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A Transparent and Economically Efficient Process for Determining Planned Airport Capacities

A Transparent and Economically Efficient Process for Determining Planned Airport Capacities. Phil Railsback Center for Air Transportation Systems Research George Mason University. Why Determine Planned Capacities?. Delays Are a Function of Planned (Scheduled) Airport Capacity

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A Transparent and Economically Efficient Process for Determining Planned Airport Capacities

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  1. A Transparent and Economically Efficient Process for Determining Planned Airport Capacities Phil Railsback Center for Air Transportation Systems Research George Mason University

  2. Why Determine Planned Capacities? • Delays Are a Function of Planned (Scheduled) Airport Capacity • Economic Cost of Reliability to • Passengers • Airlines • Recognizing Property Rights of Slots to Holders • Slots Can Be A Scarce Resource • Codification of Rights Helps Establish Value • Slots Being Claimed as Financial Assets

  3. Choosing a Planned Capacity • “Planned” v. “Scheduled” • Planned Capacity Must Include Scheduled Operations (Airlines) Unscheduled (“Pop-Up”) Airline Operations General Aviation Operations (US Part 135 and 91) • Unscheduled Operations Must be Taken Into Account in Policy and Planning

  4. Definitions • Time Period Slots Are Considered Fungible Within a Time Period • Airport State Open v. Closed, IMC v VMC, Runways in Use • Planned Capacity Policy-Established Upper Bound on Operations • Realized Capacity Actual Maximum Number of Operations Possible in a Specific Time Period on Day of Operations

  5. Definitions (continued) • Slot Availability Probability of a Planned Slot Being Realized on Day and Time of Operations • Slot Failure Event Where a Planned Slot is Not Realized • Priority Class Sub-grouping of Slots Within a Time Period to Support Multiple Slot Priorities

  6. Randomness and Capacity • Capacity is a Function of Random Processes • Weather • Inter-Arrival Rate Randomness • Departure-Arrival Interference • Fleet Mix Dependence (Wake Vortex) • Therefore Capacity is a Random Process • Capacity is Properly Described as a Probability Density Function (PDF)

  7. Airport State Identification • {Closed, IMC, VMC} X {Runway Configurations} e.g. IMC using 22/13 (Arrival/Departure) VMC using 13/13 etc. • Randomness Leads to a Capacity Distribution by State Can be Determined by Analysis or Empirical Measurement Inter-Arrival Randomness, Arrival-Departure Interference, Fleet Mix Variation • Each State Has a Probability of Occurring State Frequencies are Empirically Measurable

  8. Airport Capacity • Airport States Form a Partitioning • Each State Has a Capacity Distribution • Probability of a Realized Capacity (RC) is (by Law of Total Probability)

  9. Example: LGA • State-Specific Capacity PDFs • Based on Historical Data by State • Selected only Time Periods When Operating at Capacity • Shows Very Little Weather Dependence

  10. Planned Capacity and Slot Availability • There is a Relationship Between Planned Capacity and the Realized Capacity Distribution • The Relationship Results in • Slot Availability (%) • Expected Number of Unplanned Slots

  11. Derivation of Slot Availability • Partition By Possible Realized Capacities • Each Combination of Realized Capacity (RC) and Planned Capacity (PC): • RC >= PC, p is 1 • RC < PC, p is RC / PC • Slot Availability:

  12. Unplanned Slots • Reducing Planned Capacity Increases System Reliability at Cost of Reduced Utilization • U(PC): Expected Number of Unplanned Slots • e.g.: 9 Planned Slots, 12 Realized Slots • 3 Unplanned Slots – Opportunity Cost • The Expected Value is:

  13. Example: LGA

  14. Example: LGA

  15. Economic Efficiency • What is the Most Efficient Planned Capacity? • Maintain System Reliability v. Maximize Throughput • We Need Slot Valuation as a Function of Slot Availability • Then Maximize Summed Slot Valuation: • e.g.: 5 Slots at 98% valued at 900 € each • 10 Slots at 85% valued at 400 € each • 4500 € > 4000 € → Plan 5 Slots

  16. Auctions Can Provide Valuation • Auctions Provide Value Discovery Across Multiple Operators • We Can Integrate Desired Availability into a Slot Auction • Auction Availability/Priority Classes, or • Have Bidders Specify Desired Availability in Their Packages • Might be Prone to Auction Gaming • Necessary Condition for Operators’ Product Differentiation by On-Time Performance

  17. LGA Example: Priority 2 Slots • Compare: • 5 Priority 1 Slots, 98% Availability and (from previous plot) • 5 Priority 2 Slots, 71% Availability; or (from this plot) • 10 Priority 1 Slots, 84% (from previous plot)

  18. Conclusions • Provides Simple, Transparent Relationship Between Availability and Planned Capacities • Shows How Market Mechanisms (Auctions) Can Provide Answer to Trading Off Throughput and Reliability • Data Are Critical to Results • Insights Into Airport Behavior

  19. Questions • Phil Railsback • George Mason University • prailsba@gmu.edu

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