Technology Challenges in Air Traffic Management Competition
The two best solutions will win 60,000 €
Call for applications open from April 6th until May 31st 2026
Sign up for the Infoday on Monday 19 May at 11:30
What is the Technology Challenges in Air Traffic Management Competition?
ENAIRE launches the 5th edition of the Technology Challenges in Air Traffic Management Competition.
The competition is open to university research groups or any other type of groups.
Technological solutions applicable to any sector of activity are admitted, as long as they are focused on the provision of air traffic/air transport services.
Challenges
Technological challenges within the framework of open innovation in air traffic management (ATM) are defined as those unresolved problems or needs within the ATM ecosystem itself. To address these, we seek solutions that are based on technologies or knowledge developed in other fields, as well as within the ATM field itself, provided they offer novel approaches and have not previously been explored in existing initiatives.
It is for this reason that the technological challenges defined in this competition are cross-cutting in nature and aim to harness the knowledge and experience gained in other technological areas for use within the ATM environment.
In this context, the competition is not aimed at identifying fully developed or deployment-ready products or solutions, but rather at proposals with clear application potential that require a process of maturation, adaptation and validation within the ATM environment.
The ultimate objective is to advance this maturation process through a research agreement, enabling the proposals to evolve into outcomes such as functional prototypes, proof-of-concepts validated in representative environments, models adapted to the ATM context, or technology demonstrators that reduce uncertainty regarding their technical and operational viability.
Solutions (total or partial) are accepted for the following 4 challenges:
CERTIFIABLE AI
The incorporation of Artificial Intelligence (AI) in Air Traffic Management (ATM) opens up new possibilities to improve the efficiency, safety and capacity of systems. However, to ensure their safe and reliable implementation, it is essential to establish a certification framework that validates these solutions from development to operational deployment.
Problem/need
The introduction of Artificial Intelligence (AI)-based systems into ATM presents a critical challenge: their integration into a highly regulated environment, where any change must guarantee very high standards of safety, traceability and reliability.
In ATM, automated decisions can have a direct impact on operational safety and must be understandable, verifiable and justifiable to both human operators and certification authorities. However, many current AI techniques have limitations in terms of explainability, validation and behaviour in unforeseen situations.
Furthermore, current ATM certification processes are not fully adapted to the characteristics of AI-based systems, which hinders their transition from experimental phases to use in operational environments. This creates a gap between the available technological potential and its actual applicability in the ATM context.
Approach sought
We are looking for approaches that will improve the auditability, traceability and validation of AI-based systems in critical environments. Particular consideration will be given to approaches drawn from other sectors where the certification of complex systems is already well advanced (automotive, healthcare, energy, etc.), as well as new methodologies that enable this challenge to be tackled from non-traditional perspectives.
Expected results
Development of frameworks, methodologies, prototypes or validation environments to facilitate the progressive certification of AI systems in ATM.
HUMAN OVERSIGHT IN AUTOMATED SYSTEMS
The move toward highly automated systems in ATM poses the critical challenge of ensuring that human operators maintain effective control of the decisions made by the AI. Given that these systems can process large volumes of data and react in milliseconds, it is critical that operators understand their actions and have the ability to intervene when necessary. Without this real-time oversight, confidence in automation could be affected and operational safety compromised.
Problem/need
The evolution towards highly automated ATM environments presents a key challenge: ensuring that human operators retain effective and meaningful control over the systems, even when these make decisions autonomously and within very short timeframes, without losing situational awareness.
In the operational context of ATM, air traffic controllers must be able to quickly grasp the state of the system, interpret automated decisions and act immediately when necessary. However, increased automation can make this oversight difficult, particularly when systems use complex models or when information is not presented appropriately.
One of the associated risks is a loss of situational awareness or difficulty in intervening in a timely manner, which can compromise operational safety. At the same time, an excess of information or alerts can lead to cognitive overload, reducing the operator’s effectiveness at critical moments.
Approach sought
We are looking for solutions that improve operational transparency, understanding of automated decisions and the capacity for real-time human intervention. Innovative approaches to visualisation, human-machine interaction, dynamic adaptation of automation and cognitive load management will be welcomed, including those developed in other fields.
Expected results
Demonstrators or prototypes that enable the validation of new forms of human-machine interaction and monitoring in representative ATM environments.
RESILIENCE AND FAILURE IN AUTOMATION
Increasing automation in Air Traffic Management (ATM) promises to optimize the efficiency and safety of operations, but it also introduces greater dependence on advanced technological systems. In this context, any failure in automated systems can generate significant disruptions, compromising service continuity and operational safety.
