AISA - AI Situational Awareness Foundation for Advancing Automation

To implement advanced automation, AI and human need to be able to share situational awareness. Therefore, AISA project is exploring the effect of, and opportunities for, distributed human-machine situational awareness in en-route ATC operations. The project is developing an intelligent situationally-aware system by combining machine learning with reasoning engine.

MAHALO - Modern ATM via Human/Automation Learning Optimisation

To answer the question if automation should match human behaviour or be understandable to humans, MAHALO aims to develop an individually-tuned ML system to solve ATC conflicts and couple this to an enhanced en-route CD&R display. Insights will be used to define a framework to guide design of future AI systems.

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TAPAS -Towards an Automated and exPlainable ATM System

TAPAS aims to explore highly automated AI-based scenarios through analysis and experimental activities applying eXplainable Artificial Intelligence (XAI) and Visual Analytics, in order to derive general principles of transparency which pave the way for the application of AI technologies in ATM environments, enabling higher levels of automation.

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AICHAIN – A Platform for Privacy-preserving Federated Machine Learning using Blockchain to enable Operational Improvements in ATM

AICHAIN proposes an innovative Digital

Information Management concept combining federated machine learning (FedML) and Blockchain technologies. This enables the cyber-secured exploitation of large private data sets by an privacy-preserving federated learning architecture in which neither the training data nor the training model need to be exposed.

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ALARM aims to develop a prototype global multi-hazard monitoring and early warning system (EWS).

A global multi-hazard monitoring means near-real time and continuous global Earth observations from satellite,

with the objective to generate prompt alerts of natural hazards affecting ATM and to provide information for enhancing situational awareness and providing resilience in crisis.

CREATE - Innovative operations and climate and weather models to improve ATM resilience and reduce impacts

Air operations largely use weather information to make the air traffic flow safe, continuous and efficient. As climate changes are ongoing, available information on the weather on short and longer notice are increasing and technology is being improved. CREATE aims to achieve innovative procedures in ATM to reduce climate and environmental impact, while becoming more resilient to weather phenomena.

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DYNCAT - Dynamic Configuration Adjustment in the TMA

DYNCAT aims to enable more environmentally friendly and more predictable flight profiles in the TMA, namely on approach, by supporting the pilots in configuration management.

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FlyATM4E - Flying Air Traffic Management for the benefit of environment and climate

FlyATM4E aims to expand approved climate-assessment methods and optimization of aircraft trajectories to identify promising mitigation options suitable to solve the task of reducing overall climate impact of aircraft operations. The project will assess the feasibility of a concept for environmental assessment of ATM operations working towards environmental optimisation of air traffic operations.

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FMPMet - Meteorological uncertainty management for Flow Management Positions

FMPMet aims to integrate meteorological forecast uncertainty information into the decision-making process for flow management position (FMP). FMPMet aims to provide the FMP with an intuitive and interpretable probabilistic assessment of the impact of convective weather on the operations, up to 8 hours in advance.

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SINOPTICA - Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM

SINOPTICA aims to explore the potential of assimilating remote sensing, GNSS-derived datasets and in situ weather stations data into very high-resolution, very short-range numerical weather forecasts to provide improved prediction of extreme weather events to the benefit of ATM operations.

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SIMBAD aims to develop and evaluate a set of machine learning approaches aimed at providing state of-the-art ATM microsimulation models with the level of reliability, tractability and interpretability required to effectively support performance evaluation at ECAC level.  The project will demonstrate and evaluate the newly developed methods and tools through a set of case studies.

Maintaining safety and cost-efficiency of air transport operations while increasing the capacity will push the next generation of ATM systems towards digitalisation.

In the mid-term, a digitalised system in the human operated ATM environment will be capable of delivering reliable predictive analytics based on automated information processing.

SafeOPS aims to support these future services by investigating the use of big data analytics together with new risk assessment methodologies.

FARO - saFety And Resilience guidelines for aviatiOn

FARO aims to bring new insights about safety and resilience in ATM, with four objectives: to exploit existing safety knowledge, to quantify the impact of increasing automation on ATM safety, to analyse the impact of increasing automation on ATM resilience, and to provide design guidelines and identify future research needs.

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BEACON - Behavioural Economics for ATM Concepts

BEACON aims to study the feasibility of extending user-driven prioritisation process (UDPP) to allow multi-prioritisation processes in the airspace and exchange of slots between airlines. It will build two models: a strategic model and a detailed tactical simulator. To properly capture the agents' behaviours, BEACON will make use of behavioural economics.

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ITACA - Incentivising Technology Adoption for Accelerating Change in ATM

ITACA aims to accelerate the development, adoption and deployment of new technologies in ATM. ITACA will develop a new set of methodologies and tools enabling the rigorous and comprehensive assessment of policies and regulations aimed at amplifying the uptake of new technologies within ATM.

Modus - Modelling and assessing the role of air transport in an integrated, intermodal transport system

Modus analyses the performance of the overall transport system by considering the entire door-to-door journey holistically. The project identifies (future) drivers for passenger demand and supply and assesses the impact on airside and landside processes and capacities. Based on these analyses, potential solutions to meet high-level European transport objectives are proposed.

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TRANSIT - Travel Information Management for Seamless Intermodal Transport

TRANSIT aims to develop a set of multimodal key performance indicators (KPIs), mobility data analysis methods and transport simulation tools, allowing the evaluation of the impact of innovative intermodal transport solutions on the quality, efficiency and resilience of the door-to-door passenger journey.

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X-TEAM D2D - eXTEnded AtM for Door2Door travel

X-TEAM D2D aims to define, develop and initially validate a concept of operations for the seamless integration of ATM and Air Transport into an overall intermodal network, including other available transportation means (surface, water), to enable the door-to-door connectivity, in up to 4 hours, between any location in Europe.

