1. 1 Ames Research Center Incredible Challenges of the Air Traffic Control System Modeling, Control and Optimization in the National Airspace System Dr. Banavar Sridhar NASA Ames Research Center Moffett Field, CA 94035 Banavar.Sridhar@nasa.gov UCSC Seminar May 27, 2004

2. 2 Ames Research Center Outline What is the National Airspace System (NAS)? –Scope –Influence on the economy –Transformation –Comparison with other networks Technology: Research in Traffic Flow Management (TFM) –Strategic flow models –FACET simulation and modeling capability Transformation of the NAS Questions?

3. 3 Ames Research Center Visualization of Air Traffic Data

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5. 5 Hierarchy in TFM Centralized command and control structure Command Center, Herndon, VA 20 Centers 830 high and low-altitude sectors

6. 6 Ames Research Center Time-Scales in Air Traffic Management Ref: Boeing/Aslaug Haraldsdottir

7. 7 Ames Research Center Inter-Center Traffic Flow ZSE ZLC ZMP ZAU ZOB ZNY ZBW ZOA ZDV ZKC ZME ZID ZDC ZLA ZABZFW ZTL ZHU ZJX ZMA

8. 8 Ames Research Center TFM problem Capacity –Theoretical maximum flow rate supported by the separation standard Throughput –Rate of flow realized in operation Efficiency –How close is throughput to capacity? Objective –Maximize flow rate to meet traffic demand

9. 9 Ames Research Center Types of Control (TFM actions) Ground Delay Program –Controlling aircraft departure time to manage aircraft arrival rates Metering (Miles-in-Trail) –Controlling flow of aircraft into a center by imposing flow restrictions on aircraft one or more centers away Reroutes –Congested En-route area –Weather –Special Use Airspace Playbook –Effort to provide a common understanding of re-routing strategy under previously defined situations

10. 10 Ames Research Center Transforming the NAS

11. 11 Ames Research Center September 11, 2001 Chronology of events 8:45 a.m. A large plane crashes into World Trade Center north tower. 9:03 a.m. A second plane crashes into World Trade Center south tower. 9:17 a.m. FAA shuts down all New York City area airports. 9:40 a.m. FAA grounds civilian flights 10:24 a.m. FAA reports that all inbound transatlantic aircraft flying into the United States are being diverted to Canada. 12:30 p.m.: The FAA says 50 flights are in U.S. airspace, but none are reporting any problems.

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13. 13 Ames Research Center Commercial Transport Enplanements 0.0 100.0 200.0 300.0 400.0 500.0 600.0 700.0 800.0 0506070809101112131495969798990001020304 Large Air Carrier Passenger Enplanements (Millions) Calendar Year ForecastActual Source: 1990-2002: U.S. Air Carriers, Form 41, U.S. DOT; 2003-2014 FAA Forecasts

14. 14 Ames Research Center System Reaching Saturation Target Year * Source: LMI, Alternatives for Improving Transportation Throughput and Performance, March 2002

15. 15 Ames Research Center * Source: LMI, Alternatives for Improving Transportation Throughput and Performance, March 2002 What is at stake in air transportation? Lost growth and output from air transportation due to demand outstripping capacity* –Unserved demand of 180 billion Revenue Passenger Miles (RPMs) resulting lost annual economic output of $23 billion by 2015 ($23B does not include additional impact of lost user productivity) –Major policy / operational alternatives within the current air transportation architecture recaptures only a small fraction of unserved demand and economic output Large, continuing security costs to protect the system from acts of terrorism –Difficult to measure efficacy Rising costs, rising frustrations, lost opportunities

16. 16 Ames Research Center What makes NAS different? Safety is paramount Human-in-the-loop decision making at all levels System capacity limits established by human performance Changes need to be done while the system is in operation Difficulty in modeling user reaction to events Availability/absence/uncertainty of information Need to get consensus among various parties: FAA, unions, airlines, aircraft manufacturers, etc. Status of automation/decision support tools

