1. www.metsci.com/cdm

2. Schedule Delay Initial Delay Crews Gate Space Aircraft Passengers Propagates into Large Delay

3. Non-linear Response to Capacity Reduction Reducing the airport capacity to 50%, generates over 65,000 minutes of delay at the airport and 139,000 minutes system wide. System delay 0 50000 100000 150000 200000 250000 300000 1009692888380757267635855504742 Available Airport Capacity (Percentage) Delay Airport delay

4. Current CDM GDP Process FAA/Airline Evaluation Demand Vs. Capacity GDP Modeling Send Proposed GDP Advisory Airline Response (cancellations) Is GDP still required? Issue GDP Airline Response (Substitutions & Cancellations) Compression GDP Revision /Extension Yes End No Exit loop when program expires or is cancelled. (Ration by schedule)

5. TFM Dependencies Although, the capacity at an airport is reduced and ATC delay has been applied, users may cancel and delay flights as well as notify the FAA of earliest feasible departure times of flights. FAA Actions Cancellations Airline Delays beyond ATC delay Earliest Departure/Arrival Time updates Airline Actions Issue ATC delay Generate Demand Reduce ATC delay

6. Passengers 60 116 93 87 Total 443 P-DELAY = #PSGR X min DLYD P-Delay min = 26580 P-Delay min =3600 Original P-Delay is 738% greater than revised Passengers 0 CNX 176 (60 late) 93 87

7. Airline and FAA Actions can Reduce Delays

8. What Do We Measure? Event Predictability (also referred to as compliance) ETA predictability –Departure Compliance –ETE Fluctuation –Arrival Compliance Arrival rate delivery Rate Control Index (RCI) What could have been done to improve? What are the impacts of new changes (e.g., +_5 minute window)?

9. What Do We Measure? Departure Compliance

10. What Do We Measure ? ETE Fluctuation

11. What Do We Measure? Arrival Compliance

12. What Do We Measure? Arrival Rate Delivery Rate Control Index (RCI) –Used to quantify the deviations in the actual hourly arrival counts from the planned hourly arrival counts –Can be used to compare one program to any other –Perfect score = 100% Aggregate RCI –Looks only at total number of flights in each hour Nominal RCI –Looks at which flights arrived in each hour –Nominal RCI < Aggregate RCI

13. What Could Have Been Done to Improve? More frequent revisions Tighter enforcement of departure times Higher standards for data quality to remove: –Time-Out cancellations –Time-Out delays –Cancel but flew Re-evaluated treatment of Pop Up flights

14. What Do We Measure? +/- 5 minute Compliance Test Controlled flights departing to a GDP are required to depart within +/- 5 minutes of their Expected Departure Clearance Time (EDCT) Flights that fail to meet the compliance window must request a new EDCT from the ATCSCC. Miles In Trail restrictions are lifted for flights destined for 7 airports; ATL, DFW, ORD, EWR, STL, SFO, PHL. Goal of improved departure compliance.

15. Impact of New Changes Departure Standard Deviation Before test = 32.14 During test = 15.90

16. Impact of New Changes En Route Standard Deviation Before test = 12.85 During test = 10.00

17. Impact of New Changes Arrivals Standard Deviation Before test = 33.32 During test = 38.12

18. Impact of New Changes RCI Average Aggregate RCI 1/1/01-4/2/02:87.94 Average Aggregate RCI 4/3/02-4/21/02:96.75 RCI has improved by: 10%

19. The Need for Revision As the demand changes, the need for revisions increases. The arrival demand would have been smoothed out if a revision had been run at 1758Z during this PHL program. Solid bars = current demand Hashed bars = revised demand

20. The Fallacy of Binning Measuring demand in one-hour bins does not describe how that demand is distributed throughout the hour. Each hour bin below has the same total demand. However, the demand distributions vary dramatically. =19.4 =8.66 =0

21. Solution to Binning: Arrival Flow Rates Viewing the demand in one-hour bins does not show the underlying fluctuations that exist. Viewing the demand as a Flow Rate shows the actual demand fluctuations, forecasting the potential for airborne holding – viewed as a moving window average Images from the Flow Rate Analysis Tool

22. Equity Measures Affected Average Delay Proportions from carrier statistics EMF/EMA from power run

23. Equity Measures Affected Average Delay

24. Equity Measures Proportion of Flights Affected by Carrier

25. Equity Metric for Airlines (EMA) and Equity Metric for Flights (EMF): EMA/EMF: Compares the amount of imposed ground delay to the baseline of airborne holding 2-8: Good Equity 9-16: Significant deviations from good equity 16+: Poor equity

26. The Many Facets of Equity Long haul Vs. Short haul flights GA Vs. Scheduled Carriers Regional Vs. Majors Overhead stream Vs. Departures Equity across flights, carriers, ARTCCs, airports,... No single vantage point serves for all occasions

27. Distance-based GDPs Set inclusion for ground delay based on distance from GDP airport As GDP radius is increased, delay per flight goes down but (risk of) unrecoverable delay goes up Find optimal tradeoff

28. Delay Graphic Air Hold Ouch 220 200 180 160 140 120 100 80 60 40 20 Minutes Unrecoverable Delay Average Delay 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 Miles Air Hold Unrecov Delay Average Delay Max Delay 160 58 37

29. What Do Airlines Measure? Air En Route Times Fuel Burn Diversions Taxi-Out Times Passenger Load Factor

30. As the time of the event approaches, certainty goes up but possible options are reduced. OptionsCertainty Time Before event There is Always a Trade-off in Delaying Actions

31. Options Decrease While Knowledge Increases Objective – increase knowledge while options remain open. Essential to explore tactical relationships Options Certainty Increase knowledge earlier Keep options open longer