1. Analysis of Demand Uncertainty in Ground Delay Programs Mike Ball University of Maryland

2. destination airport flights Uncertainty in Arrival Stream airborne queue open slots slots w multiple flights Sources of uncertainty: cancellations, pop-ups, drift

3. destination airport flights Planned vs Actual Airport Acceptance Rate AAR: airport acceptance rate – rate at which flights land at airport Planned AAR (PAAR) Actual AAR queue In order to fully utilize arrival capacity, a queue must be maintained “to keep the pressure on the airport” This is done by regulating the value of the PAAR

4. Models Integer Program –considers only flight cancellations –variables: PAAR in each time period, Pr{k flights in airborne queue at end of period i} –obj fcn: min total exp airborne delay –inputs: flight cancellation prob, overall slot utilization, AAR Simulation –Considers cancellations, pop-ups, drift

5. Airborne Delay vs Cancellation Prob (IP Model)

6. “Marginal” Effects of Uncertainty in Presence of Cancellations, Pop-ups, Drift (Sim Model)

7. “Marginal” Effects of Uncertainty in Presence of Cancellations, Pop-ups Drift (Sim Model)

8. scheduled departure times arrival times Prelude to Understanding Compression Impact: Delay vs Arrival Times departure times ground delay airborne delay Delay(f) = arr_time(f) – sched_dep_time(f) – dir_en_route_time(f) Delay(f) = arr_time(f) – sched_arr_time(f) Tot_delay =  arr_time(f) –  sched_dep_time(f) –  dir_en_route_time(f)  As long as the overall set of arrival times (arrival slots used) remains the same total delay remains the same

9. Compression Benefits Compression has filled in holes in the PAAR which has reduced the amount of assigned ground delay Possible system effects: Holes in AAR have been filled in and total delay has been reduced There were no holes in AAR so reduced ground delay has been replaced by airborne delay Uncertainty in the arrival stream has been reduced enabling a reduction in the PAAR required to achieve a given AAR and a reduction in overall airborne delay Of course, each individual airline generally derives substantial benefits based on internal cost reductions.

10. Analysis Looked at PAAR vs Actual AAR (arrivals) for 1 st program hr, 2 nd program hr, etc. for three airports; tried to group like GDPs, e.g. only morning GDPs at SFO –ATL and BOS: used command center logs for PAAR and AAR –SFO: used command center logs for PAAR, tower counts for AAR. Important Questions: –Is PAAR or AAR increasing or decreasing (improvement = increase in AAR) –Is deviation of PAAR from AAR changing (improvement: PAAR and AAR closer together)

11. SFO PAAR Actual AAR

12. PAAR Actual AAR ATL

13. PAAR Actual AAR BOS

14. Typical PAARs Used Today 35 34 33 32 31 30 29 28 27 PAAR 1 2 3 4 5 6 7 Time Period (hour) 1 2 3 4 5 6 7

15. Sample PAARs Recommended by IP Model 35 34 33 32 31 30 29 28 27 PAAR 1 2 3 4 5 6 7 Time Period (hour) 1 2 3 4 5 6 7

16. Conclusions Reducing uncertainty is extremely important –Pop-ups –Cancellations w/o notification –Wide departure windows (may be most important) No evidence found (yet) that improved prediction accuracy of CDM has been transformed into actual uncertainty reduction benefits (more analysis necessary) Command Center (and FSM) should consider change in manner of setting AARs