance and human operator fatigue.

Collecting data on the actual content of working hours in EU ATSPs and confirming the share of operational and non-operational duties.

Assessing the impact of new technologies on fatigue.

Developing objective non-intrusive new fatigue monitoring technologies.

Providing recommendations for updating the SESAR human performance assessment methodology.

Proposals must define mechanisms for guaranteeing the absence of conflict of interests. The research results should aim to provide factual scientific data for intervention strategies in human operator fatigue management and working practices.

3. Methods to evaluate safety requirements of ATM/ANS ground equipment and determine appropriate assurance levels:

This area addresses the lack of harmonized methods for ensuring the safety and interoperability of ATM/ANS systems and constituents. Research should aim at providing data and information to determine:

Certification characteristics and performance of hardware platform cloud computing and Commercial Off-The-Shelf (COTS) solutions/equipment.

How best to ensure the suitability for use of COTS equipment or constituents.

Principles, assurance methods, and safety considerations to be applied in guaranteeing computing platform, virtual systems, and software applications provide their performance and safety targets.

A methodology applicable to ATM equipment to determine “failure conditions”.

Shared liability principles for assurance of certified equipment being used in a more highly automated operating environment.

Principles, methods, and safety considerations to determine software assurance level (SWAL) and hardware assurance level (HWAL).

The research results will support EASA rulemaking activities to further develop and complete the initial set of detailed specifications, enabling the application of appropriate safety requirements, harmonizing assurance methods, and clarifying the certification and declaration of ATM/ANS equipment. Research should consider ongoing standardization activities by international committees under EUROCAE WG 117 and WG 127.

4. The application of airspace classification in Single European Sky airspace:

This area focuses on the unharmonized application of airspace classification by Member States, which leads to flight inefficiencies, decreased safety, and differences in service expectations. Research should provide data and information to determine:

The distribution of the application of airspace classification in Member States airspace and the context of such application, particularly the implementation of class G airspace across Europe.

A reasoned framework (including a set of parameters based on traffic demand) to support a harmonized application of the airspace classifications.

The research should consider current traffic demand and future traffic forecast, considering VFR and IFR electric aircraft, as well as very low level (VLL) operations. The research should provide evidence and initial inputs to define an intervention strategy to define the classification application conditions in support of a Single European Sky.

5. Development of guidelines for the design of future artificial intelligence (AI) systems:

This area aims to support the evolution and update of EASA guidelines for the development of AI-enabled systems in ATM, including feedback on the effects of conformance, transparency, and complexity. Research should take as a starting point the issue 02 of the EASA AI concept paper.

Research should identify concrete applications of EASA guidelines and define appropriate activities, including human-in-the-loop simulations and new approaches for validation, verification, and testing of AI applications.

Close coordination with EASA is expected, particularly in areas such as:

Trustworthiness: Capability to keep AI-based systems with relatively high cyber-security protection.

Learning Assurance: Including the consideration of realistic operational cases in realistic operational conditions and new machine learning (ML) techniques.

AI explainability: Which goes beyond the ML techniques to extract information from the models and includes the interactions with other systems and with the human operators (human factors).

AI Safety case: Discussing with EASA and other safety experts about the needs and requirements of a concrete safety-case can help to clarify and support the development the EASA guidelines for certification.

The concept of safety critical levels needs to be further developed for AI applications in ATM. Research covers the definition and analysis of safety-related use cases for different safety level assurances.

Research should consider ongoing standardization activities by EUROCAE WG114 – SAE G34.

6. Enhancing robustness and reliability of machine learning (ML) applications:

This area aims at enhancing machine learning (ML) applications to ensure they are technically robust, accurate and reproducible, and able to deal with and inform about possible failures inaccuracies and errors. Research aims at developing potential solutions to address this challenge, which shall include/refer to the EASA methodologies for certification of AI in aviation. The research must be focused on the application of ML to ATM, by either leveraging existing ML techniques or by developing new ML techniques to address the specific challenges.

The scope may address:

Further the research on “generalisation capabilities of ML models and constituents”.

Verification methods of robustness for machine learning (ML) applications.

Standardised methods for evaluation of the operational performance of the machine learning (ML).

Application of transfer learning and data augmentation techniques for the development of the proposed applications, thus guaranteeing their robustness.

Identification, detection, and mitigation means of bias in ML applications.

ML/AI-based systems must be designed, deployed and executed while considering cyber-security aspects to prevent, detect, mitigate and respond to attacks and ensure that the system is cyber-resilient.

