A member of FAA Center of Excellence Air Transportation System (ATS) Analysis: Dynamic System Model of the ATS Lance Sherry (Ph.D.) Bengi Mezhepoglu (Ph.D. Candidate) 12/2005 CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH Education Analysis Ed ti A l i and d Research R h for f the th Next N t 1 Acknowledgements • Dave Knorr, Anne Yablonski (FAA) • Dan Goldner (Ventana Systems) • Mike Wambsgnass, Terry Thompson (Metron Aviation) • JP Clarke (Ga Tech), Mike Ball (UMd), Mark Hansen (UC-B) • Sherry Borener, Peggy Gervasi (JPDO) • George Donohue, John Shortle, C.H. Chen, Sasha Klein, Jonathan Drexler, Danyi Wang (GMU) 2 Summary • U.S. Domestic Air Transportation System (ATS): – amazing success story over last century – significant contributor to the U.S. economy • ATS is faced with (9) major challenges • Use Dynamic System Model of ATS to understand: – cause-effect of challenges ? – can system “self-heal” ? 3 Summary • Results of analysis: 1. ATS exhibits Time Constants and Equilibrium Points that should be taken into account in strategic plans • • Key metrics: (1) effective capacity, (2) demand 75% of capacity rule 2. Sustainability in a future ATS (e.g. NGATS) can be attained by “designing” mechanisms to: a) b) c) balance capacity and demand signal need for capacity enhancement incentivize innovation 4 Organization 1. 2. 3. 4. Success & Challenges Air Transportation System Model Results of Analysis Opportunities 5 A member of FAA Center of Excellence 1. Successes, Challenges CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH Education Analysis Ed ti A l i and d Research R h for f the th Next N t 6 Air Transportation Faces Challenges 7 Success Story – Capacity ATS Capacity 800000 700000 600000 500000 400000 300000 200000 100000 0 Years Domestic Enplanements Domestic RPMs (Millions) Domestic ASMs (Millions) 8 Success Story - Airfares Domestic Real Yield (1978 Cents) 50 Jets 45 Widebodies, Radar 40 1978 Cents 35 Hub-&-Spoke 30 25 Yield Mgmt 20 15 TFM, Internet, LCCs 10 5 0 1920 1940 1960 1980 2000 2020 Year Source: ATA (2005) Yield = Before Tax Revenue per Seat-Mile 9 Challenges ? 1. Airline Profit/Loss Cycles – 2. Equal Access – – 3. wasted resources and low predictability Environmental issues (emmissions, noise) Airport & Airspace Trust Fund eroding Airport & Airspace innovation cycle is dormant ATC innovation cycle is dormant – 9. delays and cancellations Congestion • 5. 6. 7. 8. Airlines consolidating service to high socio-economic metro areas Eroding access from small communities (Essential Air Service subsidies) Passenger Experience – 4. Finding economic equilibrium? Modernization efforts effectively stalled ATC labor issues (salary, staffing) 10 Challenges ? – Airline Finances 20,000,000 140,000,000 15,000,000 120,000,000 10,000,000 100,000,000 5,000,000 80,000,000 0 60,000,000 -5,000,000 40,000,000 -10,000,000 Annual Revenues Cum Net Proft/Loss & O perating Proft ($) Airline Finances 20,000,000 -15,000,000 -20,000,000 0 Cum Net Profit/Loss Source: ATA (2005) Annual Operating Profit ($K) Operating Revenues ($K) Symptom, not a cause 11 Challenges – Passenger Experience? 