CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH. NASA Ames Director s Forum November 16, 2007

Air Travel at the Edge of Chaos George L. Donohue, Ph.D. Professor Systems Engineering and Operations Research Director of the Center for Air Transportation Systems Research Volgenau School of Information Technology and Engineering NASA Ames Director s Forum November 16, 2007 CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH George L. Donohue 2007

Outline 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 2

What 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 3

Some Little Known Facts Modern Jet Aircraft Gate-to-Gate Travel Time is the Same or Longer than 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 4

Overscheduled Airports are the Problem: Average Delay per Flight Ordered by Arrival Delay at Outbound Destination. (minute) [Ning Xu GMU 2007] Airport Delay 40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0-5.0-10.0-15.0-20.0 ATL JFK PHL MSP ORD MIA EWR DTW DFW IAD CLT FLL LGA MEM BOS MCO DCA BWI IAH SEA TPA DEN CLE PIT LAS MDW STL CVG PHX SFO LAX PDX SLC SAN Delays per Flight (minute) Early-arrival Gap Inbound Delay Airborne Delay Arrival Delay at Outbound Dest. 34 OEP Airport Summer 2005 at 34 OEP Airports 5

Delay Incurred at Major Airports Propagate Network Wide (Summer 2005) Total Delay Ordered by Arrival Delay at Outbound Destination. (minute) 1450000 1250000 1050000 850000 650000 450000 250000 50000-150000 -350000-550000 ATL ORD DFW EWR PHL MSP DTW DEN BOS JFK LGA IAH IAD CLT MCO DCA PHX MIA LAX LAS BWI SEA FLL CVG CLE MDW SFO TPA PIT STL SLC SAN MEM Total Delays (minute) PDX 20,000 Flight Hours Airport Delay Early-arrival Gap Inbound Delay Airborne Delay Arrival Delay at Outbound Dest. 6 34 OEP Airport [Ning Xu GMU 2007]

NYNJ comparison to Comparable European Airports Total Total Average Delays Airport Movements Passengers Minutes 2005 2000 2005 2000 2006 Frankfurt, Gr (FRA) 490,147 458,731 52,219,412 49,360,630 2.7 London, 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 28.8 Amsterdam, 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 23.4 Munich (MUC) 398,838 - <29,000,000 1.8 New York Kennedy (JFK) <353,000 <384,000 41,885,104 32,856,220 24.3 Madrid, Sp (MAD) 415,677 <384,000 41,940,059 32,893,190 1.8 Data taken from ACI-NA, EC PR2006 and FAA ASPM 7

Air Transportation System (ATS) is a CAS with 6 Interacting Network Layers The ATS is a Public - Private Partnership with conflicting objective functions: Public Commerce and safety; interest groups Private Profit maximization Passenger/Cargo Layer (Delays, Cancellations) Airline Layer (Routes, Schedules, A/C size) TSA/FAA Layer (ATC Radar, Radios, Ctr s, Unions) Weather Layer (Thunderstorms, Ice Storms) Physical Layer (i.e. Cities, Airports, Demographics) Government Regulatory Control Layer 8

Air Transportation System is Designed to Move Passengers and Cargo Passenger Tier Performance = f (Vehicle Tier Performance, Passenger Factors i.e. Aircraft Gauge, Load Factor, Cancellations) 9

Passenger 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% 10 Close Network of OEP35 Airport in 2004

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% 11 Close Network of OEP35 Airport in 2004

Top 20 Worst Airports in the US: Passenger Quality of Service Metric Year 2004 2005 2006 Average of 2004 to 2006 12 Rank Prob. Of PaxDelay >45 min Airports Prob. Of PaxDelay >45 min Airports Prob. Of PaxDelay >45 min Airports Prob. Of PaxDelay >45 min Airports 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% D. Wang, GMU PhD. In Progress

Many Highly Congested Airports can Shift Passengers to other Large Airports Connecting Airport Passengers % Chicago O'Hare 59 Newark NJ 32 NY LaGuardia 8 NY JFK 40 Philadelphia 38 Atlanta 66 Boston 15 Miami 55 Washington Dulles 53 Dallas/Fort Worth 60 13 FAA 2006 NPIAS

Airline Load Factors are Increasing Percent Aircraft Seats Occupied (Average) 90 85 80 75 70 65 60 55 50 Load Factor (Anticipated) Load Factor ATA Historical Data 45 1960 1970 1980 1990 2000 2010 Year 14

GMU Model Projects Passenger Delays to Greatly Exceed 2000 delays by 2010 Total Passenger Delays Hours (millions) 160 140 120 100 80 60 Delayed Flights Cancelled Flights Poly. (Delayed Flights) Poly. (Cancelled Flights) 40 20 15-1998 2000 2002 2004 2006 2008 2010 2012 Year D. Wang 2007

