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Automation of Airport Operations

The scope of this topic covers the following aspects:

Application area 1: Advanced HMI interactions for tower controllers

This application area covers the development of new human machine interface (HMI) interaction modes and technologies in order to minimise the load and mental strain on the Tower controllers (especially under high traffic density situations, low visibility conditions, etc.).

The proposed applications shall go beyond or be complementary to those that are being addressed in Industrial Research (IR) solutions PJ.16-04 (Wave 1): multi-touch input (MTI) devices, use of in-air gestures, automatic speech recognition (ASR), attention guidance (AG), user profile management systems (UPMS) and use of virtual and augmented reality in different means and tracking labels. The output of PJ.16-04 is expected to be made public at the end of 2019; proposals for work in this area should plan effort to review this output and plan to incorporate it in their research if it is relevant. Note that it is expected that IR work continues as part of IR Wave 2 activities (Wave 2 candidate solution PJ.05-W2-97). Proposals should demonstrate how their work goes beyond the scope of the work planned for IR Wave 2 as described in the IR Wave 2 technical specifications.

Proposals must identify a specific improvement to operations and propose a plan to undertake its initial validation. The proposals must identify the technical enablers that are required for the proposed improvement. The work to be undertaken may include the development of the technical enabler, but cannot be limited to it, i.e. the research must include work towards the validation of how the enabler will be used. The operational validation needs to involve ATCOs.

The SJU has identified the following innovative HMI elements of interest:

  • The potential use of already developed technologies (e.g. for remote towers) in towered airports as well as the required adaptations to the specificities of these environments e.g. how to present to ATCOs tracking labels superimposed to their out-the-window view while avoiding information clutter;
  • The application of technologies in order to better integrate different information sources to reduce switching between head-up and head-down in the tower environment;
  • The potential application of emotion recognition, facial expressions, etc., in support of the optimization of human performance;
  • The integration of artificial intelligence (AI) and machine learning algorithms for the intelligent data provision to the controllers on the HMI (providing instead of “raw data”, information with context to ensure it is clear why data is being shown and what should be done based on the information presented, while avoiding information overflow). If addressing AI/machine learning, the research shall address the interaction, interplay, division, etc. of tasks and responsibility between ATCOs and algorithms as well as the deviations of ATCOs decisions from those suggested by the automated means e.g. AI.

The above list is not intended as prescriptive. Proposals for work in areas other than those listed above are welcome provided they include adequate background and justification.

Note that the proposed improvements may be applicable to current operations and/or to future operational concepts still under development by industrial research activities in SESAR.

The proposals must indicate the potential applicability of the proposed improvements in terms of categories of airports i.e. a given feature may be required for a major airport but not for a smaller one.

The proposals shall take into consideration relevant exploratory research projects such as MOTO, RETINA, etc.

Application area 2: Automation support to help flight crews on the airport surface

This application area addresses potential applications to improve the flight-crew performance during surface operations at the airport. In particular, this includes the development of on-board automation in support of a better integration with air traffic management for surface operations at the airports, such as:

  • Applications to inform the flight crew before the non-compliance takes place on the surface e.g. if approaching an intersection at high speed, etc. The warning/alert could be based upon different means e.g. input to aircraft controls, etc. Note that the aim of this application oriented concept is not conformance monitoring (covered in the following point);
  • Applications alert flight crews when they have deviated from ATC instructions (e.g. cleared route), from ATC procedures and/or from the airport configuration (AUO-0614 in the ATM Master Plan. This includes the autonomous generation of the appropriate conformance monitoring alerts by the on-board system on the basis of discrepancies detected between aircraft position and Airport Map Data Base and between aircraft position and clearances/instructions provided by ATC. Note that the ATM Master Plan operational improvement AUO-0614 is currently under research in IR by PJ3b, whose results are expected to be made publicly available at the end of 2019. Proposals for work in this area should explain how the proposed work would go beyond the IR scope, and plan effort to review the output of PJ3b and incorporate it in their work.
  • Enhanced arrival runway occupancy time thanks to efficient runway turn-off (AUO-0705 in the ATM Master Plan). The research shall address the combination of existing optimized braking to vacate solutions at a pre-selected runway exit with new applications for assisting the flight crew for achieving an efficient turn-off until aircraft has left runway protected area on the runway exit. This results in a reduced and more predictable arrival ROT. The expected reduced ROT and improved ROT predictability is relevant in good visibility conditions but it is even more so in low visibility conditions (especially in AUTO-LAND mode in CAT IIIb & c), where the observed arrival ROT is generally larger than in good visibility conditions. Proposals for work in this area must describe how they will go beyond previous SESAR 1 research in this area, referring in particular to the output of SESAR 1 project 06.08.02.The concept may be limited to the reduction, include an element of increased predictability of arrival ROT by ATC in the planning phase (e.g. equipped aircraft to indicate equipage or even prediction in seconds in flight plan), or even include an element of coordination with ATC in the execution phase (e.g. by aircraft downlinking predicted ROT to ATC around TOD or during the approach).
  • Enhanced departure runway occupancy time thanks to efficient line-up and take-off (AUO-0706 in the ATM Master Plan. The research shall address potential on-board applications to assist the flight crew of a departing aircraft for a more efficient (fast, accurate, reliable and safe) line-up and take-off. This optimised ROT, will result in a reduced and more predictable ROT at departure. The concept may be limited to the reduction of ROT, include an element of increased predictability of arrival ROT by ATC in the planning phase (e.g. equipped aircraft to indicate equipage or even prediction in seconds in flight plan), or even include an element of coordination with ATC in the execution phase (e.g. by aircraft downlinking predicted ROT to the tower ATC).
  • The integration of artificial intelligence (AI) and machine learning algorithms for the intelligent data provision to the flight crew (providing instead of “raw data”, information with context to ensure it is clear why data is being shown and what should be done based on the information presented, while avoiding information overflow) in support of reduced flight crew workload and increased safety during surface operations. If addressing AI/machine learning, the research shall address the interaction, interplay, division, etc. of tasks and responsibility between flight crew and algorithms as well as the deviations of flight crew decisions from those suggested by the automated means e.g. AI.

The above list is not intended as prescriptive. Proposals for work outside of these areas are welcome provided they include adequate justification and background.

The proposals shall assess the role of automation and its implications upon the role of the flight crew.

Application area 3: Automated apron and ground control

This research area aims at developing the operational concept for a highly automated apron management and manoeuvring area control at the airport. It shall address ground movement advisory service (apron) and/or control service (manoeuvring area). It is expected that clearance to enter/cross a runway, take off or land will still be delivered by a controller in all cases.

The research will work towards introducing a high-level of automation (corresponding to a Sheridan level of automation of 7 or more) for some or all of the following tasks:

  • Start-up approval;
  • Automatic push-back management;
  • Ground operations e.g. taxing, guidance from the gate to the runway, etc.; and/or
  • Detection of aircraft or vehicle movement, as well as of all other relevant objects, e.g. birds and debris on the runway, in order to ensure that the automation system has a situational awareness equivalent to o superior to what the human controller has in current operations, under all weather conditions, including low visibility;

The project may assume that the communication segment is solved by datalink or use voice communication (ATCO instructions sent using a combination of text-to-speech technology, pre-recorded messages, etc., and voice recognition to process incoming pilot communications). The research shall clearly identify their assumption in terms of datalink technologies and wireless communications.

The research must address fallback solutions in case of failure in the fully automated system. If the fallback requires human intervention, the relevant automation challenges must be considered (human-machine symbiosis).

The environment could be limited at small airports with less complex surface operations, and/or focused on airport with Remote Tower operations, but it could also be focused on increasing levels of automation at large airports (e.g. automatic start-up approval).

Proposals must explain how their research is positioned with respect to previous SESAR exploratory research projects in this domain MOTA, TACO and AUTOPACE, etc., but may choose a completely different approach provided they include adequate justification and background.

Airports remain one of the most significant bottlenecks in ATM. At capacity constrained airports, traffic demand can exceed the airport capacity (either at the runway, taxiway or apron) and, with the expected rapid growth in air traffic in the coming years, there will be an increasing number of capacity-constrained airports for significant periods of each day. This situation will become even more critical under adverse weather conditions. As a consequence, there is a need to find solutions to improve the efficiency of airport operations and their resilience in visually and/or challenging meteorological conditions. One of the potential areas of improvement aims at increasing the level of automation for supporting ATCOs and flight crews during the execution of their tasks. This would allow ATCOs to manage higher levels of airport throughput while at least keeping (if not improving) safety levels and to also allow flight crews to execute their tasks more efficiently. The research activities under this theme support of the Airports Council International (ACI) vision for the digital transformation of the airport business.

The proposed solutions under this sub-work area aim at:

  • Increasing airport capacity;
  • Improving cost efficiency (ATCO productivity);
  • Ensuring safety and security levels.