800 450 Average = 1.5% FLL-ORD, PHL-CLT 700 600 Number of Routes per Day Gate-to-Gate Velocity (knots) 400 Velocity = 54.874Distance 350 300 250 2 R = 0.9068 200 150 100 0.2859 S A N - B WI S LC - B WI LA S - H O U 50 500 0 0 - 1% 1 - 2% 2 - 3% 3 - 4% 4 - 5% 5 - 6% 6 - 7% 7 - 8% 8 - 9% Percentage of Flights Cancelled on Route 400 300 200 100 0 Origin to Destination Distance (nm) Data Prepared By: Danyi Wang 12 Challenges – Passenger Experience Passenger Delay per Enplanement (mins) 120 100 JFK-ORD JFK-ORD PHL-EWR JFK-PHL 80 EWR-PHL EWR-PIT JFK-PIT 60 PHL-JFK STL-PIT PHL-STL EWR-BWI JFK- LAS-M CO M CO-LAS ORD-JFK 40 LA S-DCA DCA -LA S 20 0 0 500 1000 1500 2000 2500 Route Distance 13 Challenges ? - Congestion • Number of Flights 250 Unimpeded Actual Block Time 110 mins, (σ = 11 mins) 200 • Scheduled Block Time 124 mins, (σ = 7 mins) Median Actual Block Time 133 mins 150 Mean Actual Block Time 140 mins, (σ = 43mins) 100 • • Properties of system adds average 30 mins to a 110 minute flight (28%) Properties of system results in significant variability that makes planning difficult – Actual µ/σ = 3.25 – Schedule µ/σ = 20 Congestion fuel costs to airlines = 23% of revenue from flight Adjusting schedule to mean actual block time costs airline 12% in aircraft utilization 50 0 100 90 200 150 190 290 >390 Atlanta – O’ Hare Actual Block Time (min) Schaar, Drexler, Sherry (2005) 14 Challenges ? – A&ATF Airport & Airway Trust Fund $18,000 $16,000 $14,000 $M $12,000 $10,000 $8,000 $6,000 $4,000 $2,000 - Expenses Source: ATA (2005) Income Balance Ticket Tax Income Shift to RJs, results in more ATC operations, A&TFless revenue 15 Challenges ? – ATC Labor ATSC Hiring 25,000 # Candidate + Developmental + Certified ATCS on Payroll Shortfall in Certified ATCS # ATSC 20,000 15,000 FAA-NATCA Target Staffing Level # Certified ATCS 10,000 5,000 # Developmental ATCS #ATCS Attrition = #ATCS Hired ATSC in Excess of Target Level of Staffing on Payroll 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year 16 Addressing the Challenges ? • Are Challenges symptoms or causes? – What are cause-effect relationships? • What is the systemic structure of the industry? – Can this knowledge explain behavior? – Can this knowledge focus R&D? – How do policies, regulations, and procedures affect the system – How does NGATS affect these success and challenges 17 A member of FAA Center of Excellence 2. Air Transportation System CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH Education Analysis Ed ti A l i and d Research R h for f the th Next N t 18 Air Transportation System • Air Transportation System is … – Layers of networks – Networks composed of agents – Agents: • Distributed • Autonomous • Networks and agents operating with own objective functions – Reinforce/Undermine each other • Networks exhibit: – stochastic behavior – operate in non-equilibrium state • Economically • System Performance 19 ATS Stakeholders STAKEHOLDERS Passengers and Cargo • • Provide capacity for air transportation of passengers and cargo Scheduled Flights (routes, frequency and aircraft) Airports & Airways • • Provide capacity for Airline’s Scheduled Flights Airways and their navigational aids, Flightlevels, Runways, Gates, …etc. Air Traffic Control • Provide sequencing and separation of air traffic (flow) Public Natural Resources • Optimize costs, time and reliability Purchase air transportation services Airlines • OBJECTIVE FUNCTIONS Provides “natural resources” consumed by air transportation Profit Marketshare in competitive marketplace Maximize economies of scope and scale Regional Economy Effective Capacity Congestion Throughput (Delays) Airports & Airspace Utilization Accidents/Incidents Workload Capacity Rate of Utilization Rate of Replenishment 20 Relationship between Stakeholders PUBLIC NATURAL RESOURCES NOISE, EMMISIONS FROM TRAFFIC AIR TRAFFIC CONTROL SEQ. & SEP. OF FLOW OF TRAFFIC CAPACITY FOR ABSORBING NOISE EMISSIONS FROM TRAFFIC FLOW OF TRAFFIC AIRSPACE & AIRPORTS GATES, RUNWAYS, AIRWAYS,… SCHEDULED OPERATIONS AIRLINES & OTHER USERS OF THE NAS AVAILABLE