Periodic Reporting for period 2 - SlotMachine (A Privacy-Preserving Marketplace for Slot Management)
Periodo di rendicontazione: 2021-10-01 al 2022-12-31
Balancing air traffic demand with capacity is critical to ensuring the smooth and orderly flow of flights. With rising passenger numbers and increased flight volumes, new innovative technologies will be needed to help flexibly manage ever more congested airspace. To ease congestion, simple swaps between two flights can currently take place. Such exchanges help airlines to prioritise certain flights, according to flight cost structures, to minimise costs and reduce passenger delays. For airlines, the prioritization – and swapping – of these flight slots is therefore a critical cost issue.
A challenge here is that flight cost structures, which influence how airlines prioritise flights and may vary for any number of reasons, are highly confidential. This is not information that airlines necessarily want to share with others and has hampered slot swapping between different airlines in the past.
The SlotMachine project sought to harness the power of artificial intelligence (AI) technology to create a semi-automated flight allocation swap platform, based on the cost structure priorities of different airlines. Airspace users can securely input their flight preferences, together with supporting data, via a graphic interface. This data is sent to the system’s heuristic optimiser, where genetic algorithms are applied to the combined data, to find incrementally improved solutions in terms of flight prioritisation.
The prototype builds on the principle of separating the search for optimal flight lists from the evaluation of the flight lists. The evaluation is conducted by the Privacy Engine, which employs MPC to evaluate the solutions. MPC nodes external to the SlotMachine system conduct the necessary computations. No single MPC node knows the full inputs. Different parties, e.g. different AUs, may host the MPC nodes. The employed architecture could also potentially be employed for other optimization problems. The SlotMachine project has the following main objectives:
- Delay and cost optimization. The delay and, more importantly, the delay costs should be reduced by allowing airspace users to prioritize flights and exchange ATFM slots in case of reduced capacity in the air traffic network following a regulation. The success of the optimization can be measured either by decreased costs or, conversely, by increased utility, if the preferences of airspace users are stated in terms of economic utility of a slot for a flight. A maximization of utility leads to a minimization of the costs.
- Equity and fairness over time. Airspace users giving up favourable slots should be compensated. We propose market mechanisms based on credits. Prioritization of a flight requires the airspace user to spend credits, accepting additional delay leads to the airspace user receiving credits which can be spent to prioritize flights in the future.
A challenge here is that flight cost structures, which influence how airlines prioritise flights and may vary for any number of reasons, are highly confidential. This is not information that airlines necessarily want to share with others and has hampered slot swapping between different airlines in the past.
The SlotMachine project sought to harness the power of artificial intelligence (AI) technology to create a semi-automated flight allocation swap platform, based on the cost structure priorities of different airlines. Airspace users can securely input their flight preferences, together with supporting data, via a graphic interface. This data is sent to the system’s heuristic optimiser, where genetic algorithms are applied to the combined data, to find incrementally improved solutions in terms of flight prioritisation.
The prototype builds on the principle of separating the search for optimal flight lists from the evaluation of the flight lists. The evaluation is conducted by the Privacy Engine, which employs MPC to evaluate the solutions. MPC nodes external to the SlotMachine system conduct the necessary computations. No single MPC node knows the full inputs. Different parties, e.g. different AUs, may host the MPC nodes. The employed architecture could also potentially be employed for other optimization problems. The SlotMachine project has the following main objectives:
- Delay and cost optimization. The delay and, more importantly, the delay costs should be reduced by allowing airspace users to prioritize flights and exchange ATFM slots in case of reduced capacity in the air traffic network following a regulation. The success of the optimization can be measured either by decreased costs or, conversely, by increased utility, if the preferences of airspace users are stated in terms of economic utility of a slot for a flight. A maximization of utility leads to a minimization of the costs.
- Equity and fairness over time. Airspace users giving up favourable slots should be compensated. We propose market mechanisms based on credits. Prioritization of a flight requires the airspace user to spend credits, accepting additional delay leads to the airspace user receiving credits which can be spent to prioritize flights in the future.
The general approach within the SlotMachine project was to identify the requirements from all relevant stakeholders, develop the design, implement all necessary components, and finally perform an evaluation using the SlotMachine Platform Demonstrator. The initial objectives in the project proposal were stated as:
1. Development of a novel slot swapping platform to improve utilization of available resources at airports and reduce cost for airlines.
2. Research and development for a secure and trustworthy system for slot swapping which employs an evolutionary algorithm in conjunction with the PrivacyEngine handling private data in a privacy-preserving way.
