Request for Proposals: Research to Help Shape the Future Regulatory Framework for a DES

Focus Areas

• This topic focuses on supporting the evolution of the future regulatory framework to facilitate the implementation of ATM Master Plan as well as the supporting actions identified in the European Plan for Aviation Safety (EPAS). For example: methods to evaluate performance of ATM/ANS ground equipment and determine appropriate assurance levels, the application of airspace classification in Single European Sky (SES) airspace, impact of automation on the air traffic controller regulations (e.g., licencing scheme, rostering, fatigue prevention), artificial intelligence (AI) assurance, human factors, and safety risk mitigation.

Scope

• Evolution of the human operator role and automation
  • The target vision presented in the ATM Master Plan and in the EASA artificial intelligence (AI) Roadmap entails a technological evolution that will transform the way air traffic services are provided: human operators will delegate a substantial number of tasks to the automation, and both together will form a human – machine teaming able to handle an increasing traffic demand more safely and efficientl
  • The research requires a multidisciplinary approach, involving safety, human performance, legal, insurance, regulatory, etc. expertise and shall be use-case driven. The objective of this research is not the development of an ATM solution with a high level of automation but, building on one or more ATM solutions (use-cases) proposing automation level 3 or 4 (human supervision or human safeguarding) based on conventional deterministic algorithms (i.e., not based on artificial intelligence) assess the evolution of the human operator role and automation
  • Research shall develop a thorough state of the art of the HF impact on automation and mitigation methods that are applicable in ATM and propose standardized measurement methods to quantify the adverse impacts.
• Research on human operator fatigue and rostering practices
  • The following research topics are proposed with the aim to further increase the knowledge and scientific evidence on human operator fatigue prevalence, causes and effects, and effective prevention and mitigation, and thereby support future decision-making by EASA. The research shall consider the “Study on the Analysis, Prevention and Management of Air Traffic Controller Fatigue” published by EASA in May 2024:
    • Extend the scientific knowledge about the prevalence, causes and impact of human operator fatigue including a varied and representative sample of EU ATSPs and human operators (e.g., human operators of the oldest age group) in human-in-the-loop experiments (e.g., using simulator(s) or a highly controlled operational environment).
    • Provide an updated assessment of current developments in fatigue detection technologies.
    • Develop objective non-intrusive new fatigue monitoring technologies (e.g., wireless electrode electroencephalogram (EEG), speech analysis and webcam-based eye tracking, etc.) to be used in the ATC operational environment. Research shall take into consideration ethical and data privacy issues, particularly in the context of general data protection regulation (GDPR) guidelines. Future developments in fatigue detection and/or monitoring should therefore address the balance between leveraging the benefits of advanced monitoring technologies and safeguarding individual privacy by integrating robust data protection measures, ensuring compliance with regulations, and addressing ethical considerations to gain acceptance within the ATC community. As these technologies continue to evolve, ongoing collaboration between researchers, technology developers, and regulatory bodies is strongly recommended.
    • Provide recommendations for the update of the SESAR human performance assessment methodology used by R&I projects in the SESAR programme to improve the consideration of fatigue at various stages of development and implementation of new technologies, including the assessment of the impact on fatigue of new concepts that make human operator role more passive/monotonous, for the manufacturers, the ATSPs and competent (oversight) authorities; in this regard assess the possible link with the Research project on the methods to evaluate the performance and impact of ATM/ANS ground equipment on human operator fatigue.
• Methods to evaluate safety requirements of ATM/ANS ground equipment and determine appropriate assurance levels
  • Research shall aim at providing data and information to determine:
    • Certification characteristics and performance of hardware platform cloud computing and 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 application of airspace classification in Single European Sky airspace
  • Through the application of SERA.6001 Classification of airspaces of the Annex to Regulation 923/2012, a common definition of the airspace classification has been implemented. However, the designation by the Member States has resulted is an unharmonized application which leads to flight inefficiencies, decreased safety and difference in service expectations when conducting operations in similar airspace within different Member States.
  • Research shall provide the data and information (including U-space implementation), to determine:
    • The distribution of the application of airspace classification in Member States airspace and the context of such application. The research must address in particular the implementation of class G airspace across Europe.
    • A reasoned framework (including a set of parameters based on traffic demand) to support a harmonised application of the airspace classifications.
• Development of guidelines for the design of future artificial intelligence (AI) systems
  • Research shall aim at supporting the evolution / update of EASA guidelines for the development of AI enabled systems in ATM, including feedback on the effects of conformance, transparency and complexity and other challenges associated to the design of future AI systems (e.g., tradeoffs between privacy and transparency, trustworthy AI approaches). Research shall take as starting point the issue 02 of the EASA AI concept paper.
• Enhancing robustness and reliability of machine learning (ML) applications
  • Research 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. Research shall consider the results and recommendations reported in the machine learning application approval (MLEAP) final report.
• 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).
• 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.
• Explainable Artificial Intelligences (XAI)
  • 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. The impact of inputs on outputs is an important consideration to promote when trying to explain complex models such as neural networks (NN). Similarly for control related applications (e.g., reinforcement learning), the “reachability property” from the same MLEAP report may also be of interest.
    • Despite the inherent case by case nature of compliance methods to explainability objectives, it is important to research a common baseline of methods/tools for specific groups of AI/ML applications (e.g., type of technology, type of application, dimensionality, etc.).
• 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). Moreover, research shall consider how novel virtualized and distributed ATM service architecture can be cyber-resilient and collaborate to enhance the overall security approach. New and disruptive technologies, operations, and business models to ensure ATM is resilient against internal and external threats, including health, natural disasters, terrorism, and criminal activity. Research shall ensure coordination with EASA. Research shall consider the work performed under projects SEC-AIRSPACE, FARO and FCDI.
• Applications of Data4Safety
  • Data4Safety (also known as D4S) is a data collection and analysis programme of the European Union Aviation Sector that will support the goal to ensure the highest common level of safety and environmental protection for the European aviation system.
  • 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.
  • The focus should be on the utilization of training data for ATM human operators and pilots in correlation with aviation data derived from in-service operations, rotorcraft, general aviation, and drones’ operations and in the field of environment
• Automation of the security risk assessment (SecRA) process
  • Security risk assessment is a resource-intensive, time-consuming process which incorporates the identification of assets, vulnerabilities, threats and threat scenarios, the evaluation of risk, and the selection of security controls to meet organisational security objectives. There is currently a global shortage of cybersecurity practitioners who can do this work, and this will remain the case for the next few years.
  • New European regulations (Part-IS) mandate information security management system (ISMS) requirements on aviation organisations and authorities, many of which have previously not been subject to such requirements and may not have implemented an ISMS or carried out security risk assessments in the past. The main objective of Part-IS is to address information security risks which may have an impact on safety, so mechanisms must also be in place to support the coordination of the aviation safety and security disciplines.
  • 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.
• 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. Route charging will reward those who avoid volumes of airspace with a high climate impact and disincentivise flight planning through high demand sectors / flight altitudes except where it optimises environmental benefit overall, while being cost neutral to airspace users and passengers on average. Added capacity in the “greener” volumes of airspace enabled by reduced vertical separations limits necessary flight plan modifications, furthering acceptance of the approach. Note that there is on-going work on this research element under projects Green-GEAR and AEROPLANE.

