MIT ICATMIT ICATCAPACITY LIMITS IN THE NAS

How well do we understand the dynamics ?

R. John Hansman, DirectorMassachusetts Institute of Technology

International Center for Air Transportation

rjhans@mit.edu 617-253-2271

MIT ICATMIT ICATIssue

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

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MIT ICATMIT ICATBackground

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

MIT ICATMIT ICATATM System Current Functional Structure

Aircraft StateAircraftGuidance and

Navigation

AC StateSensor

SectorTraffic Control

TrafficSensor

Vectors

Clearances

SectorTraffic

Planning

NationalFlow

Planning

ApprovedFlight Plans

ApprovedHandoffs

DesiredSectorLoads

ClearanceRequests

Other AircraftStates

FlightPlanning

Weather

FlightSchedule

FiledFlight Plans

NegotiateHandoffs

Schedule ofCapacities

< 5 min5 min5-20 minhrs - day

FacilityFlow

Planning

hrs

Execution - Tactical LevelPlanning - Strategic Level

Airline CFMU TMU D-side R-sidePilot

PlannedFlowRates

ClearanceRequests

Measurement

Real State

Plan/Intent

Requests

AOC

Efficiency Throughput

Increasing Criticality Level

Safety

Source: A. Haraldsdottir Boeing

MIT ICATMIT ICATCritical 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

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MIT ICATMIT ICATCritical 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

MIT ICATMIT ICATSchedule 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

MIT ICATMIT ICATVariable Capacity Effects1995 Delays vs Operations

10000008000006000004000002000000

0

10

20

30

40

50

60

Total Operations (CY95)

Delayed Flights (per 1000)

SFO

LGA EWR STL

LAX

ORD

DFW

ATL

BOS

JFK

PHX

LAS

SJU

HNL

PITDEN

CLT

IAH

MEM

Data from FAA Capacity Office, CY95

MIT ICATMIT ICATCapacity Example(50 Flights/hr)

0

10

20

30

40

50

60

70

Time

MIT ICATMIT ICATCapacity Example(40 Flights/hr)

0

10

20

30

40

50

60

70

Time

MIT ICATMIT ICATCapacity Example(30 Flights/hr)

0

10

20

30

40

50

60

70

Time

MIT ICATMIT ICATHub and Spoke Network

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

MIT ICATMIT ICATFully Connected Network

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

MIT ICATMIT ICATInfrastructure

Airports (Concrete) 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

MIT ICATMIT ICATACARS Constraint Identification

Normalized Total Departure Delay

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Ramp DelaysTaxi CongestCloseout InfoField TrafficATC Enrt ClrA/C Sys Check

TO Perf Re-CalcRnwy ChangeATC Hold Dep

Othr Flts L/DTO Wx Mins

BOS

ATL

ORD

DFW

One Airline, Ten Months (Jan-Oct. 97)

MIT ICATMIT ICATThe Airport / Terminal Area The Airport / Terminal Area SystemSystem

MIT ICATMIT ICATInteractive Queuing Model BOS 22L,22R,27 Configuration

N

MIT ICATMIT ICATBOS Queuing Model 27/22L-22R Configuration

N

MIT ICATMIT ICATBOS Queuing Model 4L/4R-9 Configuration

N

MIT ICATMIT ICATRunway Configuration Capacity Envelops

Runway Configuration Capacity Envelops(Source: ETMS / Tower Records, 7-9 AM, 4-8 PM, July 1-15

1998 except Saturdays, Logan Airport)

0

5

10

15

20

25

0 5 10 15 20 25

Actual Departure Rate (per 15 minutes)

Actual Arrival Rate (per 15 minutes)

4L/4R-9 (reportedaverage 68 AAR - 50DEP)

27/22L-22R (reportedaverage 60 AAR - 50DEP)

33L/33R-27 (reportedaverage 44 AAR - 44DEP)

Single Runway (January1999, reported average34 AAR 34 DEP)

MIT ICATMIT ICATDownstream RestrictionsGround Stops

Downstream Restrictions Effect on Departure Rate(source: CODAS/ETMS, Logan Airport, July 17-1998)

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

6:00:00 8:24:00 10:48:00 13:12:00 15:36:00 18:00:00 20:24:00 22:48:00

Time (Local)

Departure Rate (per 15 minutes)

Average Departure Rate July 17, All day restrictions

GS to EWR, LGA, IAD, PHL, ORD and BWI 15:15 - 21:00, ACK GS 11:00 - 13:00

ADP

ADP

Downstream Restrictions Effect on Delays(Source: ASQP, Logan Airport, All Airlines, July 17-1998)

-50-30-101030507090

110130150

6:00:00 8:24:00 10:48:00 13:12:00 15:36:00 18:00:00 20:24:00 22:48:00

Time (Local)

