My main activity these last years revolved around Air Traffic Management. Using concepts from network theory, complex networks, agent-based modelling, and statistical tools like community detection I tried over the years to give another point of view on the Air Traffic Management.
Indeed, in 2013, around 27,000 flights every day crossed the European airspace. The smooth and safe handling of all these flights is guaranteed through Air Traffic Management
(ATM), which has three main tasks:
- Air traffic control: managing the movements of aircraft to prevent collisions;
- Airspace management: organising airspace so as to handle different types of air
activities, traffic volumes and resource needs;
- Flow and capacity management: prioritising aircraft to ensure an orderly flow.
This system has worked very well in the last decades but there is an emerging need for a fundamental change on how aircraft will be directed in the future. The European Commission initiated SESAR (Single European Sky ATM Research), which develops
a new ATM system to handle more traffic at a lower cost.
I was part of the project ELSA for most of its course. ELSA (EmpiricaLly grounded agent baSed model for the future ATM scenario) was a research project funded by SESAR which was developing an Agent-Based Model able to simulate the changes foreseen by SESAR to assess how much they would improve the ability of the ATM system to manage a larger number of aircraft with increased efficiency.
The project was in two parts. The first one was aiming at producing stylised facts which could then be used for the modelling. The second part of the project consisted in writing an Agent-Based Model able to give some insight about the future solutions envisioned by SESAR. The model was split in two, with a Strategic and a Tactical layer, able to work independently or in conjunction.
First part — Data Analysis and Community detection
Second part — Air Traffic Simulator
The members of ELSA were:
University of Palermo
Scuola Normale Superiore di Pisa