Problem/need
The increasing automation in ATM is transforming the way services are delivered, boosting the system’s efficiency and capacity. However, this evolution also increases reliance on complex technological systems, introducing new risks associated with failures, performance degradation or unexpected behaviour.
In the ATM environment, even partial failures can have a significant impact, as they affect systems operating in real time and under strict security requirements. In such situations, the system must be able to continue operating safely under degraded conditions, maintaining service provision and preventing the failure from spreading.
One of the main challenges lies in managing the transition from a nominal state to a degraded one and, in particular, in the recovery to normal operating conditions. This transition involves not only technical aspects but also interaction with human operators, who must assume a greater level of control at critical moments without this leading to an unmanageable overload or a loss of situational awareness.
Approach sought
We are looking for solutions to improve fault detection, management and recovery in highly automated systems, including approaches based on resilience, dynamic adaptation and human-machine interaction. Particular consideration will be given to approaches developed in other sectors with high levels of automation that can be adapted to the ATM context.
Expected results
Prototypes, models or demonstrators that enable the validation of resilience and recovery strategies in environments representative of ATM.
DIGITAL ASSISTANT FOR AIR TRAFFIC CONTROLLERS
The increasing complexity of air traffic management requires advanced tools to optimize decision making and reduce the cognitive load on controllers. In this context, the development of a proactive digital assistant represents a key innovation to improve operational efficiency and safety, enabling smoother collaboration between the human operator and automated systems.
Problem/need
Air traffic management is a highly complex activity that requires real-time decision-making under conditions of high cognitive load. Air traffic controllers must process information, anticipate potential losses of separation between aircraft and manage dynamic situations, all whilst maintaining high safety standards.
Although support tools exist, many of them do not adapt dynamically to the operational context or the individual characteristics of the air traffic controller, which limits their effectiveness. Furthermore, the introduction of new capabilities based on artificial intelligence poses challenges relating to trust, usability and integration into the operational workflow.
One of the main challenges is to develop solutions that truly complement the operator, adding value without increasing the cognitive load or interfering with decision-making. Furthermore, any solution must be capable of operating in a highly regulated environment, where validation, transparency and user acceptance are key factors.
Approach sought
We are looking for solutions that provide advanced support for air traffic controllers’ decision-making, tailored to the operational context and the user. Innovative approaches to intelligent assistance, personalisation, interaction and adaptive learning will be welcomed, including those developed in other fields.
Expected results
Demonstrators or prototypes of assistance systems that can be evaluated in simulated environments or environments representative of ATM.
Phases of the competition
May 31st, 2026
May 31st, 2026
1. Presentation of proposed solutions
Deadline for submitting applications through the form available on this website.
July 31st, 2026
July 31st, 2026
2. Evaluation of proposed solutions
The Jury will pre-select the finalists.
August and September 2026
August and September 2026
3. Jury Interviews
The finalists will present their proposed solutions to the Jury.
September 10th, 2026
September 10th, 2026
4. Selection, notification and acceptance of the challenge
The Jury will inform the winning research groups.
end of 2026 – beginning of 2028
end of 2026 – beginning of 2028
5. Winning solution research and follow-up phase
From the date of acceptance of the challenge, each winning research group will sign a research agreement to begin work that will last 18 months.
Prize
The winning research groups will sign a research agreement with a duration of 18 months, having at their disposal an amount of 60,000 €, of which 40,000 € will be delivered in the year 2026 as an advance payment and 20,000 € in the year 2027 after the closing of the activities.
Unlike previous editions, in this edition an agreement will be signed for research in the scientific field of the winning project, which may be part of a doctoral thesis. The prize will be signed between two parties, CRIDA and the company or university that submitted the idea.
18 meses
Convenio de investigación
60.000 €
En 2 fases
18 months
Research agreement
60.000 €
In 2 phases
How to register?
To register for the competition, please complete the following steps:
- Download the rules of the competition and the registration form from the top of the website.
- Fill out the registration form and send it to the email address listed in the rules of the competition (or click here).
- Once you receive the confirmation email, you have successfully registered for the competition!
What is ENAIRE?
In Spain, all aircrafts that take off, land or transit through its airspace receive communications, navigation and surveillance services through a modern and complete network of facilities operated by ENAIRE.
In the following infographic they show how air traffic control services are provided, according to the phases of a flight.
Some of Enaire's areas of interest
Safe and smooth air traffic
Environmentally sustainable air traffic
Drone traffic integration
Airspace design and organization
Traffic demand and capacity balancing
Automation
Artificial intelligence