3. Realization of a proof-of-concept implementation of the SlotMachine Platform Demonstrator, which offers privacy-preserving slot management.
Work package 2 focused on the Requirements Specification and the System Design in general. While in D2.3 Business Concepts the envisioned SlotMachine solution and operating methods were described. One of the operational acceptance objectives from Airspace Users was to be able to provide automatically or semi-automatically priorities to SlotMachine and get a transparent and stable offer from SlotMachine with as little manual inputs as possible. Another need was that handled credit transactions shall be stored in an immutable and redundant form to verify that the process is indeed fair and at the same time automatically encrypt protected information that must be hidden from other participants, and AUs get a summary/report every once in a while, (for example, depending on the frequency of SlotMachine usage, every Aeronautical Information Regulation And Control (AIRAC) cycle/every three months/every season, etc.) to ensure transparency of equity/inequity balance in the system. E.g.: a dashboard aggregates metadata and key performance indicators from flight prioritization exchanges to allow statistical evaluation of the SlotMachine performance.
Work package 3 and 4 worked on the concept and implementation of the various components developed during the project to address those requirements while work package 5 focused on the integration of all those components including validation and dissemination of the whole demonstrator.
To ensure the realization of potential synergies with other SJU projects, SlotMachine used the KTN Engage and participated in the SESAR Innovation Days (SID) via poster presentations in 2021 and 2022. In return SlotMachine members have been invited to other relevant ER projects advisory boards. In order to reach the wider academic community and industrial partners in air traffic management (ATM), SlotMachine participated and published in some of the main venues for ATM research, namely the Digital Avionics Systems Conference (DASC), the Integrated Communications Navigation and Surveillance (ICNS), and the Congress of the International Council on the Aeronautical Sciences (ICAS Congress).
1. Development of a novel slot swapping platform to improve utilization of available resources at airports and reduce cost for airlines.
2. Research and development for a secure and trustworthy system for slot swapping which employs an evolutionary algorithm in conjunction with the PrivacyEngine handling private data in a privacy-preserving way.
3. Realization of a proof-of-concept implementation of the SlotMachine Platform Demonstrator, which offers privacy-preserving slot management.
Work package 2 focused on the Requirements Specification and the System Design in general. While in D2.3 Business Concepts the envisioned SlotMachine solution and operating methods were described. One of the operational acceptance objectives from Airspace Users was to be able to provide automatically or semi-automatically priorities to SlotMachine and get a transparent and stable offer from SlotMachine with as little manual inputs as possible. Another need was that handled credit transactions shall be stored in an immutable and redundant form to verify that the process is indeed fair and at the same time automatically encrypt protected information that must be hidden from other participants, and AUs get a summary/report every once in a while, (for example, depending on the frequency of SlotMachine usage, every Aeronautical Information Regulation And Control (AIRAC) cycle/every three months/every season, etc.) to ensure transparency of equity/inequity balance in the system. E.g.: a dashboard aggregates metadata and key performance indicators from flight prioritization exchanges to allow statistical evaluation of the SlotMachine performance.
Work package 3 and 4 worked on the concept and implementation of the various components developed during the project to address those requirements while work package 5 focused on the integration of all those components including validation and dissemination of the whole demonstrator.
To ensure the realization of potential synergies with other SJU projects, SlotMachine used the KTN Engage and participated in the SESAR Innovation Days (SID) via poster presentations in 2021 and 2022. In return SlotMachine members have been invited to other relevant ER projects advisory boards. In order to reach the wider academic community and industrial partners in air traffic management (ATM), SlotMachine participated and published in some of the main venues for ATM research, namely the Digital Avionics Systems Conference (DASC), the Integrated Communications Navigation and Surveillance (ICNS), and the Congress of the International Council on the Aeronautical Sciences (ICAS Congress).
One of the core technologies analysed is multiparty computation (MPC) which enables the evaluation of functions while keeping the inputs private. It will be used in SlotMachine to replace the trusted party typically needed to evaluate the private bids and priorities of airspace users during the optimization step. Secondly, we investigated methods for verifiable computing and how the overall process could be made more transparent although the private inputs must be kept confidential. Efficient and practical zero-knowledge proof systems have been studied and the most promising candidates to realize some form of public verifiability and traceability are highlighted. Finally, blockchain solutions to realize a dedicated permissioned ledger as a trust anchor in SlotMachine have been analysed. The scalability and performance were measured in practical deployment scenarios.