About Complexity Science
Complex Systems can be defined as the collection of a high number of parts (e.g. elements, individuals, agents) that interact in a nonlinear fashion. The system exhibits behaviours at the system-wide level that emerge from the combined actions of individuals within the system (emergent behaviour) and cannot be understood only from the information stored at the individual level. Such as floaks formed by birds. Complexity Research provides us with methodologies and tools aimed at understanding the mechanisms that govern such emergent behaviours, and to reduce their negative impact.
Complexity Science is not a single theory, but a highly interdisciplinary set of ideas that encompass methodologies and tools from different fields, including nonlinear dynamics, statistical physics and numerical simulation.
Complexity in the Air Transport Network
The air transport system contains a huge number of elements, or agents, that interact, in many situations nonlinearly, giving rise to emergent behaviours. System failures are usually a consequence of small and localized problems which spread across the entire network. Technical problems or adverse weather may generate delays at one airport, which then propagate to other airports and result in a major disruption in the European air transport network. In this kind of system, any external, but also internal, disturbance can lead the system beyond a critical point generating a major disruption.
In other words, the air transport system is a complex system. However, most efforts in air traffic modelling thus far have not taken into account this paradigm, and thus have failed to model emergent behaviour with a suitable treatment of the uncertainty. There is wide consensus within the ATM community that the state-of-the-art in ATM modelling still lacks useful macro-approaches able to capture system behaviour and explain high-level cause-effect relationships. Complex systems techniques can provide new insight into the understanding of these phenomena, focusing on interactions among elements, and help overcome some of the limitations of the current models.
ComplexWorld: bridging the gap
ComplexWorld will analyse the research on the applicability of state-of-the-art Complex Systems Science methodologies with the objective of advancing the understanding of ATM system behaviour, as a necessary step prior to improving its overall performance.
Modelling complexity will allow the operation of the system far from those conditions that raise unwanted behaviours, leading to a more rational allocation of resources and improving the benefits for airspace users and passengers.
In the ATM framework, the main challenges or the ComplexWorld Network will be to advance the following aspects of the system:
• Develop design principles that facilitate the introduction of changes in one or more subsystems, or the adaptation to external changes (agility).
• Study and understand its resilience to internal and external perturbations; its tolerance to faults; and the way such disturbances propagate through the system.
• Define concepts, solutions and architectures in favour of a more reliable system adaptation, as well as strategies for an intelligent healing of the ATM system of systems.
• Investigate the impact of uncertainty on overall system behaviour and understand how sensitive the system is to measure errors (e.g. position, speed), to the lack of precise data (e.g. wind, turbulence) or to the uncertainty introduced by certain phenomena that are intrinsically unpredictable.
• Build a true performance-driven ATM system, by allowing the development of a set of performance metrics that incorporate uncertainty as part of their definition.
• Consider the variability and non-determinism of human performance.
Discover our Wiki!
The ComplexWorld wiki aims to provide an alive platform to gather together the research results in the field of complexity science applied to air transport.