Funding Information

• Budget (EUR) – Year 2025: 14 000 000
• Contributions: 1000000 to 2000000
• The maximum project duration is 30 months, including a 6-month period at the end of the project life cycle to undertake communications, dissemination and exploitation activities in relation to the research results.

Expected Outcomes

• To significantly advance the following development priority:
  • AR-1 Research to help shape the future regulatory framework for a Digital European Sky. The expected outcomes are
  • Support the evolution of the future regulatory framework addressing the impact of automation on the human role, providing insight on the challenges and potential solutions to design AI and non-AI based automation tools.
  • Contribute to a harmonised application of airspace classifications in Europe.
  • Improve ATM safety developing applications of Data4Safety.

Specific requirement for this topic

• 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.

Eligibility Criteria

• Entities eligible to participate:
  • Entities eligible to participate Any legal entity, regardless of its place of establishment, including legal entities from nonassociated third countries or international organisations (including international European research organisations) is eligible to participate (whether it is eligible for funding or not), provided that the conditions laid down in the Horizon Europe Regulation have been met, along with any other conditions laid down in the specific call/topic.
  • A ‘legal entity’ means any natural or legal person created and recognised as such under national law, EU law or international law, which has legal personality and which may, acting in its own name, exercise rights and be subject to obligations, or an entity without legal personality .
• Entities eligible for funding :
  • To become a beneficiary, legal entities must be eligible for funding. To be eligible for funding, applicants must be established in one of the following countries:
    • the Member States of the European Union, including their outermost regions:
      • Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden.
    • the Overseas Countries and Territories (OCTs) linked to the Member States:
      • Aruba (NL), Bonaire (NL), Curação (NL), French Polynesia (FR), French Southern and Antarctic Territories (FR), Greenland (DK), New Caledonia (FR), Saba (NL), Saint Barthélemy (FR), Sint Eustatius (NL), Sint Maarten (NL), St. Pierre and Miquelon (FR), Wallis and Futuna Islands (FR).
    • countries associated to Horizon Europe;
      • Albania, Armenia, Bosnia and Herzegovina, Faroe Islands, Georgia, Iceland, Israel, Kosovo, Moldova, Montenegro, New Zealand, North Macedonia, Norway, Serbia, Tunisia, Türkiye, Ukraine, United Kingdom.

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