Annual Passenger Enplanements Predicted to be Lost: FAA Forecast to 2025 Annual Projected Enplanements Foregone Because of Airport Capacity Constraints 30 Annual Enplanements Lost (Millions) 25 20 15 10 5 All available landing slots fully utilized regardless of congestion EWR JFK ORD LGA Optimistic: All Planned Airport Improvements Occur 2025 2015 2005 0 ATL BOS BWI CLE CLT CVG DCA DEN DFW DTW EWR FLL HNL IAD IAH JFK LAS LAX LGA MCO MDW MEM MIA MSP ORD PDX PHL PHX PIT SAN SEA SFO SLC STL TPA 16 Airports FAA 2005 TAF & 2004 Benchmark

Estimated Annual Cost to US (Lost Consumer Surplus, 2005$) due to Expected Airport Capacity Limitations $25 Annual Cost to US Economy ($B) $20 $15 $10 $5 --FAA Assumptions on Growth in Airport Operations --Boeing Passenger Growth Assumptions: 3.6% per year --Aircraft Upgage: 5% in 2015, 10% in 2025 Assumes: $200/segment ticket Price Elasticity = -1 CY2015, All A/P Improvements CY2015, No A/P Improvements CY2025, All A/P Improvements CY2025, No A/P Improvements $0 100% 95% 90% 85% 80% 17 Usable NAS Capacity (%) Shaver 2007

Minimum Congestion Cost is a function of NEXTGEN Technology Effectiveness and Network Efficiency Annual Congestion Cost ($B) $20 $15 $10 $5 $0 Caution: Some Costs Not Included Sum of Costs ($B) Costs Resulting from Passenger Delays and Flight Cancellations Consumer Surplus Costs Resulting From Limiting Airport Slots 0.8 0.85 0.9 0.95 1 Congestion Factor 18

Outline 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 19

Jet Blue and Delta AL are Competing for the JFK Market: Passengers Pay the Price in Flight Delays and Cancellations JFK Summer 2007 Departures 25 FAA Announced Departure Rate (weekday AVG +/- 2) Airline's Scheduled Departures Flight Departures per 15 Minure Epoch 20 15 10 5 0 5 AM 10 AM 3 PM 8 PM Midnight 0 20 40 60 80 100 120 24 Hours in 15 min. Epochs 20

Reduction in Average Number of Aircraft Seats by Airport All Departures 200 180 160 140-15.5% 120 100-12.7% -0.1% -6.8% 9.9% -18.9% -10.4% -11.4% -4.2% 80 60 40 20 0 ATL DFW EWR IAD IAH JFK LGA ORD PHL July 2002 July 2007 Dorothy Robyn The Brattle Group 21

JFK Average Delay Profile (2006) JFK Delay per Flight (minutes) 80 60 40 20 0-20 -40 0 5 10 15 20 Time of Day (hour) 22

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 23

Delay per Flight (minutes) NYNJ Airport with Current Slot Controls: LGA 2004 2006 (DOT Data) 80 60 40 20 0-20 LGA Arrivals per Hour 60 40 20 Optimum Rate Calculated Capacity (Today) and Actual Throughput 39,39 Calculated Capacity - Today Facility Reported Rate - LGA (arrivals, departures per hr) Infrequent Most Frequent Each symbol represents actual traffic during a single hour -40 0 5 10 15 20 Time of Day (hour) 0 0 20 40 60 Departures per Hour Marginal Rate IFR Rate 60 37,37 60 37,37 Arrivals per Hour 40 20 Arrivals per Hour 40 20 24 0 0 20 40 60 Departures per Hour 0 0 20 40 60 Departures per Hour

Current Government Rules at LGA Lead to Poor Use of Runway Resources Inefficient use of resources Airports win Airlines win (High Load Factor/Large Aircraft) Airports lose Airlines lose (Low load factor/small Aircraft) 25

Outline 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 26

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 27

Outline 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 28

Part 121 (Scheduled Commercial) Accident Rates are Increasing My filtered part-121 accidents Analysis from Zohreh Nazeri, PhD GMU 2007 29 c ount per million operations 2.5 2 1.5 1 0.5 0 y = 0.0533x + 1.0647 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Trends for Incidents Associated with Accidents Trends of the factors in incident databases Pilot factors decreasing Aircraft factors slowly decreasing ATC factors increasing Analysis from Zohreh Nazeri, PhD GMU 2007 30 count per million operations count per million operations Pilot primary factors in ASRS reports 160 140 120 100 80 60 40 20 0 50 40 30 20 10 0 y = -7.1868x + 123.33 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 ATC primary factors in ASRS reports 1995 1996 y = 0.0824x + 29.716 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 count per million operations Aircraft primary factors in ASRS reports 1000 800 600 400 200 count per million operations 0 1995 1996 y = -3.8007x + 683.79 1997 1998 1999 2000 2001 2002 2003 2004 2005 ATC incidents in FAA/OED data, Terminal 40 35 30 25 20 15 10 5 0 2006 y = 1.4581x + 18.118 95 96 97 98 99 00 ;01 02 03 04