17. 17 Ames Research Center Strategic Flow Models

18. 18 Ames Research Center Outline Strategic Flow Models Linear Time-variant Dynamic System representation Flow Matrix Forcing Function Example Bounds on the Model Concluding remarks

19. 19 Ames Research Center Traffic Flow Models Detailed models –Useful for developing algorithms affecting individual aircraft –Controller/Traffic Manager decision support tools Aggregate models –Useful for understanding the general behavior of the system –Effectively address system uncertainties and long term behavior DetailedAggregate DeterministicCTAS, FACET, CRCTFlow models StochasticSector CongestionQueuing models

20. 20 Ames Research Center Traffic Flow Different CentersAtlanta Center on different days

21. 21 Ames Research Center Linear Time-Varying Dynamic Traffic Flow Model

22. 22 Ames Research Center A Matrix (May 6, 2003: 6 hour average, 5-11P.M, PST)

23. 23 Ames Research Center Variation of A Matrix Daily Variation: May 6,7,8 2003 5-11 P.M Variation during May 6: 11P.M- 5A.M, 5-11 A.M, 11A.M-5 P.M

24. 24 Ames Research Center Variation of A Matrix During May 6, 2003 5-11 P.M Hourly Variation Two-Hour Variation

25. 25 Ames Research Center Modeling A(k) Constant for different time intervals

26. 26 Ames Research Center Normalized mean and standard deviation of Error

27. 27 Ames Research Center Modeling of the forcing function: (Bu+Cw) Departure Counts (May 6, 2003: Every 10 Minutes)

28. 28 Ames Research Center Effect of using A from previous days Atlanta Center (ZTL) Traffic Counts for May 8, 2003 predicted using May 7 and May 6 flow matrices

29. 29 Ames Research Center Departure Counts (May 6-8, 2003: Every 10 Minutes) May 6May 7May 8

30. 30 Ames Research Center Modeling departures using mean value

31. 31 Ames Research Center Error Bounds for Model

32. 32 Ames Research Center Modeling departure errors as gaussian

33. 33 Ames Research Center Concluding Remarks Described linear time varying models to represent traffic flow for developing strategic TFM decisions. Linear dynamic traffic flow system model with a slowly varying transition matrix and Gaussian departure representation adequately represents traffic behavior at the Center-level. Error bounds around nominal traffic counts in the Centers was described. Numerical examples presented using actual traffic data from four different days to demonstrate the model characteristics. Advantages –Unlike trajectory-based models, these models are less susceptible to uncertainties in the system, –The model order is reduced by several orders of magnitude from 5000 aircraft trajectories to 23 states at any given time –Tools and techniques of modern system theory can be applied to this model because of its form. Capabilities of this class of models for strategic traffic flow management will be explored in the future.

34. 34 Ames Research Center Future ATM Concepts Evaluation Tool (FACET)

35. 35 Ames Research Center Future ATM Concepts Evaluation Tool (FACET) Environment for exploring advanced ATM concepts Balance between fidelity and flexibility –Model airspace operations at U.S. national level (~10,000 aircraft) –Modular architecture for flexibility –Software written in “C” and “Java” programming languages »Easily adaptable to different computer platforms »Runs on Sun, PC and Macintosh computers 3 Operational Modes: Playback, Simulation, Hybrid Used for visualization, off-line analysis and real- time planning applications

36. 36 Ames Research Center FACET Architecture Applications Air and Space Traffic Integration Airborne Self- Separation Data Visualization Direct-To Analysis Dynamic Density System-Level Optimization Traffic Flow Management ETMS/ASDI NOAA Winds Flight plans & Positions Climb Cruise Descent Centers Sectors Airways Airports Aircraft Performance Data Adaptation Data Traffic & Route Analyser User Interface Route Parser & Trajectory Predictor Weather Historical Database

37. 37 Ames Research Center FACET Displays Traffic 3-DConvective Weather Winds

38. 38 Ames Research Center ATL Arrivals (Purple) and Departures (Green)

39. 39 Ames Research Center FACET Display 16 17

40. 40 Ames Research Center Severe Weather Playbook Reroutes (Eastbound Traffic over Watertown)

41. 41 Ames Research Center Alternative effects of TFM actions Nominal Local Reroute MIT Local Reroute Playbook A D B C B

42. 42 Ames Research Center Integrated traffic counts in ZMP Sector 16 [A] Nominal Counts, [B] Playbook Reroute, [C] Playbook + MIT, [D] Playbook + MIT+Local Reroute.