SEATS UNCONSTRAINED TRIP DEMAND PASSENGERS & CARGO AIR TRANSPORTATION SYSTEM 21 Variability in Demand • Environment • Demographics S Traffic Flow Service Providers: Air Traffic Control (TFM, AOCs, ARTCCs, TRACONs, Towers) D • Congestion • Accident prevention • Weather • Budgets, Labor, Contract • Technology S Air Transportation Service Providers: Airlines D • Seasonal, Day-of-Week, Hour-of-Day, • Income Elasticity • Price Elasticity D • Competition, Prices of competing modes • Supply Chain price (e.g. Fuel) • Technology & Labor costs • Supply of resources (e.g. gates, aircraft) S Infrastructure Service Providers: Airports and Airspace Air Transportation Consumers: Passengers & Cargo AIR TRANSPORTATION SYSTEM 22 A member of FAA Center of Excellence 3. ATS Dynamics 3-1) Time Constants 3-2) Demand and Capacity Balancing Feedback Loops 3-3) System Equilibrium CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH Education Analysis Ed ti A l i and d Research R h for f the th Next N t 23 Dynamical System Model Market Forces Market Forces Value of Substitute Service/Product Supply of Service/Product + - Control Law: Price Setting through “Price Curve” + - Plant: Consumer Demand through “Demand Curve” Demand for Service Product Phase-plane Plant exhibits nonlinear dynamics (e.g. price elasticity) Equilibrium No-equilibrium 24 Time Constants ? Changes in Pax & Cargo demand • Changes in Airlines supply – Routes, Frequency, Gauge • τ = Weeks to 3 -6 Months D – τ = Weeks to Months S • Traffic Flow Service Providers: Air Traffic Control (TFM, AOCs, ARTCCs, TRACONs, Towers) : e Providers ic rv e S re Infrastructu d Airspace Airports an Changes in A&A supply – Sector changes • τ = 3-6 months, 2 years • τ = 10 – 30 years • Changes in ATC – Staffing, Sectors D – Runways, gates, routes, Crz FLs ice tion Serv ta r o p s n a Air Tr s: Provider Airlines S • S • τ = 3 years D – Increased Fleet Air Transportation Consumers: Passengers & Cargo • τ = 7 – 10 years AIR TRANSPORTATION SYSTEM 25 Pax v. Seats Feedback Loop (1) • Strong feedback-loop – Airfares set by airlines based on demand for available seats – Scarce resources (seats) result in higher prices Air Transportation Service Providers: Airlines Seat Supply P D • Feedback distorted by: – Hyper-competition for marketshare – Monopolies on given routes – Bankruptcy protection – Network integrity – Use-it-or-Lose it rules • Innovation Rate – Very high Airfare Enplanements – Loop has no external costs Seats • Revenue Management D P Air Transportation Consumers: Passengers & Cargo AIR TRANSPORTATION SYSTEM 26 Flights v. Slots - Feedback Loop (2) • Weak feedback-loop – Fees and Taxes based on: • Revenue-neutrality • Congestion (delay) costs Air Transportation Infrastructure: Airports & Airspace Airspace & Airports Supply P – Weak Airspace & Airports Capacity D • Fees & Taxes • Congestion Costs to airlines • not responsive to market • Feedback distorted by: – Absence of value of scarce resource • Scheduled Flights – FAA F&E Budget – Costs borne by (third party) passengers – Administrative measures (slots, uni-laterals) Innovation Rate – Slow – Negligible productivity improvements at chokepoints D P Air Transportation Service Providers: Airlines 27 Slots v. Sep. - Feedback Loop (3) – Contract, budget & staffing plans determine staffing levels based on forecasts – Costs borne by (third party) passengers (& taxpayers) – Absence of value of scarce resource P D • Salaries, budgets, staffing plans • Contract • Innovation Rate – Slow – Negligible productivity improvements • # aircraft per sector in 15 mins Demand for Flow