Implementing Dynamic Air Transport
Slot Trading Through Secure Auction
Mechanism
Emre Koyuncu, Baris Baspinar, Guney Guner,
N. Kemal Üre, Massimiliano Zanin, Vaishali Mirchandani, Emilio
Alvarez Pereira and Gokhan Inalhan
Simulation Models for Results for Business Cases
We have developed simulation models for
Slot Trading and Dynamical Landing Queues
and
Analysis of Delay Reports
Data Library
• The test data for the simulations is created through real traffic data
– Available datasets for modeling
• ALLFT+ data in DDR2 of EUROCONTROL
• Capacity reports in DDR2 of EUROCONTROL
– Complete through statistical analyses
Slot Trading and Dynamical Landing Queues
Primary market: Slots are sold by airports to airlines.
Secondary market: Slot trading occurs between airlines.
Strategic: Slots are sold for some period. planned auctions.
Operational: slot trade occurs during tactical operation.
Slot Trading and Dynamical Landing Queues
Scenario 1: N airlines try to buy slots from an airport. Strategic and primary market.
Scenario 2: N airlines try to buy slots from another airline. Strategic and secondary market.
Scenario 3: N airlines try to buy a priority approach from an airport. Operational market.
Simulation Model for
Slot Trading and Dynamical Landing Queues
Scenario 1 for
Slot Trading and Dynamical Landing Queues
Scenario 1: N airlines try to buy slots from an airport. Strategic and primary market.
Scenario 1 for
Slot Trading and Dynamical Landing Queues
Slot Allocation Model (SAM)
Based on data driven ATM Queuing Model
Data driven slot allocation through EUROCONTROL DDR2 ALLFT+ data
la (t)
Arrival
service rate
Arrival demand
ma (t) + q a (t)
Taxi-out
Estimated Landing Time
service rate upon trade
Departure
service rate
Airport/Runway Queuing
System
Turnaround
time
md (t + 1)
ld (t + 1)
Departure demand
Taxi-in
Target Off-Block Time
Take off Slot Allocatian
1.0.0 Taxi-in
Taxi-out
Landing Slot Allocatian
Estimated In-Block Time
Calculated Take off Time
Slot Interest Decision Maker (SID)
• Slot Interest Decision Maker (SID) adds competition by adding
random factor in slot demand.
– Competition begins when at least two airlines want to get same
slot.
Scenario 1 for
Slot Trading and Dynamical Landing Queues
Web based SMC simulation portal for the participants
Participant
who wants
to sell his
slot
Number Of
SMC Server
Creates a new event
in order to gathering
data from
participants
Application
Selection
Menu
Start Secure
Computing
Display
Results
Scenario 2 for
Slot Trading and Dynamical Landing Queues
Scenario 2: N airlines try to buy slots from another airline. Strategic and secondary market.
Scenario 2 for
Slot Trading and Dynamical Landing Queues
Slot Interest Decision (SIM) Model
hypothetically generates a market and creates traders by utilizing flight frequencies
using ALLFT+ data
The idea behind the concept model is that
• airlines are interested in selling non-scheduled or least frequently
used slots
• airlines are interested in buying the slots around their most
frequently used slots
Scenario 2 for
Slot Trading and Dynamical Landing Queues
Web Based Simulation Portal for
Slot Trading and Dynamical Landing Queues
Scenario 3 for
Slot Trading and Dynamical Landing Queues
Scenario 3: airlines try to buy a priority approach from an airport. Operational market.
Scenario 3 for
Slot Trading and Dynamical Landing Queues
Slot Interest Decision (SIM) Model
Evaluate en-route delays for each landing aircraft.
If it is more than 30 minutes, airline is interested in buying a
priority slot.
SMC Bid comparison
• SMC Engine collects offers.
– If the result is a tie between two or more participants, the referee
provides a notification to the participants and creates a new
secure auction.
– If the minimum price that the seller asks for has not been
reached, participants are informed about this.
• Winning price and the winner is disclosed to all participants
Web Based Simulation Portal for
Slot Trading and Dynamical Landing Queues
…example logs
Pricing policy
•
For Scenario 1, the price for slots is based on demand intensity
– where the more demand, the higher the minimum price will be for a
specific flight hour.
– The minimum and the maximum values of a particular airport are based
on the maximum demand
• busiest airport is most expensive
Time
5am
6am
Price for EGLL 550 € 500 €
Time
Price for LEBL
5am
350 €
7am
600 €
6am
7am
300 € 400 €
… 8pm 9pm
750 € 800 €
…
10pm
800 €
8pm
9pm
550 € 600 €
10pm
600 €
Pricing policy
•
For Scenario 2, slot pricing for airline slot swapping is dependent on
– their frequency of flight and
– the demand intensity at the requested slot hours.
•
For Scenario 3, the min price of priority landing slots is a
– fixed flat rate (for a specific airport for a specific day)
Conclusions
Slot Trading and Dynamical Landing Queues
Primary and secondary markets including real-time (priority landing) for slot trade have been
simulated through the Secure Multiparty Computation (SMC) library.
Considering the needs of such trade, a web-based Simulation Portal has been developed,
enabling referee and participants to manage each type of trade operations,
• logging into the system,
• putting slot into market,
• bidding for slots, etc.
Through the batch simulations, we have demonstrated the feasibility of such business for slot
trade.
In addition to secure information sharing through the SMC tools, structuring highly dynamic
market adds benefits to the airlines, allowing to make their operations more flexible according
to the current needs.
•
To assess the advantage of this business model, one can run these simulations through the
real commercial interests, which is not open to others.