Air Travel at the Edge of Chaos - George Mason …catsr.ite.gmu.edu/pubs... · Air Travel at the...

CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCHCENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCHCENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCHCENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH

Air Travel at the Edge of ChaosGeorge L. Donohue, Ph.D.

Professor Systems Engineering and Operations ResearchDirector of the Center for Air Transportation Systems Research

Volgenau School of Information Technology and Engineering

NASA Ames Director’s Forum November 16 , 2007

© George L. Donohue 2007

2

CATSRCATSRCATSRCATSROutline• How Bad and widespread is the Problem

• What Has Changed Since 1947• Passenger QOS• Economic Impact

• What are the Underlying Causes• Too Many Scheduled Flights into Too Few Runways

• Why the Airlines cannot fix the Problem Themselves• Prisoners Dilemma and Curse of the Commons

• Safety is the Underlying Capacity Constraint• Current Safety Trends• Airport Arrival Time Slot Auctions

• High Payoff Research Topics • NEXTGEN ATM system

3

CATSRCATSRCATSRCATSRWhat has Changed since 1947?

•Transonic vs. Subsonic Aircraft•40,000 ft vs. 20,000 ft Altitude•Avionics:

• Flight Management Systems• Required Navigation Perf.

0.1nm• Required Time of Arrival• Traffic Collision Avoidance

System – On the Aircraft!• AOC Data Links• Zero Visibility Landing

Systems•ATC radar Separation•WHAT HAS NOT CHANGED

• Air Traffic Controllers talking to Pilots using WW II AM Radio Technology

4

CATSRCATSRCATSRCATSRSome Little Known Facts

•Modern Jet Aircraft “Gate-to-Gate”Travel Time is the Same or Longerthan Propeller aircraft (DC-6 circa 1947) for many routes in NE Triangle

• Typical Jet Aircraft is 70% Faster and fly's 80% Higher

•Jet Aircraft can fly Over most bad weather•Modern Commercial Jet Aircraft can land in very low visibility•Airport Congestion Causes Most ATC Delays and Airline Schedule Padding Masks Real “Gate-to-Gate”Delay

5

CATSRCATSRCATSRCATSR

Overscheduled Airports are the Problem:Average Delay per Flight

Ordered by Arrival Delay at Outbound Destination. (minute) [Ning Xu GMU 2007]

-20.0

-15.0

-10.0

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

ATL JFK

PH

L

MSP

ORD MIA

EW

R

DTW

DFW IA

D

CLT FLL

LGA

ME

M

BO

S

MC

O

DC

A

BW

I

IAH

SE

A

TPA

DE

N

CLE PIT

LAS

MD

W

STL

CV

G

PH

X

SFO LA

X

PD

X

SLC

SA

N

34 OEP Airport

Del

ays

per F

light

(min

ute)

Airport DelayEarly-arrival GapInbound DelayAirborne DelayArrival Delay at Outbound Dest.

Summer 2005 at 34 OEP Airports

6


Delay Incurred at Major Airports Propagate Network Wide (Summer 2005)

-550000

-350000

-150000

50000

250000

450000

650000

850000

1050000

1250000

1450000

ATL

OR

D

DFW

EWR

PHL

MS

P

DTW

DEN

BOS

JFK

LGA

IAH

IAD

CLT

MCO DC

A

PHX

MIA

LAX

LAS

BW

I

SEA FL

L

CVG

CLE

MDW SF

O

TPA

PIT

STL

SLC

SAN

MEM PD

X

34 OEP Airport

Tota

l Del

ays

(min

ute)

Airport DelayEarly-arrival GapInbound DelayAirborne DelayArrival Delay at Outbound Dest.

