EMERGIA is a research project within the SESAR WP-E programme. EMERGIA investigates whether SESAR long-term concept of operations can take advantage of powerful emergent behavior identified within the iFly project. further information can be found in the EMERGIA website: http://emergia.nlr.nl
EMERGIA – Powerful Emergent Behaviour In ATM
Project consortium and contact information
Coordinator: National Aerospace Laboratory NLR, Amsterdam Contact: Prof. Dr. Ir. Henk Blom, e-mail: firstname.lastname@example.org
EMERGIA User Group members:
- Honeywell International s.r.o.
- NATS, UK
- NextGen Aerosciences, USA
Air Traffic Management (ATM) is a safety-critical complex socio-technical system which involves various types of emergent behaviour at multiple time scales. For current ATM, various types of uncertainties and positive emergent behaviour have been well embedded through decades of evolutionary development. In view of the kind of changes that are being foreseen in the SESAR concept of operations beyond 2020 architecture and design, significant changes in emergent behaviours are unavoidable. As long as these novel emergent behaviours are not understood it is very well possible that these have negative effects on ATM performance under various uncertainties. However, if emergent behaviour is identified and understood at architectural socio-technical system design level, then this understanding can be used to adapt the future ATM design such that emergent behaviours work in favour of future ATM. The EMERGIA project will identify potentially negative emergent behaviours of SESAR2020+, and subsequently will improve the SESAR2020+ system architecture and design such that their emergent behaviours become positive. This objective is accomplished by exploiting innovative complexity science techniques that have been developed during the last ten years through large European Commission research projects HYBRIDGE (2002-2005) and iFly (2007-2011).
Introduction and problem statement
The SESAR concept of operations beyond 2020 (SESAR2020+) involves a series of changes relative to the current ATM situation. Central to these changes is the paradigm shift that aircraft should fly according to agreed conflict free 4D trajectory plans which are made known to all actors involved as Reference Business Trajectories (RBT’s). The big unknown in this RBT framework is how everything works under various kinds of uncertainties, as a result of which one or more aircraft may not realize their RBT’s. There are several categories of uncertainties (including unexpected disturbances) that cannot be totally avoided, such as:
- Meteorological uncertainties;
- Data related uncertainties;
- Human related uncertainties;
- Technical systems related uncertainties.
In principle the SESAR2020+ ConOps has been designed to take care of these kinds of uncertainties through the possibility to revise 4D trajectory plans, and also to allow air traffic control to issue tactical flight instructions to pilots if the 4D planning layer has ran out of time. Although these tactical instructions are quite similar to the established way of working by an air traffic controller, there also are significant differences. Under SESAR2020+ an air traffic controller is expected to handle significantly more aircraft in its sector. Therefore the SESAR2020+ ConOps also foresees dedicated tactical decision support tools for air traffic controllers. The key issue is how to optimize the socio-technical collaboration between the 4D planning layer and the tactical layer in order to manage air traffic most effectively while taking into account the various uncertainties. In conventional ATM, medium term planning is provided by the planning controller, flight crews and their Flight Management Systems (FMS), whereas the tactical loop is formed by the tactical controller and flight crews. Thanks to decades of evolutionary developments, the collaboration between these two layers has been optimized. For SESAR2020+ a similar optimization of the novel 4D planning layer with the tactical layer is needed. Because the collaboration between these layers involves dynamic interactions between human decision makers, technical support systems, aircraft evolution, weather and other uncertainties, the combined effects result in types of emergent behaviours that cannot be predicted from the sum of the elemental behaviours. This can easily lead to negative emergent behaviours at time scales that remain invisible using established evaluation techniques.
During large European research projects HYBRIDGE and iFly, innovative complexity science techniques have been developed and applied to airborne self-separation concepts of operations. In order to understand and improve the emergent behaviours of SESAR2020+ at multiple time scales, the EMERGIA project will use these innovative complexity science techniques. This way EMERGIA aims to dramatically reduce the risks that negative emergent behaviours have to be repaired late at huge operational costs, and will shorten the period needed to optimize the system architecture and design of SESAR2020+. The most advanced airborne self-separation concept of operations studied within iFly, makes use of similar 4D planning and tactical layers as SESAR2020+, though fully airborne. Application of the innovative complexity science techniques to this advanced airborne-self separation has shown that its 4D planning and tactical layers work so well together that this leads to very powerful positive emergent behaviours, even beyond expectations of the concept developers. As a result of these powerful positive emergent behaviours, the advanced airborne self-separation concept considered can safely accommodate very high en route traffic demands. This raises the question how these powerful emergent behaviours can be maintained while moving the 4D planning layer and the tactical layer to the ground, as is the case with SESAR2020+. EMERGIA is expected to answer this research question.
The expected results of the EMERGIA project are that any potentially negative emergent behaviours of SESAR2020+ are identified, and that this information is used to improve the SESAR2020+ system architecture and design such that their emergent behaviours become positive. This is done by taking advantage of the iFly identified powerful emergent behaviour for an advanced airborne self-separation ConOps.
EMERGIA will address this research question in three steps. The first step is to use the innovative complexity science techniques to identify the emergent behaviours of SESAR2020+ at multiple time scales. The second step is to compare these emergent behaviours to the powerful positive emergent behaviours of the advanced airborne self-separation ConOps, and to learn improving SESAR2020+ in case of significant difference in emergent behaviours. The third step is to evaluate the improved SESAR2020+ ConOps on its emergent behaviours, again by using the innovative complexity science techniques.