7. Support to the certification of novel ATM (AI-based and non-AI-based) systems that enable higher levels of automation:

The objective of this research element is to address issues related to the certification of:

Novel AI-based ATM systems that enable higher levels of automation (level 3 and above, which corresponds to EASA AI levels 2B and above).

Novel non-AI based ATM systems that enable higher levels of automation (level 3 and above).

Research will address solutions, methods, etc. that could support and harmonise certification of innovative ATM systems based or not on machine learning or artificial intelligence techniques (e.g., scenario-based testing, reinforcement learning for control systems, etc.). It is expected that proposals define a holistic approach to address this challenge considering not only technical aspects of the certification but also legal and regulatory aspects including privacy.

8. Development of a framework to achieve effective Human-AI Teaming:

Research aims at investigating concrete and feasible means of compliance for the new layer of Human Factors objectives and how compliance could be assessed including a definition of KPIs for performance in new roles for human, non-human, and hybrid teams. The research project could also lead to complement anticipated means of compliance for the Human-AI Teaming.

Research may include the creation of frameworks / methods for training AI-based systems together with humans, to be able to include in the objective functions notions of collaboration or KPI related to team success, and not only individual goals. The absence of standardised testbeds in AI-based ATM research fragments it and prevents truly collaboration between the research actions, even more so in the domain of Human-AI Teaming.

The research shall take as a starting point one or more use cases of application of automation level 2 to ATM that do not use AI and are already at a maturity level TRL6 or above and investigate the potential introduction of AI to enhance the performance of the Human-AI team.

9. Explainable Artificial Intelligences (XAI):

The objective of this research is to improve transparency of automated systems in the ATM domain investigating methods based on Explainable Artificial Intelligence (XAI) in operational use cases e.g., predicting air traffic conflict resolution and delay propagation, validating the robustness and transparency of the system, etc.

The research shall address the following aspects:

Elaborate a state of the art review to evaluate the progress made on XAI by several research groups (e.g., DEEL (dependable, explainable and embedded learning)).

Based on the state of the art review identify and develop further axes of research.

Investigate the “relevance property” highlighted in machine learning application approval (MLEAP) final report.

10. Innovative methodologies for ATM safety, security, and resilience:

Research aims at developing methodologies (or evolution of existing ones) for safety, security and resilience that will contribute to ensure that ATM is robust against ever-evolving risks, threats, and disruptive events in the physical and cyber worlds in a novel ecosystem (e.g., enabled by automation level 3 and above).

11. Applications of Data4Safety:

Research aims at defining, developing, validating, and assessing potential future applications / use cases of the data collected under Data4Safety Programme, which could be later integrated during the next stages of the D4S development phase. The goal is to improve the overall capacities of the European Union aviation system to manage risks and support data-driven changes with adapted aviation intelligence, by developing the capability to discover vulnerabilities in the system across terabytes of data.

12. Automation of the security risk assessment (SecRA) process:

Automating the security risk assessment (SecRA) process would assist organisations and authorities to meet the needs of Part-IS by easing the development of SecRAs while reducing the resources required.

13. Climate and environmentally driven route charging:

Research shall address the potential of climate and environmentally driven route charging, with new mechanisms for charging airspace users to incentivise minimum climate impact.

The total budget for this call is 24,000,000 EUR. The call is divided into two work areas:

WA1: Four topics with a total budget of 10,000,000 EUR, with individual contributions ranging from 500,000 to 1,000,000 EUR, and an indicative number of 1 grant per topic.

WA2: Two topics with a total budget of 14,000,000 EUR, with individual contributions ranging from 1,000,000 to 2,000,000 EUR, and an indicative number of 1 grant per topic.

The call specifies that eligible costs will take the form of a lump sum as defined in the Decision of 7 July 2021. Beneficiaries will be subject to additional dissemination and exploitation obligations, including proactive sharing of results, making results available for reuse, granting non-exclusive licenses for standardization purposes, and ensuring mutual access to background and results of linked actions. The maximum project duration is 30 months, including a 6-month period for communications, dissemination, and exploitation activities.

Applicants are encouraged to use the provided application form templates and guidance documents, including the Horizon Europe Programme Guide, Model Grant Agreements, SESAR 3 Project Handbook, and the Funding & Tenders Portal Online Manual. A SESAR 3 JU Call Helpdesk is available for inquiries. Partner search tools and information on National Contact Points and the Enterprise Europe Network are also provided to assist applicants.

