ATM application-oriented research for connected and automated ATM

Topic description

ExpectedOutcome:

Project results are expected to contribute to the following expected outcomes.

• Environment: the proposed solutions should have no negative impact on the environment (i.e. in terms of emissions, noise and/or local air quality) or on the potential improvement of the aviation environmental footprint;
• Capacity: the proposed solutions are expected to contribute to capacity by enhancing the management of separation minima, both for en-route airspace and the TMA, and the provision of additional meteorological services. At airport level, the solutions will enhance the calculation of arrival runway occupancy times and the resilience of runway throughput to meteorological disruptions, enhance departure queue management, improve visual separation procedures for the aerodrome circuit and support fully automated airport operations through improved predictability;
• Cost-efficiency: the proposed solutions are expected to justify the investment costs related to the adoption of automated technologies and tools;
• Safety: The proposed solutions are expected to maintain at least the same level of safety as the current ATM system, with higher levels of automation, especially through the identification of negotiation-based resolutions at conflict resolution and collision avoidance levels, safety nets for new separation modes and improved approach procedures into secondary airports in low-visibility conditions;
• Security: The proposed solutions are expected to identify and mitigate the potential security risks deriving from having a more interconnected and automated ATM system.

The challenge is to design and develop concrete innovative applications (that are already TRL1, achieved within SESAR programme or outside) that aim at increasing the level of automation and connectivity of the future ATM ground system and make these applications ready to transition towards industrial activities in future DES calls. The future architecture of the European sky will rely in an increased level of automation: the proposed innovative solutions shall aim at achieving between level 4 [Automation supports the human operator in information acquisition and exchange, information analysis, action selection and action implementation for all tasks/functions. Automation can initiate actions for most tasks. Adaptable/adaptive automation concepts support optimal socio-technical system performance] and level 5 [Automation performs all tasks/functions in all conditions. There is no human operator.] in all operating environments, including the transition areas between Europe and neighbouring ICAO regions, which may have specific regulations and challenges. Higher levels of automation are considered an essential enabler for increasing the performance of the ATM system, enabling numerous actors to interact with each other seamlessly, with fewer errors making the system scalable and even safer than today. Proposals may take up the challenge to develop innovative solutions for an affordable and service-oriented way of sharing trajectories across ATM actors, enabling the capacity, cost efficiency, operational efficiency and environmental performance ambitions of the European ATM Master Plan for controlled airspace and airports. To realise the SESAR vision, innovative solutions to increase the level of connectivity between all components of the ATM infrastructure will be required i.e. hyper connectivity between all stakeholders (vehicle-to-vehicle, vehicle-to-infrastructure) via high bandwidth, low-latency ground-based and satellite networks.

The SESAR 3 JU has identified the following innovative research elements that could be used to meet the challenge described above and achieve the expected outcomes. The list is not intended to be prescriptive; proposals for work on areas other than those listed below are welcome, provided they include adequate background and justification to ensure clear traceability with the R&I needs set out in the SRIA for the connected and automated ATM flagship:

• Increased automation in core En-Route/TMA ATC functions. The objective of this research element is to develop core functions of en-route/TMA ATC centres aiming at automation levels 4 / 5 (as per the ATM Master Plan). Research may propose operational concepts and concrete applications that will support the evolution of en-route/TMA ATC from executive to supervisory control (e.g. delegation of control to the automation). Research shall address the challenges on the role of the human to ensure that the proposed applications are fully consistent with human capabilities and the specific challenges that hinder the application of machine learning / artificial intelligence methods for the further automation of ATM (e.g. transparency, generalisation, etc.). Research shall take into account the recommendations provided by the “expert group on the human dimension of the Single European Sky”. Research may address the impact on the roles, the definition, responsibilities and tasks of the different actors e.g. ATCOs, FMPs, ATSEPs, supervisor, etc.), their training needs and other important aspects such as e.g., liability, certification aspects, etc. in an environment with higher levels of automation (R&I need: advanced separation management).
• Sector-less ATM. This research element aims at developing a sector-less concept, which considers all the entire upper airspace of the ECAC states as one single airspace and therefore, foresees the elimination of existing country boundaries and all sector boundaries within them. Research may evaluate the needs of advanced AI/ML-based tools (corresponding to automation levels 4 and/or 5) and the evolution of existing capabilities (e.g. evolution of the CWP HMI to consider larger airspaces, wide area communications, etc.) to support the concept in such wide area. Research may address how the concept will impact the current structure of the Air Navigation Service Providers (ANSPs), which will no longer be responsible for a specific national territory, but for aircraft flying across the entire ECAC airspace and explore potential alternatives to the conventional ANSPs (R&I need: advanced separation management).
• Evolution of flight-rule concepts, separation management service concepts and airspace classification. This element covers the potential evolution of responsibility for separation provision in an environment where advanced detect and avoid (DAA) and electronic conspicuity systems are fitted to majority – but not all - of participating traffic. Research should cover, individually and collectively, the role of the separator and the mode of separation provision; the need for and possible updates to or renewal of the airspace classification system; the definition and potential renewal of flight rules for manned and unmanned aircraft systems; and a potential review/qualification of the need for visual flight rules (VFR) flights to remain in visual meteorological conditions, including the need to remain clear of cloud, given the existence of advanced electronic systems that replace and/or augment the performance of the human eye. The research must assess the impact on all current airspace users, including main airlines, business aviation, general aviation, sports aviation and military aviation, as well as considering the impact on new entrants (both drones flying low and manned or unmanned aircraft systems flying at high altitude) (R&I need: advanced separation management).
• Use of advanced meteorological information and capabilities (R&I need: advanced separation management). This research covers the needs to:
  • incorporate ensemble weather information into decision support tools that can be adapted for different ATM stakeholders;
  • produce very high-resolution, very short-range weather forecasts using numerical weather prediction models and observational data assimilation;
  • share very short-range weather forecasts based on Aircraft Meteorological Data Relay and observational data assimilation (e.g., predicted wind, wind shear) during the approach and landing phases, Mode-S EHS, new possibilities emerging form ADS-C, etc. The research also covers the novel avionics and flight crew procedures required to use this information.
• Ionosphere gradients monitoring and Space Weather Forecast. This element covers monitoring and forecasting of ionospheric conditions to enhance GNSS positioning and improve the availability of augmentation systems (GBAS, SBAS) used in aviation. Most aircraft are equipped with GNSS receivers using GNSS position solution as an alternate surveillance tool in combination with other means (DME, VOR, NDB, INS, LDACS A-PNT, etc.). It is expected that, in the future, GNSS will be more frequently used for determining geometric altimetry as an alternative to barometric altimetry. Using data fusion technique, future ATM applications will combine data collected by the vehicle’s own sensors as well as ground- and space-based augmentation techniques (e.g., exploiting multi-constellation GNSS). However, GNSS signals may be disturbed, attenuated or even lost due to severe space weather activities with impact on the ionosphere. Monitoring and forecasting ionospheric conditions and gradients is therefore needed to calculate exact GNSS position for navigation as well as in the determination of geometric altimetry. Furthermore ionospheric gradient information is crucial to assess the availability of augmentation systems (GBAS, SBAS) used in aviation (R&I need: advanced separation management).
• Traffic allocation to arbitrary flight levels. This research aims at enabling aircraft to fly at any arbitrary flight level, as optimised by aircraft performance, weight and atmospheric conditions. Even/odd cruise level assignment should be based on traffic supply, rather than on the semi-circular rule (also known as the hemispheric rule). The results should enable the use of all flight levels in the European one-way ‘trunk routes’ concept (R&I need: advanced separation management).