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NewSense aims to improve safety and efficiency of operations primarily in secondary airports with innovative low-cost surface surveillance solutions, based on 5G cellular networks for the long term, and msafmWave radar for the medium term, allowing the implementation of affordable Advanced-Surface Movement Guidance and Control Systems (A-SMGCS).

SINAPSE - Software defined networking architecture augmented with Artificial Intelligence to improve aeronautical communications performance, security and efficiency

SINAPSE aims to propose an intelligent and secured aeronautical datalink communications network architecture design, based on the software defined networking (SDN) architecture model augmented with Artificial Intelligence (AI) to predict and prevent safety services outages, to optimize available network resources and to implement cybersecurity functions protecting the network against digital attacks.

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CADENZA - Advanced Capacity and Demand Management for European Network Performance Optimization

CADENZA aims to develop a detailed trajectory broker concept for the European network, incorporating advanced demand-capacity balancing mechanisms. The trajectory broker will balance capacity and demand through a coordinated capacity provision process and collaborative trajectory management (including a novel trajectory charging scheme). Significant improvements in cost-efficiency and delay are expected.

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ISOBAR - Artificial Intelligence Solutions to Meteo-Based DCB Imbalances for Network Operations Planning

ISOBAR aims at the provision of a service- and AI-based Network Operations Plan, by integrating enhanced convective weather forecasts for predicting imbalances between capacity and demand and exploiting AI to select mitigation measures at local and network level in a collaborative ATFCM operations paradigm.

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START - a Stable and resilient ATM by integrating Robust airline operations into the network

START aims to develop, implement, and validate optimisation algorithms for robust airline operations that result in stable and resilient ATM performance even in disturbed scenarios The main focus of the project is the optimization of conventional traffic situations while considering disruptive weather events such as thunderstorms.

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NOSTROMO - Next-Generation Open-Source Tools for ATM Performance Modelling and Optimisation

The ATM system is composed of elements that interact with each other generating a number of properties characteristic of complex adaptive systems. NOSTROMO aims to develop new approaches to ATM performance modelling able to reconcile model transparency, computational tractability and ease of use with the necessary sophistication required for a realistic representation of the ATM system.

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INVIRCAT - IFR RPAS Control in Airports and TMA

INVIRCAT aims to create a concept of operations for remotely piloted aircraft systems in the terminal manoeuvring area of airports, assessing it through simulations and draft a set of recommendations for rulemakers and standardisation bodies.

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SAFELAND - SAFE LANDing through enhanced ground support

SAFELAND aims to support flight and landing of aircraft operated by a single pilot, in case of partial or total incapacitation of the pilot. SAFELAND will focus on the ground side, specifically on the role ATM could have in managing the transition from a single pilot operated flight to a status with reduced or absent contribution of the onboard pilot to landing.

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URClearED - A Unified Integrated Remain Well Clear Concept in Airspace D-G Class

URClearED aims to support current study activities on the RWC functionalities by defining and analysing operational scenarios, which allow to assess requirements and assumptions made in current standards and applicable documents, and then paving the way to future industrial level activities on such system.

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USEPE aims to research on drones’ separation methods in high demanding environments such as cities, and on the use of machine learning algorithms to automate the safe separation and deconfliction of drones, while maintaining airspace capacity in different environments. The research approach will take into account both the strategic and tactical flight phases.

Web: www.sesarju.eu/projects/USEPE

BUBBLES - Defining the BUilding Basic BLocks for a U-Space SEparation Management Service

BUBBLES aims to formulate and validate the concept of a U-space advanced (U3) ‘separation management service’. It will develop algorithms to compute the collision risk of UAS, allowing to define separation minima and methods, so that a safety level stated in terms of overall probability of collision can be defined and maintained.

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DACUS - Demand and Capacity Optimisation in U-space

DACUS aims to develop a service-oriented demand and capacity balancing (DCB) process for drone traffic management. This overall objective responds to an operational and technical need in European drone operations for a tangible solution integrating the functionalities of the SESAR U-space services for traffic management to produce timely, efficient and safe decisions.

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ICARUS - Integrated Common Altitude Reference system for U-Space

ICARUS aims to propose an innovative solution to the challenge of the common altitude reference inside very low-level (VLL) airspaces with the definition of a new U-space service and its validation in a real operational environment.

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ASPRID aims to assess the problem of protecting the airport operations from drone intrusion (careless or malicious) under a holistic and operationally oriented approach.  The project proposes to investigate vulnerability of airport under the different types of threat and possible ways of response as well as to study the interrelations between all those aspects involving different scenarios.

AEON aims at defining a concept of operations focusing on engine-off taxiing techniques, and a set of dedicated tools to support the operators. The project defines how to determine, in real time, efficient and conflict-free routing plans for autonomous and non-autonomous aircraft taxiing from gates to the corresponding runways and the other way around.

IMHOTEP aims to develop a concept of operations and a set of data analysis methods, predictive models and decision support tools that allow information sharing, common situational awareness and real-time collaborative decision-making between airports and ground transport stakeholders.

ECHO aims to deliver a comprehensive demand analysis and innovative and feasible concept of operations enabling near term and future Higher Airspace operations in a safe and orderly manner. The higher airspace including the operators forms a new, almost legacy free environment enabling an expeditions uptake of innovations or extrapolated SESAR solutions.

HAAWAII aims to research and develop a reliable, error resilient and adaptable solution to automatically transcribe voice commands issued by both air-traffic controllers and pilots, and to perform proof-of-concept trials in challenging environments. Also, the objectively estimated controllers’ workload utilising digitised voice recordings of the complex London TMA will be assessed.