In summary, this SESAR 3 Joint Undertaking call invites research proposals to shape the future regulatory framework for the Digital European Sky. It focuses on integrating human factors with increasing automation and AI in ATM, enhancing safety and security, harmonizing airspace classifications, and promoting environmentally sustainable practices. The call provides funding opportunities for research and innovation actions with a single-stage submission process and a lump sum grant agreement. The research should contribute to the evolution of the regulatory framework, improve ATM safety, and support the Single European Sky initiative.

Eligible Applicant Types: The eligible applicant types are not explicitly defined in the provided text. However, given the nature of the call as a "Research and Innovation Action" (RIA) under Horizon Europe, eligible applicants would typically include universities, research institutes, SMEs, large enterprises, and other organizations capable of conducting research and development activities. Air Navigation Service Providers (ANSPs) and Air Traffic Service Providers (ATSPs) are also implied as potential applicants.

Funding Type: The funding type is a grant, specifically a "HORIZON Lump Sum Grant" under the Horizon Europe Programme. This implies that beneficiaries will receive a lump sum contribution to cover eligible costs.

Consortium Requirement: The text does not explicitly state whether a single applicant or a consortium is required. However, given the multidisciplinary nature of the research topics and the need for diverse expertise (safety, human performance, legal, insurance, regulatory, etc.), it is highly likely that a consortium of multiple applicants would be more competitive. The partner search announcements also suggest that consortia are expected.

Beneficiary Scope (Geographic Eligibility): The geographic eligibility is primarily focused on EU member states and associated countries, as this is a Horizon Europe program. The text mentions that "A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects," indicating that some third-country participation is possible, subject to specific provisions outlined in the Horizon Europe Programme Guide.

Target Sector: The primary target sector is aviation, specifically air traffic management (ATM) and air navigation services (ANS). The call also targets related areas such as artificial intelligence (AI), machine learning (ML), cybersecurity, human factors, safety, security, and environmental sustainability within the aviation context.

Mentioned Countries: The text refers to "Member States" in the context of the application of airspace classification, implying that the call is primarily targeted at EU member states. The reference to "non-EU/non-Associated Countries" suggests that other countries may be eligible under specific conditions.

Project Stage: The expected maturity of the project is research and innovation actions. The call aims to support research activities that will generate factual scientific data, develop methodologies, and provide evidence-based recommendations for future regulatory frameworks. The projects should support the evolution of the regulatory framework, design of AI and non-AI based automation tools, harmonized application of airspace classifications, and improved ATM safety. The call also mentions use cases at TRL6 or above for Human-AI Teaming.

Funding Amount: The funding ranges vary depending on the specific topic. For HORIZON-SESAR-2025-DES-ER-03-WA1-1, -2, -3 and -4, the contributions range from 500,000 to 1,000,000 EUR. For HORIZON-SESAR-2025-DES-ER-03-WA2-1 and -2, the contributions range from 1,000,000 to 2,000,000 EUR.

Application Type: The application type is an open call, with a single-stage submission process.

Nature of Support: The beneficiaries will receive money in the form of a lump sum grant.

Application Stages: The application process involves a single stage.

Success Rates: The success rates are not explicitly mentioned in the text.

Co-funding Requirement: The text does not explicitly mention a co-funding requirement. However, as this is a Horizon Europe program, it is possible that some level of co-funding may be required, depending on the specific rules and conditions of the call.

Summary: This is a Horizon Europe call for proposals under the SESAR 3 Joint Undertaking, focusing on exploratory research to shape the future regulatory framework for a Digital European Sky. The call aims to support research and innovation actions (RIA) that address key challenges in air traffic management (ATM) and air navigation services (ANS), including the evolution of the human operator role in highly automated systems, human operator fatigue and rostering practices, safety requirements for ATM/ANS ground equipment, airspace classification, the design of AI systems, the robustness and reliability of machine learning applications, the certification of novel ATM systems, the development of a framework for effective Human-AI Teaming, explainable artificial intelligence (XAI), innovative methodologies for ATM safety, security, and resilience, applications of Data4Safety, automation of security risk assessment, and climate-driven route charging. The call is open to a wide range of applicants, including universities, research institutes, SMEs, and large enterprises, primarily from EU member states and associated countries. The funding is provided as a lump sum grant, with contributions ranging from 500,000 to 2,000,000 EUR, depending on the specific topic. The application process involves a single stage, with a deadline of September 16, 2025. The maximum project duration is 30 months. The research activities should consider the potential impact of proposed regulatory evolutions on military aviation.