• Evolution of separation minima. The scope of the research includes investigating advanced modes of separation (e.g. dynamic separation) based on predictive modelling and ML techniques and enabled by further automation and improved connectivity. In addition, the dynamic calculation of the necessary separation parameters between aircraft (horizontal and vertical) to meet a minimum acceptable safety level (i.e. moving away from pre-determined separation standards) for en-route and TMA airspace should be addressed. The separation minima to be developed include both minimum radar separation (MRS), which aims to keep the risk of collision sufficiently low to meet the target level of safety (TLS), and minimum wake separation (MWS), which aims to keep the risk of wake encounter sufficiently low to meet the TLS and potentially provide safety benefits. The separation to be applied in operations will always be the maximum of the applicable MRS and MWS. The operational improvement will also require combined separation minima and consideration of flight-specific data (R&I need: advanced separation management).
• Adaptation of ground and airborne safety nets to new separation modes. This element covers advanced separation management that will require close conformance monitoring of the negotiated and authorised flight trajectories throughout the execution phase, so that operations are not disturbed by unnecessary resolution advisories, in particular if lower separation minima are introduced/considered. Consideration of the level of independence of safety nets from other aspects of control will be critical, as the levels of autonomy automation of detection, classification, resolution and monitoring of conflicting profiles in the planning and tactical phases of ATM will significantly increase (R&I needs: integration of safety nets (ground and airborne) with the separation management function).
• Space-based multilateration. This element covers space-based multilateration through ranging by satellites already used for space-based VHF or ADS-B systems, with preference given to those used for space-based ADS-B, as this could serve to cross-check the GNSS position acquired through ADS-B (in the same way that Mode S radar has a double check). Research may cover the specific challenges for active and passive spaced-based multilateration (e.g., synchronization, interoperability analysis with ground systems, etc.). The development of an integrity parameter for space-based ADS-B downlink to ground system should also be covered. Research shall address how to integrate the space-based multilateration in the context of performance based communication and surveillance (PBCS) concept (R&I need: enabling the deployment of a performance-based CNS service offer).
• Use of dedicated 5G network for complex low altitude operations. Research addresses the potential use of a dedicated 5G network customized for complex low altitude operations (e.g., airports and their terminal areas, vertiports, logistic hubs, highly populated urban areas) supporting CNS requirements of safety critical applications. The potential solutions may be applicable to U-space, airports, vertiports, uncontrolled & controlled airspace with complex UAS and UAM operations. Research may address the possibility of sending local GNSS augmentation corrections through the 5G network. . Since the solution may be potentially very expensive, research shall address business case aspects considering that there are other potential alternatives e.g., LDACS. A coordinated approach with regulators and European institutions to overcome the issue that potential air traffic applications currently do not represent sufficient business motivation for network operators to implement additional features of 5G specs. Research shall consider the work done by GUTMA (Global UTM Association) and GSMA (GSM Association) to standardize some 5G protocols applicable to U-space (R&I need: enabling the deployment of a performance-based CNS service offer).
• Potential use cases and applications of LDACS for other airspace users (e.g., GA, U-space, Innovative Air Mobility). The objective is to research the potential application of LDACS datalink / voice infrastructure (delivered at TRL6 for schedule / business aircraft in industrial research) focused on other airspace users e.g., GA, U-space, etc. The research shall address the definition of operational use cases, which should also take into consideration U-space and Urban Air Mobility areas (R&I need: enabling the deployment of a performance-based CNS service offer).
• Alternate surveillance (A-SUR). Alternate surveillance builds on the idea that the position known by an aircraft through whatever means (e.g., GNSS, DME, VOR, NDB, INS, LDACS A-PNT, etc.) can be downlinked through whatever datalink is available (e.g., SATCOM, LDACS, VDLM2, Hyperconnected 4G/5G/LTE, Mode S, ADS-B, etc.) to be used as back up for surveillance. Therefore, on the ground it is made available in ASTERIX format in case the primary surveillance are not available. Alternative means of surveillance can be also explored (e.g., high-resolution video images, etc.). Research addresses:
  • The definition of initial performances that the alternative downlinks should have to comply with (within the context of PBCS framework);
  • The design of innovative data fusion and predictive algorithms (e.g. based on ML) to integrate very heterogeneous data sources;
  • The analysis of the integrity of the data in case of operational use.

