The Air Transport System is a highly complex system of systems with a huge number of involved actors and many unpredictabile elements.
Understanding the cause-effect relationships between Air Traffic performance drivers and performance indicators constitutes a major, unresolved challenge. Policy makers have a very limited understanding of how the assignment of solutions and resources to respond to current and future ATM challenges will affect the network, and have little guidance in defining the right mechanisms to manage delay propagation, capacity limits, network congestion, and other phenomena.
As a single, globally connected, real-world system with millions of daily users, the Air Transport Network profoundly effects the competitiveness of economies, on businesses and on the passengers and delivery customers who rely on it. And it must be safe. Experimenting with approaches within the current system without having some understanding of potential outcomes is not practical. For this reason, establishing reliable and functional modeling and simulation is of paramount importance.
The main goal of the CASSIOPEIA project is to develop a theoretical framework and a demonstrative software platform that helps to understand the cause-effect relationships between Air Traffic performance drivers and performance indicators. In pursuit of this goal, a number of complimentary results are derived:
- Betterment of state-of-the-art in the field of Air Traffic System Performance Modeling
- Assistance to policy makers in making more informed decisions
- Betterment of state-of-the art in Complex Adaptive Systems
- The development of Complex System research in ATM
In order to cope with its objectives, the CASSIOPEIA project was structured into two main streams. First, a theoretical framework was developed providing a high level specification for the next stage, which is the software development. The developing phase not only included implementation, but also a careful analysis of requisites and design. Once both the theoretical framework and the agent base simulation platform were complete a set of three Case Studies were analysed in detail to demonstrate the potential application of these new techniques, encompassing different types of modeling challenges and techniques.