Mixed-Integer Nonlinear Programming (MINLP) deals with the most general optimization problems, involving both continuous and discrete variables and nonlinear constraint functions. These are among the most challenging computational optimization problems, arising in countless applications from various areas. While research on mixed-integer linear optimization is quite advanced, MINLP is considered an emerging area that is likely to grow in the coming years. MINLP models being in general very difficult to solve, they require exploiting their properties and developing special solution techniques to reduce the computational effort. The ATOMIC project is in the framework of this hot research topic, with the aim of contributing to the advancement in both modeling stimulating real-life problems and developing efficient methods for their solution. A number of challenging problems arising in Air Traffic Management (ATM) constitute interesting research topics particularly in Operations Research and Optimization and naturally lead to MINLP models. Air traffic is at the core of the social and economic dynamism of our society, and an efficient Air Traffic Management has evidently a deep impact on the social, economic, environmental and industrial context. In this framework, a few problems urgently need addressing to ensure a higher level of automation in ATM and consequently more efficiency and safety. The present project focuses on air traffic conflicts, which occur when aircraft are too close to each other according to their predicted trajectories. Mixed-Integer Nonlinear Programming formulations appear to be the natural candidates for these addressed ATM problems, where the need for modeling logical choices suggests the simultaneous presence of mixed (continuous-integer) variables and nonlinear constraints arise from separation condition modeling. Solution algorithms for these ATM problems are mainly based on evolutionary computation. While these methods are computationally efficient, the global optimal solution and even a feasible solution (with no conflict) is not guaranteed to be achieved in a given time. Recent advances in mixed-integer linear and nonlinear programming open new perspectives that have been lacking in earlier researches on conflict avoidance and can have an impact on its effective solution. The present project is therefore aimed to fully exploiting and developing mixed-integer optimization techniques to propose efficient solutions. The optimization will be performed developing specific strategies to deal with the computational difficulty of the target large-scale problems. Deterministic Branch-and-Bound (BB)-type methods (spatial-Branch-and-Bound and interval-Branch-and-Bound variants) will be primarily considered, exploring strategies that can have an impact on the algorithm's ability to provide an optimal solution, including for example strong reformulations and branching strategies. To deal with the difficulty of the problem, other strategies will be also explored, where the optimality guarantee is forsaken in exchange for the computational efficiency. Specifically, we will investigate hybridization of mathematical programming techniques and (meta)-heuristics, in a “matheuristic” framework, where an essential feature is the exploitation of the features of the conceived mathematical programming models of the addressed problem. Starting from the results obtained for the considered specific application, we will seek to identify more general classes of MINLP problems to which the developed techniques can be applied. Expected results of the project include new mathematical models from mixed-integer programming and effective optimization methods, as well as a software library implementing the proposed algorithms.

CICONIA’s ambition is to improve the understanding of non-CO2 emissions with regards to the current aircraft/engine technologies and operating fleet, as well as their evolution and their climate effects, but with the clear objective to evaluate and develop impact reduction solutions covering several promising mitigation options on flight operations, through the definition of innovative dedicated Concepts of Operations (CONOPS) and their assessment in comparison to legacy operations. CICONIA wants to define and assess CONOPS solutions with engagement from all concerned stakeholders: Airlines with their OCC, Network, Met providers and Air Traffic Control. CICONIA mitigation options will offer the best proposal for reduction in climate impacts, taking into account both, the CO2 and non-CO2 climate effects. A TRL4 is targeted at the end of the 3 years project. CICONIA is composed of the four main topics: 1. A weather service that will improve weather forecasting capabilities tailored for operational mitigation concepts, provide technical enablers definition and recommendation for long term improvement that will feed a better understanding of the stakes; 2. A climate enabler that will improve climate impact assessment and models tailored for operational mitigation concepts; 3. CONOPS strategies definition: CICONIA proposes to further analyse how operational stakeholders could integrate mitigations in their plan or in their tactical operations to mitigate climate impacts. A climate enhanced operations CONOPS will be delivered and assessed with representative fast time simulation platforms, integrating weather and climate models, enabling the evaluation of a large area and long time period. These simulations will support the assessment of the complete picture from climate, economics and operational impact points of view, conducting trades on different assumptions, understanding their impact on the decision making and finally providing guidance; 4. An ATM mitigation solution through trials: Investigate multiple ATM strategies for flights to minimise or avoid persistent warming contrails, through operational trials and data analysis. This solution will focus on reducing the climate impact of non-CO2 components, specifically by minimising crossings of persistent, highly warming contrails from aircraft in oceanic airspace. CICONIA aims as well at providing material to Authorities and Regulators, to analyse the appropriate rulemaking that could serve a fair and uniformed framework to minimise non-CO2 climate effects in a global environmental centric approach addressing as well CO2. Regulations aimed at mitigating non-CO2 effects through operational measures should be proven effective from a climate benefit standpoint, fair from an economic impact on the operator's standpoint, and operationally feasible/acceptable/manageable. An Advisory Board will federate external organisations who want to take part in the CICONIA results.

