1. CAPACITY LIMITS IN THE NAS How well do we understand the dynamics ?
R. John Hansman, Director
Massachusetts Institute of Technology
International Center for Air Transportation

2. Issue
The US Air Transportation system is approaching a critical saturation threshold where nominal interruptions (e.g. weather) result in a nonlinear amplification of delay
US and Regional Economies highly dependant on Air Transportation
Business travel (stimulated by info technology)
Air Freight
Personal travel
System is highly complex and interdependent
Need better understanding of system dynamics and real constraints to guide and justify efforts to upgrade NAS
Current efforts will not provide capacity to meet demand
Impact of upcoming capacity crisis is not well understood

6. Background
ATM is a human centered contract process for the allocation of airspace and airport surface resources.
Current NAS has evolved over 60 years
The system has significant local adaptations resulting in nonhomogeneity
Airspace design
Local procedures
Letters of agreement
Noise restrictions
Site specific training (FPL = 3 years)
Major operational changes were event driven, enabled by technical capability
Positive radar control - Grand Canyon 1956
TCAS - Los Cerritos 1982

7. ATM System Current Functional Structure
Aircraft State
Aircraft
Guidance and
Navigation
AC State
Sensor
Sector
Traffic
Control
Vectors
Clearances
Planning
National
Flow
Approved
Flight
Plans
Handoffs
Desired
Loads
Clearance
Requests
Other Aircraft
States
Weather
Schedule
Filed
Negotiate
Schedule of
Capacities
< 5 min
5 min
5-20 min
hrs - day
Facility
hrs
Execution - Tactical Level
Planning - Strategic Level
Airline
CFMU
TMU
D-side
R-side
Pilot
Planned
Rates
Measurement
Real State
Plan/Intent
AOC
Efficiency
Throughput
Increasing Criticality Level
Safety
Source: A. Haraldsdottir Boeing

8. Critical Issues 1 Capacity Limits (Schedule vs. Infrastructure)
Airports
Airspace
Controllers
Environmental Limits
Noise (relates to Airport)
Emissions (local, Ozone, NOX, CO2)
Understanding of Current System
Complexity
Dynamics , non-linearity's
Labor Issues
Safety vs Capacity
How to improve current high levels
Separation Standards example

10. Critical Issues 2 Role of Information Technology
Decision Aids vs Information Sharing (eg CDM)
Centralized vs Distributed Control
Impact of Structure
Vulnerability/Robustness Issues
Political Issues
How does air transportation impact economic development
Balance between local and regional interests
Impact of Labor on system
Transition issues

11. Schedule Factors
Peak Demand/Capacity issue driven by airline Hub and Spoke scheduling behavior
Peak demand often exceeds airport IFR capacity (VFR/IFR Limits)
Depend on bank spreading and lulls to recover
Hub and Spoke amplifies delay
Hub and spoke is an efficient network
Supports weak demand markets
Schedules driven by competitive/market factors
Operations respond to marketing
Trend to more frequent services, smaller aircraft
Ratchet behavior
Impact of regional jets
Ultimately, airlines will schedule rationally
To delay tolerance of the market (delay homeostasis)
Limited federal or local mechanisms to regulate schedule

12. Variable Capacity Effects 1995 Delays vs Operations

13. Capacity Example (50 Flights/hr)

14. Capacity Example (40 Flights/hr)

15. Capacity Example (30 Flights/hr)

16. Completely Connected Network = 2(N-1) Flights
Hub and Spoke Network
Completely Connected Network = 2(N-1) Flights
(eg., 50 Airports, 98 Flights)

17. Fully Connected Network
Completely Connected Network = N(N-1)
(eg., 50 Airports, 2450 Flights)

18. Infrastructure Airports (Concrete) Aging Infrastructure
Arrival/Departure Capacity Set by Runways/ Wake Vortex Separations
Marginal Increase in Peak Capacity Available at Existing High Demand Airports (less than 40%)
New Airports/Runways Politically Difficult
Community opposition
Gates and land-side limits
Load shedding to underutilized airports occurring
MHT, PVD, BWI
Impact on Terminal Areas
Aging Infrastructure
Modernization challenge
Communications, Navigation, Surveillance, Information, Software
Reliability impact
Labor issues

19. ACARS Constraint Identification

20. The Airport / Terminal Area System

21. Interactive Queuing Model BOS 22L,22R,27 Configuration

22. BOS Queuing Model 27/22L-22R Configuration

23. BOS Queuing Model 4L/4R-9 Configuration

24. Runway Configuration Capacity Envelops

25. Downstream Restrictions Ground Stops

26. Downstream Restrictions Local TRW

27. Gate Dynamics
Low Predictability of Departure Demand based on Schedule

28. Gate Dynamics: On Gate Departure Preparation

29. Minimal Noise Procedures NOISIM JP Clarke MIT

30. 3° Decelerating Approach (JFK 13L)
Existing ILS Approach
3° Decelerating Approach

31. Safety vs Capacity The system is extremely safe but conservative
Separation Standards
What is the true level of criticality of the ATM?
NAV, COM, Surveillance, Control
Redundancy architectures vs. high integrity
GPS (sole means?)
ATC (TCAS)
Design system/procedures for non-normal operations
How do you dependably predict the safety impact of changes in a complex interdependent system?
Statistics of small numbers
Differential analysis limited to small or isolated changes
Models??
Safety Veto Effect

32. FACTORS AFFECTING SAFE SEPARATION ASSURANCE
SURVEILLANCE EFFECTS
Position uncertainty
Velocity/higher states
Scan effects
Contingency
(unknown-unknowns)
Aircraft dynamics
Response dynamics