Technical enablers, expected performances and architectures to include this data in the surveillance chain should be analysed. In addition, cost analysis for different alternatives for A-SUR should be part of the research (R&I need: enabling the deployment of a performance-based CNS service offer).

• Trajectory advisories. Research aims at developing automated applications that could provide trajectory advice (including uncertainty considerations and improved weather forecasts) to ATCOs either for human confirmation or for automatic implementation. This trajectory advice could consist of a ranked list of trajectory options based on different optimization criteria (e.g., optimising cost, minimising environmental impact, etc.). For elaborating these trajectory advisories, the automated application shall assure separation and consider a variety of other operational constraints (e.g., ad-hoc downstream and pilot requests or non-conformance, continuous descent and arrival management demands, downstream airspace availability and workload, AUs business needs and equity, the evolution of certainty over the prediction horizon, ATCO preferences and ensuring workflow integration and redundancy and safe degradation, etc.). Research includes the analysis on the uncertainty spread of airport take-off times, as those uncertainties ripple forward into the downstream ATC sectors, influencing significantly on any ATC related resolution and automation support tool. Research may use operational data and/or “intermediate” operational data (from demonstrations, shadow mode trials, simulations, etc.) to build a wide catalogue of non-nominal situations to help dimensioning the level of uncertainty at various operational stages and prediction look-ahead times (R&I need: network-wide synchronisation of trajectory information).
• Innovative applications for improving traffic synchronization. Research aims at developing innovative applications for queue management in ATM, thus optimising airport and TMA throughput and reducing the environmental impact of ATM. The data-integration between arrival and departure managers, A-CDM parties and TBS tools, to allow the dynamic optimisation of runway use based on prevailing operational needs is also under scope (R&I need: intelligent queue management). This may include the enhancement of:
  • Extended AMAN capabilities e.g. the transfer of the predicted arrival holding times from the TMA to the upstream airspace or airports to reduce holding, the use of ML and AI for the refinement of AMAN algorithms, the use of weather data, by taking into account more efficient spacing through incorporation of satellite-based navigation techniques (ABAS, SBAS, GBAS), etc. Regression algorithms could be used (e.g. state of the art techniques such as transformer-based networks) to reduce possible errors made in the AMAN algorithm, etc.;
  • Departure queue management e.g. through further automation and exchange of highly accurate trajectory information between all actors (i.e. airports, ANSPs and aircraft operators). ML and AI could be used (but not only) to monitor differences between DMAN sequences and their implementation, in order to improve DMAN sequencing algorithms, improve pre-tactical planning, etc. Classification and regression models could be implemented using the monitoring of the DMAN sequences to improve their accuracy;
  • Coupled AMAN–DMAN functions e.g. by using improved algorithms e.g. based on ML and AI techniques to identify the most appropriate departing aircraft to make use of an arrival gap. The integration with other airport systems will ensure that the departing aircraft is loaded in a timely manner and taxies to the right place at the right time to be ready to take off. Ranking models could be implemented to determine the best aircraft based on arrival gap, aircraft waiting time, and other environmental conditions.
• Automated provision of optimised trajectories during airport ground operations for all aircraft, vehicle drivers and tugs. This research addresses different optimization criteria e.g., delays, environmental impact, etc. for all aircraft, vehicle drivers and tugs during airport ground operations. The proposed solution should aim at providing optimised trajectories before the execution of taxiing operations, monitoring the executing of these operations, and re-planning when deviations from the initial plans are detected. Research includes the suitability of the multi-agent systems for degraded conditions too i.e., situations with low-visibility conditions, changing weather and weather extremes, etc., and its robustness when human roles are in the loop. Research shall take into account the output of project AEON (R&I: airport automation including runway and surface movement assistance for more predictable ground operations).
• Improved aircraft protection on the airport surface. Research focuses on the development of advanced capabilities to support the flight crew to protect the airframe and decrease collision risk with nearby mobiles or fixed obstacles when moving on the airport surface (e.g., thanks to radar system generating alerts when the aircraft is getting close to mobiles/obstacles). The airport moving map and ATSA-SURF might not be sufficient to prevent collision with nearby mobiles (e.g., A380 incident at John Fitzgerald Kennedy airport) or fixed obstacles (e.g., A380 incident at Le Bourget air show). Safety is improved as this will help to avoid common accidents on the airport surface that often cause serious damage to the aircraft wings. This will also avoid disturbances cause by aircraft incidents on the airport operations (R&I: airport automation including runway and surface movement assistance for more predictable ground operations).
• AOP and performance monitoring for a group of airports. Research address the development of a single AOP to address the needs of a group of airports with similar operational needs that are too small to have their own AOP. This AOP combines information from each individual airports in order to meet collaboratively agreed joint targets for the group of airports, but taking into consideration individual airport needs and situation. The coordination among airports should always align and never compete with the overall airport-network view. Research also address the collaborative process for the definition of performance targets agreed for any set of airports that decide to gather under such a common AOP. The wider neighbouring community will participate in this process. The benefit of joint target setting will be the ability to set more challenging targets for a group of airports than would be possible for a single airport, thus providing improved service to the Airspace Users over a range of KPA. The overall performance of the group of airports will be monitored against the shared performance targets. The performance of one single airport or the group of airports will be provided, suitably filtered to all the stakeholders (wide access to airport performance). When a group of airports (too small to have their own AOP) with similar operational needs have decided to gather under a single AOP, there is a need to set and monitor the performance targets in order to further enable performance optimisation. Research may include TMA aspects e.g., planning (R&I: airport automation including runway and surface movement assistance for more predictable ground operations).
• ATCO stress and fatigue risk assessment and ATCO resilience. An increased level of ATCO productivity will make it possible to manage traffic growth with the current level of resources, thus improving cost efficiency. However, stress and fatigue are physiological responses that have negative effect on ATCO performance and hence on safety. ATCO resilience is the ability for controller individuals to detect, resist or recover from suffering negative experiences such as stress and fatigue. Research on solutions to predict and monitor these negative effects not only in actual environments, but also in future highly automated environments are crucial to identify corrective measures such as adaptive automation. Historical data may be exploited to find models to assess and predict stress or fatigue (system interactions, reaction times, ATCO tasks, voice frequency, communications, etc.). It is also known that individual particularities such as ATCO chronotype, hours of sleep, accumulative high workload in different shifts, may affect differently to stress or fatigue reporting. Research is needed on how individual features can affect stress and fatigue and how these can be incorporated in their assessment. In addition, ATCO resilience against stress and fatigue should be improved. Resilience has been proven to be associated with some inherent traits of individuals: is positively correlated with conscientiousness, agreeableness, openness to experience and extraversion, and negatively correlated with neuroticism. On the other hand, the formation and improvement of individual resilience are considered as the dynamic process, which could be learned at any period of life. Resilience could be acquired over a period by using a process rather than coming all at once. Psychological coherence training and biofeedback training have proven to be an efficient method for ensuring individual detection and recover from fatigue and stress; as well as for achieving resilience quickly during the short breaks in long-time continuing monitoring and working (R&I need: Role of the Human).