A Privacy-Preserving Marketplace for Air Traffic Flow Management Slot Configuration

C. Schütz, E. Gringinger, N. Pilon, T. Lorünser
Schu21d (2021)
Proceedings of the 40th Digital Avionics Systems Conference (DASC 2021), San Antonio, Texas, USA, October 3-7, 2021, IEEE Press, ISBN 978-1-6654-3420-1/21, DOI: 10.1109/DASC52595.2021.9594401, 2021.
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Abstract (English)

In case of reduced capacity and congestion at an airport, flights are delayed, which means additional costs for the airlines. The amount of costs incurred by an airline differ between flights and depend on various factors, e.g., passenger compensation and costs for crew replacements. Some flights can wait longer than others before the delay causes significant additional costs. From a global perspective, it would be beneficial to prioritize the flights based on the incurred costs. Airlines, however, will be reluctant to share those costs. Therefore, we propose the SlotMachine system for flight prioritization that keeps confidential inputs from airlines private in an encrypted form that not even the system can read the costs. Using multiparty computation in combination with a heuristic optimization algorithm, the SlotMachine system finds an optimal flight list. A flexible credit system may ensure fairness and equity over time: Airlines may earn credits by accepting additional delay, which can be spent for prioritizing flights in the future.

Keywords: flight prioritization, multi-party computation, evolutionary algorithm, heuristic optimization