In numerous domains (aeronautics, medical, military, nuclear, command-and-control), visual activity is an essential element of the expertise. Therefor, eye tracking and the study of eye movements are omnipresent in neuroscience, psychology, industrial engineering, human factors, and computer science, to study the operator’s state. In addition to the comprehension of the attentional processes, the voluntary eye movements can be used for human-system interaction. Nevertheless, due to the lack of appropriate software and hardware, the use of the gaze-based interaction in real and virtual environments is for now mostly restricted to the research domain. Nowadays, the most used eye tracking technique is video-based tracking using infrared illumination. However, the tools using this technique present a certain number of disadvantages. Notably, for the head-mounted tools, such systems obstruct the visual field et therefore are not suitable for integration in real operational environnements. An alternative technique consists of measuring the changes in electric potential near the eye. The electro-oculography (EOG) requires only a few electrodes to place on the face and does not obstruct the visual field nor unnecessary illuminates the eyes with the infrared light. This technique is convenient for the head-mounted peripherals such as audio or virtual reality headset. The projet ELOCANS addresses this lack of software and hardware for gaze-based interaction in operational environments. In numerous activities such as air traffic control or piloting an aircraft, the operators are already equipped with peripherals (typically, headsets). We are looking to optimize the efficiency of these existing peripherals and integrate the EOG. By studying the EOG integration in these control/communication peripherals to enhance the human-system interaction and making possible the psycho-physiological monitoring (based on blink rate, for instance), this projects has numerous possible applications in aeronautics (fighters, helicopters, UAV operation), naval systems, and control-command centers. We aim to propose an alternative placement for the EOG electrodes that correspond to the available surfaces of the existing peripherals, to develop corresponding signal processing algorithms, to develop the interaction techniques and physiological monitoring algorithms for these devices. During the project, two prototypes will be considered for aeronautical and military domains: 1) an audio headset that integrated the eye tracking for applications in aeronautics and C2, 2) a plug-in for virtual reality headset for applications in industry and consumer marker but also for military training and UAV remote control.

Remote digital towers (RDT) are taking place around the world to ensure efficiency and safety. TRUSTY harnesses the power of artificial intelligence (AI) to enhance resilience, capacity, and efficiency in making significant advancements in the deployment of digital towers. The overall goal of TRUSTY is to provide adaptation in the level of transparency and explanation to enhance the trustworthiness of AI-powered decisions in the context of RDT. Through the video transmission data from RDT, TRUSTY considers the following major tasks: 1. Taxiway monitoring (i.e., bird hazard, presence of a drone, autonomous vehicle monitoring, human intrusion, etc.). 2. Runway monitoring (approach and landing) misalignment warning and the corresponding explanation. To deliver trustworthiness in an AI-powered intelligent system several approaches are considered: • ‘Self-explainable and Self-learning’ system for critical decision-making • ‘Transparent ML’ models incorporating interpretability, fairness, and accountability • ‘Interactive data visualization and HMI dashboard’ for smart and efficient decision support • ‘Adaptive level of explanation’ regarding the user's cognitive state. • “Human-centric AI” enhances the trustworthiness of AI-powered systems. • “Human-AI teaming” to consider users’ feedback to insure some computation flexibility and the users’ acceptability. To achieve the goal, TRUSTY will rely on the SotA developments in interactive data visualization, and user-centric explanation and on recent technological improvements in accuracy, robustness, interpretability, fairness, and accountability. We will apply information visualization techniques like visual analytics, data-driven storytelling, and immersive analytics in human-machine interactions (HMI). Thus, this project is at the crossroad of trustworthy AI, multi-model machine learning, active learning, and UX for human and AI model interaction.

Air-to-ground communication technology is at the heart of the end-to-end air traffic management concept, which requires the global integration of current, future, and emerging communication networks. The present ATMACA (Air Traffic Management and Communication over ATN/IPS) project addresses an innovative solution enabling effective, seamless, interoperable air-to-ground datalink communication technologies and digital flight monitoring and management environment through aeronautical telecommunication (ATN) based on internet protocol suite (IPS) within all domains of flight. In this frame, ATMACA project aims at supporting “air-ground integration and autonomy” innovation flagship in the Strategic Research and Innovation Agenda (SRIA) presenting the strategic roadmaps to achieve SESAR phase D “Digital European Sky” in European ATM Master Plan 2020 edition. ATMACA proposes a beyond the state-of-the-art IP-based datalink communication solution by introducing an application-layer mobility management for ATN and enabling commercial of-the-shelf equipment. It will also provide a next generation human machine interface (HMI) which will process higher quality data, enable interactions with the existing and future aeronautical applications and services, and meet the needs of end-users. ATMACA solution will be validated based on real-time simulations and real-time monitoring tests by considering relevant applicable SESAR key performance areas and indicators as well as industry standards. The consortium consists of a balanced mixed of universities and industrial partners (an air navigation service provider, an airline and a research and consultancy firm specialized in HMI design) to ensure the achievement of the project objectives. ATMACA project’s outcomes will deliver a robust and reliable communication and ATM solution serving as a baseline for the future ATN and next SESAR ATM solutions.