Total Delay Ordered by Arrival Delay at Outbound Destination. (minute)

[Ning Xu GMU 2007]

20,000 Flight Hours

7


NYNJ comparison to Comparable European Airports

Data taken from ACI-NA, EC PR2006 and FAA ASPM

Total Total Average DelaysAirport Movements Passengers Minutes

2005 2000 2005 2000 2006Frankfurt, Gr (FRA) 490,147 458,731 52,219,412 49,360,630 2.7London, UK (LHR) 477,884 466,815 67,915,403 64,606,826 3

Newark (EWR) 437,402 450,187 33,999,990 34,188,468 28.8Amsterdam, NL (AMS) 420,736 432,480 44,163,098 39,606,925 0.7

New York Laguardia (LGA) 404,853 384,554 <29,000,000 <28,000,000 23.4Munich (MUC) 398,838 - <29,000,000 1.8

New York Kennedy (JFK) <353,000 <384,000 41,885,104 32,856,220 24.3Madrid, Sp (MAD) 415,677 <384,000 41,940,059 32,893,190 1.8

8


Air Transportation System (ATS) is a CAS with 6 Interacting Network Layers

Government Regulatory Control LayerPhysical Layer (i.e. Cities, Airports, Demographics)

Weather Layer (Thunderstorms, Ice Storms)

Airline Layer (Routes, Schedules, A/C size)TSA/FAA Layer (ATC Radar, Radios, Ctr’s, Unions)

Passenger/Cargo Layer (Delays, Cancellations)

•The ATS is a Public - Private Partnership with conflicting objective functions:

•Public – Commerce and safety; interest groups

•Private – Profit maximization

9


Air Transportation System is Designedto Move Passengers and Cargo

Passenger Tier Performance = f (Vehicle Tier Performance, Passenger Factors i.e. Aircraft Gauge, Load Factor, Cancellations)

10

CATSRCATSRCATSRCATSRPassenger Total Delay – Airports• 10 of the OEP-35 airports 50% Total EPTD• some airports significantly impact Passenger Delay more than

others (e.g. ORD, ATL, DFW and MCO)

50%

Close Network of OEP35 Airport in 2004

11


200 Routes generate 50% of Total Passenger Delay

• 17% of the 1044 routes between OEP-35 airports 50% Total EPTD• LGA, JFK, EWR, PHL connected Routes 11 out of top 20 routes

50%

Close Network of OEP35 Airport in 2004

12


Top 20 Worst Airports in the US:Passenger Quality of Service Metric

Year

Rank Airports

Prob. Of PaxDelay >45 min Airports



Prob. Of PaxDelay >45 min

1 ORD 14% EWR 18% ORD 17% EWR 16%2 EWR 14% LGA 17% EWR 16% LGA 15%3 LGA 13% ATL 14% LGA 15% ORD 15%4 PHL 12% PHL 13% PHL 15% PHL 13%5 ATL 11% BOS 13% JFK 14% ATL 12%6 MIA 9% ORD 12% IAD 12% JFK 11%7 FLL 9% FLL 12% MIA 12% BOS 11%8 MCO 9% JFK 12% ATL 12% MIA 11%9 DFW 9% MIA 11% MDW 12% FLL 10%

10 LAS 9% SFO 11% DTW 12% IAD 10%11 BOS 9% SEA 10% DFW 12% DFW 10%12 SFO 9% IAD 10% BOS 11% SFO 10%13 IAD 9% TPA 10% DEN 11% DTW 9%14 JFK 9% MCO 10% CLT 10% MCO 9%15 CLE 9% BWI 9% IAH 10% LAS 9%16 SEA 8% PIT 9% CLE 10% CLE 9%17 TPA 8% PDX 9% PIT 10% PIT 9%18 STL 8% DTW 9% DCA 10% SEA 9%19 PDX 8% LAS 9% MEM 10% MDW 9%20 BWI 8% DCA 9% SFO 10% DCA 9%

2004 2005 2006 Average of 2004 to 2006

D. Wang, GMU PhD. In Progress

13


Many Highly Congested Airports can Shift Passengers to other Large Airports

ConnectingAirport Passengers

%Chicago O'Hare 59

Newark NJ 32NY LaGuardia 8

NY JFK 40Philadelphia 38

Atlanta 66Boston 15Miami 55

Washington Dulles 53Dallas/Fort Worth 60

FAA 2006 NPIAS

14

CATSRCATSRCATSRCATSRAirline Load Factors are Increasing

45

50

55

60

65

70

75

80

85

90

1960 1970 1980 1990 2000 2010

Year

Perc

ent A

ircr

aft S

eats

Occ

upie

d (A

vera

ge) Load Factor

(Anticipated)

