Research for Ground Delay Program Enhancements

October 31, 2001

Metron Aviation, Inc.

Robert Hoffman, Ph.D.

10/17/2001 2

Main Thrusts of GDP-E Research

• Allocation of Arrival Resources among– single airport, using distance (“distance-based GDP”)

– multiple arrival fixes (“multi-fix GDP”)

– multiple airports (“multi-airport GDPs”)

10/17/2001 3

FAA Ground Delay Programs

• Single airport scenario with a demand-capacity imbalance

• Apply FAA-assigned ground delays to flights bound for a common destination airport

• Ground delays reduce rate of arrival flow– alleviates airborne holding

– transfers airborne queues to the ground

10/17/2001 4

Central (deterministic) GDP Issues

• Demand predictions (carrier supplied data)• Capacity predictions (runway config, AARs)• Geographical scope of the program• Temporal scope of the program

– start/end time, model time, potential cancellation time

• Equity among– flights

– air carriers

10/17/2001 5

Stochastic GDP Issues

• Demand uncertainty– pop-up flights (FA delays)

– cancellations (compression)

– departure times questionable

– en route time

• Capacity uncertainty– capacity prediction usually based on weather forecast

10/17/2001 6

Ground Delay or Air Delay?

• Aggressive program – ground delay lots of flights over long time

– risk of unrecoverable ground delays

• Hedge against weather forecast – ground delay fewer flights over less time

– risk of excessive airborne arrival queues

10/17/2001 7

Current practices

• Geographic scope of GDP set via combinations of ARTCCs (“centers”)

• Tiers (first, second, …) commonly used• Power Run enumerates options

Avg Delay 54 49 32 31Max Delay 115 109 77 77Unrecov Delay 407 390 525 507

10/17/2001 8

How distance-based GDPs can help

• Choose inclusion to program via proximity to GDP airport– e.g., flights within 1500 miles subject to ground delays

• More options than tiers/centers– can only improve quality of solution

– fine tune geographic scope

• Leverage off distance to – mitigate uncertainties

– improve optimization (Power Run)

10/17/2001 9

Sample Tradeoff:Avg Delay Vs. Unrecov Delay

300

350

400

450

500

550

600

650

300 350 410 540 700 760 910 1000 1090 1600 >1600

1100

1150

1200

1250

1300

1350

1400

1450

1500

Efficient solution

Unrec

Trade-off

Avg

BOS 2 Feb 1999

10/17/2001 10

Prototype GraphicTradeoff Curve

200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800

1020 2040

Miles

UnRecov and

Avg Delay

(wtd sum)

Tier 1 Tier 3Tier 2

Recommended

Not Recommended

Max Delay: 271 MinAvg Delay: 135 MinTotal Delay: 1557 MinFlight Count: 139Ooh ooh, pick me!

10/17/2001 11

Tradeoff Curve is a function of MinExpected Duration of GDP

200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800

Miles

Tier 1 Tier 3Tier 2

Hours0102030405060708091011

User Set

Unnecessary Delay

220

200

180

160

140

120

100

80

60

40

20

10/17/2001 12

New Power Run

Air HoldOuch

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 HoldUnrecov DelayAverage DelayMax Delay

160

58

37

10/17/2001 13

10/17/2001 14

Can we optimize GDP settings?

• Yes, but – single parameter searches stronger than multi-

dimensional searches

– must be tempered with traffic flow expertise

• Limitations– quantification of equity principles

– cost/objective functions harder than constraints

• Successes/Benefits– more uniform GDP settings

– first formal treatment of stochastic factors

10/17/2001 15

Multi-fix GDPs

• Current model of flow into airport (during GDP) is a single queue

10/17/2001 16

Multi-fix GDPs

• In reality, flow into an airport is multiple queues over fixes.

10/17/2001 17

Objective of Multi-fix GDP

• To develop algorithms/procedures for controlling multiple flows into GDP airport

• Note: in FSM, we have single fix control capabilities only

10/17/2001 18

Issues in Multi-fix GDP

• Effective arrival fix balancing• Equity among fixes (distribute delay evenly)• Modify current substitution practices

– open arrival slot over one fix does not mean opan arrival slot over another

10/17/2001 19

Multi-Airport GDP Objective

• To develop algorithms/procedures to coordinate GDPs at several airports

• Issues:– efficient use of regional airspace

– equitable access to regional airspace by all airports

– modify current substitution practices

Arp1 Arp2

Arp3Arp4

10/17/2001 20

Multi-Fix Vs. Multi-Airport GDP

• Abstractly, each problem balances multiple flows into a common resource

• Solution to one is solution to the other

Arp1 Arp2

Arp3Arp4

10/17/2001 21

Most General Problem

• Flows into fixes, into airports

• Multi-fix solution must work with multi-airport solution

Origins Fixes Airports

N

S

E

W

EWR

LGA

JFK

TEB

A

B

C

D

10/17/2001 22

Case Study: New York City area

10/17/2001 23

Multi-queue/Multi-resource Allocation Issues

• Added equity consideration– equity among airports (or fixes)

• Greedy algorithms (e.g., RBS) no longer optimal– how sub-optimal is sub-optimal?

• Equity vs. Efficiency greater issue than ever before

10/17/2001 24

Progress on Multi-airport GDP

• Space-time flow model has been developed with equity a primary consideration

• Complex model has simple RBS-like solution

• Integer program, multi-commodity?

N

S

E

W

R E G

L G A

E W R

N

S

E

W

R E G

L G A

E W R

N

S

E

W

R E G

L G A

E W R

,, 2N L G At tE

,, 1N L G At tE

, 1L G At te

, 2L G At te

10/17/2001 25

Deployment Path

• Finalize algorithms and analysis• Dialogue with operational people• Prototyping, war games• Validation

– need to communicate to others

– intuitively explainable?

– how realistic?

• Plug into FSM ultimately

10/17/2001 26

Welcome By-product

• New ideas for rationing– apply to the single airport case

• Avoid RBS side effect– carriers with flights in rear of GDP get disproportionate

delays

• Revamp rationing algorithm for single airport?

10/17/2001 27

Future work (multi-airport/fix)

• Finalize flow model and alternative approaches• Select best balance of mathematical modeling,

flow representation, and practicality• Open questions:

– how inefficient is the equity model?

– how inequitable is the efficiency model?

• Merger of multi-airport/fix (long range)