33. SURVEILLANCE STATE VECTOR MODELING APPROACH
A modeling approach is developed to provide a framework to formalize the surveillance effects component
Trend towards surveilling more aircraft states, e.g. ADS-B (enabling better control precision?)
Surveillance State Vector X(t) containing uncertainty & errors X(t) at time t is given by:

34. TYPES OF INTENT
IP(t) = generalized representation of the pilot’s intent for his a/c
IC(t) = generalized representation of future behavior of the aircraft to the extent it is known or assumed by the controller
IFP(t), Flight plan/clearance
IE(t), Alternate procedures (e.g. emergency)
IAFS(t) = generalized representation of intent programmed into the autoflight system
Errors & uncertainty I(t) in controller assumptions of trajectory:
IC(t) ≠ IP(t), Controller misunderstanding—controller incorrectly assumes pilot intent
IP(t) ≠ IFP(t), Pilot blunder—does not follow ATC clearance
IC(t) ≠ IFP(t), Miscommunication—controller gives incorrect instruction
IP(t) = IE(t) ≠ IC(t), Emergency—diversion off flight plan for technical reasons

35. ATC Workload as a System Constraint

36. Local Controller Communication Workload

37. RUNWAY INCURSIONS BY TYPE
Caused by multiple aircraft occupancy of an active runway:
Taxiing aircraft crosses an active runway without clearance
Aircraft taxies along active runway thinking it is a taxiway
Landing aircraft slow to clear runway upon landing
Landing aircraft violates LAHSO
Source: ASRS Database report set, 50 most recent records of runway incursions (as of 12/30/98)
26%

38. INCORPORATION OF HUMAN ELEMENTS
CLOSEST
POINT OF
APPROACH
STATISTICS
CONTROLLER
EXPOSURE
STATISTICS
SURVEILLANCE
DETECTION
SIMMOD Pro!
AIRSPACE
MODEL
AIRCRAFT
STATES, Xi
RESPONSE
PILOT (i)
COMMS
SURVEILLANCE
VIOLATION
GENERATOR
DETECTION
MODIFIED
AIRCRAFT BEHAVIOR
RESPONSE

39. SIMMOD MODELING OF RUNWAY INCURSIONS AT LAX

40. DETECTION / RESPONSE RESULTS
NOTE: Simulation results are for demonstration purposes only. Simulations were conducted in part using hypothetical assumptions and input data. Analysis results are strictly hypothetical.
(eg.AMASS, LVLASO)

41. Information Technology
Key roles of IT in ATM
Decision Support Tools (eg CTAS, URET)
Shared Information Systems (eg CDM tools, Datalink)
Need to Develop Information Architectures to Support Information Sharing
Flight Information Object (CONOPS 2005)
Articulation of Intent
Incorporation of IT will result in planned and unplanned changes in human interaction and ATM processes
Roles, Responsibilities, Interaction Dynamics
Need to understand the “Sociology of ATM”
Pilots
Controllers
Dispatchers

42. ATM Tactical Information Architecture
Supervisor
Controller
CCI
Controller
CCC
Controller
ATC Facility CP
Pilot/Controller CP AA
Pilot/Airline
Pilot PA
Controller/Controller PA
CCI
Intra-Facility
Controller/Controller
CCC
Company
Dispatcher
Cross-Facility AA
Airline/ATM
Airline

43. ATM Strategic Information Architecture
Tower C
Airline C
Tower B
Airline B
Airline
Tower A
Airline A
Operations
Airline
Supervisor
TMC
Center
Operations
Airline
Center
Operations
TMC
Center
Central
Flow
Control
Host
TRACON C
TMC
ARTCC C B A
Supervisor
TRACON B
TRACON A
Supervisor
TMC
TMC

44. Flight Object Organization
Information from NAS User Personnel and Tools
Flight As
Filed
Cleared
Flown
Object
Current
History
Planned
or Projected
Information from Air Traffic Management Personnel and Tools
Information from Sensors and Pilot Reports
Abstraction Example from MITRE CAASD

45. Flight Object Interaction with the Host
Baseline
FFP1
FFP2
(From filed flight plan)
Aircraft identifier
Aircraft type
Filed route
Filed cruise altitude
Filed cruise speed
Origin
Destination
Scheduled departure time
Estimated time en route
Estimated arrival time
Equipment in use
Aircraft identifier
Aircraft type
Filed route
Filed cruise altitude
Filed cruise speed
Origin
Destination
Scheduled departure time
Estimated time en route
Estimated arrival time
Equipment in use
Flight As
Filed
Current
History
Planned
or Projected
Computer identifier
Route, altitude, and speed (cleared flight plan information and amendments as known to Host*)
Current
History
Planned
or Projected
Flight As
Flown
Cleared
Computer identifier
Route, altitude, and speed
Radar track position
Calculated speed and
direction
Altitude report
Radar track position
Calculated speed and direction
Altitude report (from Mode C)
Estimated time at next waypoint (based on flight plan and position reports)
Estimated time at downstream fixes (based on flight plan and position reports)
*Clearances made using voice communications, such as interim altitude duration and radar vector clearances, may not be available electronically.
FFP1 Timeframe
FFP2 Timeframe
Beyond FFP2 Timeframe (TBD)
Host provides information element to flight object
Host uses information element from flight object

46. Suggested Solutions to Capacity Shortfall
Privatization, the silver bullet?
May improve modernization,costs and strategic management
Limited impact on capacity
Re-regulation
Increased Costs
Peak Demand Pricing
Reduced service to weak markets
Run System Tighter
Requires improved CNS
Safety vs Capacity Trade
Build more capacity
Local community resistance
Multi-modal transportation networks