ATC factors Communication Errors Top complexity factors associated with ATC factors: number of aircraft in airspace -- airspace design runway configuration -- controller experience 31 % comm errors Top-10 traffic complexity factors associated w ith communcation errors 40.00% 30.00% 20.00% 10.00% 0.00% other blank #a/c, other #a/c airspace, #a/c, other rwy config, other airspace, other #a/c, experience, other These factors will get worse over time: airspace #a/c, rwy config 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 Aircraft factors Flight Control System problems growing Other aircraft factors decreasing 0.3 0.2 0.1 0-0.1-0.2-0.3-0.4-0.5-0.6-0.7 Growth of aircraft problems in SDRS data 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 Aircraft flight control system problems Flight Control System Nacelle/Pylon attachment Collision Avoidance System Wing y = 0.4037x - 0.2704 Compressor Assembly Landing Gear trend line slop count per million operations 1995 1996 1997 1998 1999 2000 2001 2002 2003 Analysis from Zohreh Nazeri, PhD GMU 2007

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: 33 Runway Occupancy Time (ROT) Landing Aircraft Inter-Arrival Time (IAT) Cap max = 90 sec IAT at 10-3 P SRO = 40 Arr/RW/Hr Queuing Delay Onset at ~ 80% = 32 Arr/RW/Hr limit for Predictable Performance

Queuing Delays set the Practical Capacity Limitation set by Safety Separation Standards THEORETICAL QUEUEING DELAY Lack of Schedule Synchronization and 90 second IAT generate Queuing Delays above about 80% of Maximum Runway Capacity DELAY ( Minutes ) 70.00 60.00 50.00 40.00 30.00 20.00 10.00 Cancellations begin ~ K[rho/(1-rho)] 32 Arr/RW/Hr 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 DEMAND / MAX. CAPACITY 34

Data Analysis Process to Estimate: IAT, IAD and ROT pdf s Airplane i Threshold Airplane i+1 Runway Aircraft Type Threshold Leave Runway Heavy 10:23:14 10:24:04 Large 10:24:28 10:25:13 Large 10:26:16 10:27:12 Small 10:28:32 10:29:28......... 35 Col. Clint Haynie, USA PhD., 2002 Yue Xie, PhD. 2005

ROT vs. IAT to find Simultaneous Runway Occupancy (SRO) Probability: est to be ~ 2 / 1000 Runway Occupancy Time (sec) SRO Region Inter-Arrival Time (sec) 36 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]

It does Not Have to Be this Way Runway Occupancy Time (sec) New Avionics & Procedures Existing Avionics and Slot Controls Inter-Arrival Time (sec) 37 Changes in FAA Procedures, Airport Slot Controls and New Avionics Will Improve BOTH Safety and Capacity

Summary 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 38

Calculated Capacity (Today) and Actual Throughput Optimum Rate Arrivals per Hour 80 60 40 20 42, 42 Calculated Capacity - Today Facility Reported Rate - EWR (arrivals, departures per hr) Infrequent Most Frequent Each symbol represents actual traffic during a single hour 0 0 20 40 60 80 Departures per Hour Marginal Rate IFR Rate Capacity Increase: Closer Spacing & better Schedule Synchronization 80 80 All Weather 39 Arrivals per Hour 60 40, 40 40 20 0 0 20 40 60 80 Departures per Hour Arrivals per Hour 60 33, 33 40 20 0 0 20 40 60 80 Departures per Hour EWR : DoT/FAA 2004 Capacity Benchmark Report

A Natural DoT Congressional Question? Is There an Optimal Allocation of Scarce Runway Resources? 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? 40 How would airport and network delays be altered?

Modeling 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 41

NY LGA Has 67 Daily Markets 42

Airline Competitive Scheduling: Modeling Framework ASPM, BTS databases Demand-Price Elasticity $ Auction IMC Rate: 32 Slots/Hr S 1 S2 D Network Flow Optimization Problem # Flight schedules Fleet mix Average fare Flight delays Delay Network Simulation 43 (Le, 2006)

Model Estimate of Airline Response to an All Weather Predictable Schedule Restriction Estimate of Aircraft Up-Gauging 300 250 Current Fleet Allocation - 1010 Flts 90% Optimum Fleet Allocation - 806 Flts 20 % Fewer Scheduled Flights Number of Daily Flights 200 150 100 50 Increased Passenger Throughput Same Airfares Loss of 3 Unprofitable Markets 0 70% Less Delay 19 to 37 44 to 50 69 to 77 88 to 110 117 to 133 138 to 158 166 to 181 194 to 225 Aircraft Seating Capacity 44

Outline 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 45

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 46

IS 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? 47

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 48