43. 43 Ames Research Center EWR and LGA Delay Contours

44. 44 Ames Research Center FACET for AOC Applications March 2001: request by Aircraft Dispatcher’s Federation (ADF) team to increase NASA research FACET modified to work with Aircraft Situation Display to Industry (ASDI) data Developed a version of FACET for AOC use  Enable efficient operations planning by AOC –Risk analysis –Departure planning and congestion assessment –Integration with weather  Commercial Technology Office to license the software to Flight Explorer (FACET release in FE 6.0, October 2004)

45. 45 Ames Research Center Comments from Airline Dispatchers “I usually (almost always) plan for the worst case scenario. The ability to tailor fuel uplift to individual flights with a very high degree of confidence in the probability of en route delay is worth tens of millions of dollars to the airlines. It costs me about $400,000 a year to carry one additional minute of fuel on each flight. If I am carrying an average of 35 minutes, and I really only need a system-wide average of 15 minutes, that would be worth $8 million per year to my airline alone.” “I would find the predictive data very helpful in planning routing and fuel load.” “The concept of alerting a dispatcher regarding ATC sector overload and inbound ATC reroutes is an excellent idea.” “To the dispatcher at the desk, I think it would give him a huge advantage to see, understand, plan, fuel and brief the crews on possible ATC initiatives based on volume issues.” “FACET would be great because when the Command Center says, or the ATC community says “These are your three options,” we could say: “You know, you might want to consider a fourth option here that we could game or model on FACET.” “We’ve been asking for a common situation display for a long time. This may be the basis for it.”

46. 46 Ames Research Center Transformation of the NAS

47. 47 Ames Research Center Commission on the Future of the United States Aerospace Industry Recommendations: #2:“The Commission recommends transformation of the U.S. air transportation system as a national priority.” Rapidly deploy a new highly automated ATM system #3“The Commission recommends that the U.S. create a space imperative. #9“The Commission recommends that the federal government significantly increase its investment in basic aerospace research, which enhances U.S. national security, enables breakthrough capabilities, and fosters an efficient, secure and safe aerospace transportation system.”

48. 48 Ames Research Center Strategic Plan & Perf. Goals Strategic Plan & Perf. Goals Strategic Plan & Perf. Goals Strategic Plan & Perf. Goals Strategic Plan & Perf. Goals Strategic Plan & Perf. Goals DoD FAA Strategic Plan & Perf. Goals Strategic Plan & Perf. Goals OEP CIP Infra. Plan Infra. Plan R&D Plan R&D Plan NASA DHS Aviation System Joint Program Office Aviation System Joint Program Office As Required As Required As Required Executive Board R&D Plan R&D Plan R&D Plan R&D Plan National Plan National Plan R&D Plan R&D Plan Pgm. Plan Pgm. Plan JPO develops and maintains National Transformational Plan which includes: –Associated policies, technology, processes –Overall operational concepts –Supporting research –Implementation strategies –Policy and implementation commitments Partners in Development of National Plan for the Future NAS

49. 49 Ames Research Center Time Capability Defining a Transformational System Future NAS (initial design space ) Current NAS Transition-1 NAS Transition-2 NAS Transition space Future NAS

50. 50 Ames Research Center Issues in the transformation of NAS Automation –Need –Impact Human Factors Policy –Regulations –Certification Equity –Allocation of scarce resources –Sharing of information Cost of equipment Integration with existing systems Software verification and validation