Load Factor ATAHistorical Data

15


GMU Model Projects Passenger Delays to Greatly Exceed 2000 delays by 2010

Total Passenger Delays

-

20

40

60

80

100

120

140

160

1998 2000 2002 2004 2006 2008 2010 2012

Year

Hou

rs (m

illio

ns)

Delayed FlightsCancelled FlightsPoly. (Delayed Flights)Poly. (Cancelled Flights)

D. Wang 2007

16


Annual Passenger Enplanements Predicted to be Lost: FAA Forecast to 2025

Annual Projected Enplanements Foregone Because of Airport Capacity Constraints

0

5

10

15

20

25

30

ATL

BO

S

BW

I

CLE CLT

CVG DC

A

DEN

DFW

DTW

EWR

FLL

HN

L

IAD

IAH

JFK

LAS

LAX

LGA

MC

O

MD

W

MEM M

IA

MSP

OR

D

PDX

PHL

PHX

PIT

SAN

SEA

SFO

SLC

STL

TPA

Airports

Ann

ual E

npla

nem

ents

Los

t (M

illio

ns)

202520152005

Optimistic: All Planned Airport Improvements

Occur

All available landing slots fully utilized regardless of congestion

EWR

ORDJFK

FAA 2005 TAF & 2004 Benchmark

LGA

17


Estimated Annual Cost to US (Lost Consumer Surplus, 2005$) due to Expected Airport Capacity Limitations

$0

$5

$10

$15

$20

$25

100% 95% 90% 85% 80%Usable NAS Capacity (%)

Ann

ual C

ost t

o U

S Ec

onom

y ($

B) CY2015, All A/P

Improvements

CY2015, No A/PImprovements

CY2025, All A/PImprovements

CY2025, No A/PImprovements

--FAA Assumptions on Growth in Airport Operations--Boeing Passenger Growth Assumptions: 3.6% per year--Aircraft Upgage: 5% in 2015, 10% in 2025

Shaver 2007

Assumes:$200/segment ticketPrice Elasticity = -1

18


Minimum Congestion Cost is a function of NEXTGEN Technology Effectiveness and Network Efficiency

$0

$5

$10

$15

$20

0.8 0.85 0.9 0.95 1Congestion Factor

Ann

ual C

onge

stio

n C

ost (

$B)

Consumer Surplus Costs Resulting From Limiting Airport Slots

Sum of Costs ($B)

Costs Resulting from PassengerDelays and Flight Cancellations

Caution: Some Costs Not Included

19






• High Payoff Research Topics• NEXTGEN ATM system

20


Jet Blue and Delta AL are Competing for the JFK Market:Passengers Pay the Price in Flight Delays and Cancellations

5 AM 10 AM 3 PM 8 PM Midnight

JFK Summer 2007 Departures

0

5

10

15

20

25

0 20 40 60 80 100 120

24 Hours in 15 min. Epochs

Flig

ht D

epar

ture

s per

15

Min

ure

Epo

ch

FAA Announced Departure Rate(weekday AVG +/- 2)Airline's Scheduled Departures

21


Reduction in Average Number of Aircraft Seatsby Airport – All Departures

-4.2%-11.4%

-10.4%

-15.5%

-18.9%9.9%

-6.8%-0.1%-12.7%

0

20

40

60

80

100

120

140

160

180

200

ATL DFW EWR IAD IAH JFK LGA ORD PHL

July 2002 July 2007Dorothy RobynThe Brattle Group

22

CATSRCATSRCATSRCATSRJFK Average Delay Profile (2006)

Time of Day (hour)