Control • Feedback distorted by: Flow Supply Flow Control Productivit y • Weak feedback-loop Traffic Flow Service Providers: Air Traffic Control (TFM, AOCs, ARTCCs, TRACONs, Towers) D P Air Transportation Infrastructure: Airports & Airspace 28 Slots v. NPR - Feedback Loop (4) • Feedback distorted by: – Absence of value of scarce resource – Global and local issue PNR Supply P D • Costs borne by public Demand for Natural Resources – Capacity and Rate-ofReplenishment is under debate – Costs borne by (third party) public – Regulations (noise abatement, engine upgrades) Public Natural Resources: Air & Water Quality, Noise Supply of Natural Resources • Weak feedback-loop D • Innovation Rate – High in some areas – Driven by forces other than scarcity of resources P Air Transportation Infrastructure: Airports & Airspace 29 Feedback Loops Infrastructure: Airports and Airspace Balancing Mechanism (staffing, salaries, bu dgets) Demand Service Providers: Traffic Flow Natural Resource Providers: Public/Gov ernment Supply Service Providers: Airlines (Flights) ism Balancing Mechan tax, t ke tic , es fe (landing admin measures) Infrastructure: Airports and Airspace Supply Demand Consumers: Passengers & Cargo (Trips) Demand Balancing Mechan ism (airfares, subsidies ) Service Providers: Airlines (Seats ) Supply Excess Demand Excess Supply AIR TRANSPORTATION SYSTEM 30 Feedback Loops • Absence of feedback loops prevents: 1. Maximizing use of scarce resources • Exacts costs on third parties not part of loop (Golaszewski, 2005) – – delays, workload, overtime, sick-leave, pollution not a problem until resource becomes scarce 2. Signaling for improvement • • Crisis results in action 75% of capacity rule (Miller and Clarke, 2005) 3. Innovation • • • absence of value of resource (given demand) prevents return-on-investment (ROI) absence of ROI prevents venture capital (VC) absence of VC prevents best-minds from investing time & energy 31 Equilibrium ? • Contributes to challenges to ATS ice tion Serv ta r o p s n a Air Tr s: Provider Airlines D – Time constants – Weak feedback loops D • ATS is unable to reach and maintain equilibrium due to: S – ability to anticipate changes : e Providers ic rv e S re Infrastructu d Airspace Airports an S • No shortage/excess D – supply = demand Traffic Flow Service Providers: Air Traffic Control (TFM, AOCs, ARTCCs, TRACONs, Towers) S • Equilibrium: Equilibrium Air Transportation Consumers: Passengers & Cargo AIR TRANSPORTATION SYSTEM 32 A member of FAA Center of Excellence 4. Opportunities CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH Education Analysis Ed ti A l i and d Research R h for f the th Next N t 33 Opportunities 1. Create awareness and educate decisionmakers, media, and public • Gross mis-understandings exist, must be addressed • NAS Strategy Simulator 2. Plans & budgets should incorporate dynamics of model • time-constants, equilibrium points • Key metrics: (1) effective capacity, (2) demand • 75% of capacity rule 34 Opportunities 3) Sustainability in future ATS (e.g. NGATS) can be achieved by including in the specification of mechanisms to • balance existing supply with demand • • • Establish property rights and liability (Coase, 1988) signal need for capacity enhancement incentivize innovation, renewal, & expansion • Airports & Airspace, Air Traffic Control, Public Natural Resources 35 A member of FAA Center of Excellence Thank you Questions? Lance Sherry - lsherry@gmu.edu, 703-993-1711 CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH Education Analysis Ed ti A l i and d Research R h for f the th Next N t 36