De

lay

pe

r Flig

ht (

min

ute

s)JFK

0 5 10 15 20-40

-20

0

20

40

60

80

23


New York LaGuardia Airport:Case Study of a Slot Controlled Airport

Data (2005):• Throughput:

404,853 flights/yr• Average flight delay:

38 min• Revenue passengers:

26,671,787• Average aircraft size:

96 passenger• Average inter-city fare:

$133

24


NYNJ Airport with Current Slot Controls:LGA 2004 – 2006 (DOT Data)

Marginal Rate IFR Rate

Calculated Capacity (Today) and Actual Throughput

Optimum Rate

0

20

40

60

0 20 40 60

Departures per Hour

Arr

ival

s pe

r Hou

r

Calculated Capacity - Today

Facility Reported Rate - LGA(arrivals, departures per hr)

39,39

Each symbol represents actual traffic during a single hour

Infrequent Most Frequent

0

20

40

60

0 20 40 60

Departures per Hour

Arr

ival

s pe

r Hou

r

37,37

0

20

40

60

0 20 40 60

Departures per Hour

Arr

ival

s pe

r Hou

r

37,37

Time of Day (hour)

Del

ay p

er

Flig

ht (

min

ute

s)

LGA

0 5 10 15 20-40

-20

0

20

40

60

80

25


Current Government Rules at LGA Lead to Poor Use of Runway Resources

• Inefficient use of resources

Airports loseAirlines lose

(Low load factor/Small

Aircraft)

Airports winAirlines win

(High Load Factor/Large

Aircraft)

26







27


Why do the Airlines Schedule beyond the Maximum Safe RW Capacity with Flights that Loose Revenue?

• There is no government regulation to limit schedules for safety or compensate passengers for delays and cancellations• These were errors in the 1978 Deregulation Act

• Passenger surveys indicate that frequency and price are the most desirable characteristics of a flight

• Passengers are not told of consequences of schedule to travel predictability

• If any one airline decided to offer rational schedules, their competition will offer more frequency to capture market share• Thus, still producing delays and cancellations for all

• In Game Theory, this is called the Prisoner’s Dilemma

28







29


Part 121 (Scheduled Commercial)Accident Rates are Increasing

My filtered part-121 accidents

y = 0.0533x + 1.0647

0

0.5

1

1.5

2

2.5

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

coun

t per

milli

on o

pera

tions

Analysis from Zohreh Nazeri, PhD GMU 2007

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CATSRCATSRCATSRCATSRTrends for Incidents Associated with Accidents

Trends of the factors in incident databases• Pilot factors decreasing• Aircraft factors slowly decreasing• ATC factors increasing

Pilot primary factors in ASRS reports

y = -7.1868x + 123.330

20406080

100120140160

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

coun

t per

mill

ion

oper

atio

ns

Aircraft primary factors in ASRS reports

y = -3.8007x + 683.79

0

200

400

600

800

1000

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

coun

t per

mill

ion

oper

atio

ns

ATC primary factors in ASRS reports

y = 0.0824x + 29.716

0

10

20

30

40

50

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

coun

t per

mill

ion

oper

atio

ns

ATC incidents in FAA/OED data, Terminal

y = 1.4581x + 18.118

05

10

15202530

3540

95 96 97 98 99 00 ;01 02 03 04

coun

t per

milli

onop

erat

ions

Analysis from Zohreh Nazeri,

PhD GMU 2007

31

CATSRCATSRCATSRCATSRATC factors – Communication Errors

Top complexity factors associated with ATC factors:

• number of aircraft in airspace -- airspace design

• runway configuration -- controller experience

Top-10 traffic complexity factors associated w ith communcation errors

0.00%

10.00%

20.00%

30.00%

40.00%

other

blank

#a/c,

othe

r

#a/c

airsp

ace,

#a/c,

othe

rair

spac

e, oth

er

#a/c,

expe

rienc

e, oth

er

rwy c

onfig

, othe

rair

spac

e

#a/c,

rwy c

onfig

% c

omm

err

ors

These factors will get worse over time:

• air transportation is projected to grow for the next 10 years

• majority of controllers will retire within next few years

Analysis from Zohreh Nazeri,

PhD GMU 2007

32

CATSRCATSRCATSRCATSRAircraft factors

“Flight Control System” problems growingOther aircraft factors decreasing

Growth of aircraft problems in SDRS data

-0.7-0.6-0.5-0.4-0.3-0.2-0.1

00.10.20.3

Fligh

t Con

trol S

ystem

Nacell

e/Pylo

n atta

chmen

t

Collisi

on A

voida

nce S

ystem Wing

Compre

ssor

Assem

blyLa

nding

Gea

r

tren

d lin

e sl

op

Aircraft flight control system problems

y = 0.4037x - 0.2704

00.5

11.5

22.5

33.5

44.5

1995

1996

1997

1998

1999

2000

2001

2002

2003

coun

t per

milli

on o

pera

tions

Analysis from Zohreh Nazeri, PhD GMU 2007

33


Safety at Principle Network Nodes(i.e. Airports) is the Constraint

• Aircraft Safety Separation Time over the Runway Threshold sets the ATS capacity limits

• Critical Technical Parameters that Define Network Capacity:• Runway Occupancy Time (ROT)• Landing Aircraft Inter-Arrival Time (IAT)• Capmax = 90 sec IAT at 10-3 PSRO = 40 Arr/RW/Hr• Queuing Delay Onset at ~ 80% = 32 Arr/RW/Hr

limit for Predictable Performance

34


Queuing Delays set the Practical Capacity Limitation set by Safety Separation Standards

•Lack of Schedule Synchronization and 90 second IAT generate Queuing Delays above about 80% of Maximum Runway Capacity

THEORETICAL QUEUEING DELAY

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

DEMAND / MAX. CAPACITY

DE

LA

Y (

Min

utes

)

~ K[rho/(1-rho)]

32 Arr/RW/Hr

Cancellations begin

35


Data Analysis Process to Estimate:IAT, IAD and ROT pdf’s

Runway

Threshold

Airplane i+1

Airplane i

Aircraft Type Threshold Leave RunwayHeavy 10:23:14 10:24:04Large 10:24:28 10:25:13Large 10:26:16 10:27:12Small 10:28:32 10:29:28

. . .

. . .

. . .

Col. Clint Haynie, USA PhD., 2002

Yue Xie, PhD. 2005

36


ROT vs. IAT to find Simultaneous Runway Occupancy (SRO) Probability: est to be ~ 2 / 1000

Inter-Arrival Time (sec)

Runway Occupancy

Time(sec)

SRORegion

•Detroit Metropolitan Airport (DTW)• Freq (IAT < ROT) ~= 0.0016 in peak periods and

0.0007 overall (including non-peak periods - 1870 total samples)• IMC: 1 / 669= 0.0015 in peak periods• Correlation coefficient = 0.15 [Babak, Shortle and Sherry, 2006]

37

CATSRCATSRCATSRCATSRIt does Not Have to Be this Way

Inter-Arrival Time (sec)

Runway Occupancy

Time(sec)

New Avionics & Procedures

Existing Avionics and Slot Controls

Changes in FAA Procedures, Airport Slot Controls and New Avionics Will Improve BOTH Safety and Capacity

38

CATSRCATSRCATSRCATSRSummary on Capacity

• 40 Arrival per Runway per Hour is current Safety Maximum

• 32 Arrivals per Runway per Hour is ONSET of Queuing Delays• Using Current (OLD) Technology• Using Current (OUTDATED) ATC Procedures

• FAA has Refused to Mandate New Technology and Procedures to Reduce the Variability in IAT to Increase BOTH Safety and Capacity

39


Marginal Rate IFR Rate

Calculated Capacity (Today) and Actual Throughput

Optimum Rate

0

20

40

60

80

0 20 40 60 80

Departures per Hour

Arr

ival

s pe

r Hou

r

Calculated Capacity - Today

Facility Reported Rate - EWR(arrivals, departures per hr)

Each symbol represents actual traffic during a single hour

Infrequent Most Frequent

42, 42

0

20

40

60

80

0 20 40 60 80

Departures per Hour

Arr

ival

s pe

r Hou

r

40, 40

0

20

40

60

80

0 20 40 60 80

Departures per Hour

Arr

ival

s pe

r Hou

r

33, 33

EWR :

DoT/FAA

2004 Capacity Benchmark Report

Capacity Increase:Closer Spacing & better Schedule Synchronization

All Weather

40


• What would happen if schedules at major airports were Capped at Safe, Predictable Runway Capacity and allocated by a Market mechanism?• What markets would be served?• How would airline schedules change?

– Frequency– Equipment (#seats per aircraft)

• How would passenger demand change?– At airport– On routes

• How would airfares change?– What would happen to airline profit margins?

• How would airport and network delays be altered?

A Natural DoT – Congressional Question?Is There an Optimal Allocation of Scarce Runway Resources?

41

CATSRCATSRCATSRCATSRModeling Approach and Assumptions

• Port Authority of NY&NJ has the ability to Determine and Set an Optimum Schedule to:• Operate at Competitive Profit Margins• Maximize Passenger Throughput• Ensure an Airline Operating Profit (Max, 90%,80%)

• All Current Origin and Destination Markets are Considered• 67 Scheduled Daily Serviced Markets

• Current Market Price Elasticity Remains Constant

42

CATSRCATSRCATSRCATSRNY LGA Has 67 Daily Markets

43


Network Flow Optimization Problem

(Le, 2006)

Demand-Price Elasticity$

#

S1S2

DASPM, BTS databases

Delay Network Simulation

Flight schedulesFleet mixAverage fareFlight delays

Airline Competitive Scheduling: Modeling Framework

Auction IMC Rate:

32 Slots/Hr

44


Model Estimate of Airline Response to an All Weather Predictable Schedule Restriction

Estimate of Aircraft Up-Gauging

0

50

100

150

200

250

300

19 to 37 44 to 50 69 to 77 88 to110

117 to133

138 to158

166 to181

194 to225

Aircraft Seating Capacity

Num

ber

of D

aily

Flig

hts

Current Fleet Allocation - 1010 Flts 90% Optimum Fleet Allocation - 806 Flts

•20 % Fewer Scheduled Flights

•Increased Passenger Throughput

•Same Airfares

•Loss of 3 Unprofitable Markets

•70% Less Delay

45







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The Predicted Growth in Aviation Demand is based on Passenger Demand NOT Aircraft Operations

• Larger Aircraft will be required to meet X2 or X3 demand• Business Jet and VLJ Air Taxi Service will emerge to

compete with Commercial aviation due to current System Failure• May not be able to put the Geni back in the Bottle• Environmental Implications?

• New Aircraft (e.g. B 787) should be Environmentally Friendly (Emissions/passenger/mi.?)• US airlines are not currently ordering them due to poor financial

position• New Public Policy will be needed to Deal with these

Complex Adaptive System Problems• NEXTGEN System not addressing these issues

47

CATSRCATSRCATSRCATSRIS NGATS addressing the Problem?

• ADS-B (out), 4-D trajectories, RNP-0.1• Good but NOT ENOUGH

• Aircraft Gauge, Schedule Synchronization and Network Load Balancing will Be Required• Annual Combinatorial Clock Slot Auctions ?

• Aircraft Separation in Terminal Airspace and on the Runways MUST be REDUCED by X3!• Closely Spaced, Fully-coupled Autopilot Formation

Landings with 2 – Lane Runways?• Closely Spaced Airports need to be Cross-linked

with Runway Independent Air Transport• New Generation of Heavy Lift Helicopters?

48


Center for Air Transportation System Research Publications and Information

• http://catsr.ite.gmu.edu

– Other Useful Web Sites

• http://mytravelrights.com• http://gao.gov• http://www.airconsumer.ost.dot.gov

Air Travel at the Edge of Chaos - George Mason …catsr.ite.gmu.edu/pubs... · Air Travel at the...

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