Time (minutes)

Taxi Out Push Delay

GS to EWR, LGA, IAD, PHL, ORD and BWI 15:15 - 21:00, ACK GS 11:00 - 13:00

MIT ICATMIT ICATDownstream RestrictionsLocal TRW

Downstream Restrictions Effect on Delays(Source: ASQP, Logan Airport, All Airlines, July 23-1998)

-50

-30

-10

10

30

50

70

90

110

130

150

6:00:00 8:24:00 10:48:00 13:12:00 15:36:00 18:00:00 20:24:00 22:48:00

Time (Local)

Time (minutes)

Taxi Out Push Delay

Thunderstorms, BOSOX, MHT and PSM (exit gates): GS and INTRAIL 12:30 - 20:30

Downstream Restrictions Effect on Departure Rate(source: CODAS/ETMS, Logan Airport, July 23-1998)

0.002.004.006.008.00

10.0012.0014.0016.0018.0020.00

6:00:00 8:24:00 10:48:00 13:12:00 15:36:00 18:00:00 20:24:00 22:48:00

Time (zooloo)

Departure Rate (per 15

minutes)

Average Departure Rate July 23, All day restrictions

Thunderstorms, BOSOX, MHT and PSM: GS and MINIT 12:30 - 20:30

ADPADP

ADPADP ADP

MIT ICATMIT ICATGate Dynamics

Low Predictability of Departure Demand based on Schedule

"Scheduled Departure Time" to "Ready for Push or Taxi"

0

10

20

30

40

50

60

70

80

0:00 0:08 0:16 0:24 0:32 0:40 0:48 0:56 1:04 1:12 1:20 1:28 1:36

Time (hr:min)

Frequency

Mean = 14 min (absolute )S td. Dev = 17 min 22 sec

MIT ICATMIT ICATGate Dynamics:On Gate Departure

Preparation

MIT ICATMIT ICATMinimal Noise Procedures

NOISIM JP Clarke MITMODE CONTROL PANEL

(MCP)COURSE IAS/MACH HEADING VERT SPEED COURSE ALTITUDE

3

6

10

17

FCS

TRK M

8.9 NM 0623.7z

KCOS

CAGER

WENNY

FLOTS

EHSI

0619.6z

ClockMCP Status

ALT V/S HDG SPD

5000 016 180

NOSE

LEFT RIGHT

Gear Status

Flap Status

UP

1

515

20

2530

MarkerBeacons

EADISpeed Altitude

PULL UP

GND

PROX

MID

INNER

OUTER 030

36

GPWS

Windscreen

5300185

A/TIDLE

VNAV

CMD

LNAV

GS 193 2470

-200

VerticalSpeed

PRECIP

WINDSHEAR

WINDSHEARAHEAD

CONTROL DISPLAY UNIT

CAGER

WENNY

WATKI

EKR

036 / 16.9

060 / 23.5

076 / 17.4

35000 / 350

30000 / 300

25000 / 250

20000 / 250

SPEED BRAKES, THROTTLES, FLAPS, GEAR

PILOT'S CHAIRCONTROL STICK

DISPLAY

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3° Decelerating ApproachExisting ILS Approach

3° Decelerating Approach (JFK 13L)

MIT ICATMIT ICATSafety 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

MIT ICATMIT ICATFACTORS AFFECTING SAFE SEPARATION ASSURANCE

Aircraft dynamics Response dynamics

Contingency(unknown-unknowns)

SURVEILLANCE EFFECTS• Position uncertainty

•Velocity/higher states

•Scan effects

MIT ICATMIT ICATSURVEILLANCE 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:

X(t)=

Position, R(t)

Velocity, V(t)

Acceleration, A(t)

Intent, I(t)

M

⎧

⎨

⎪ ⎪ ⎪

⎩

⎪ ⎪ ⎪

⎫

⎬

⎪ ⎪ ⎪

⎭

⎪ ⎪ ⎪

δX(t) =

δR(t)

δV(t)

δA(t)

δI(t)

M

⎧

⎨

⎪ ⎪ ⎪

⎩

⎪ ⎪ ⎪

⎫

⎬

⎪ ⎪ ⎪

⎭

⎪ ⎪ ⎪

MIT ICATMIT ICATTYPES 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

MIT ICATMIT ICATATC Workload as aSystem Constraint

MIT ICATMIT ICATLocal Controller Communication Workload

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CROSSING ACTIVE

RUNWAY40%

TAXI (NOT CROSSING)

26%

TAKE OFF10%

LANDING4%

OTHER20%

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%

MIT ICATMIT ICATINCORPORATION OF HUMAN ELEMENTS

SIMMOD Pro!AIRSPACE

MODEL

CONTROLLER

SURVEILLANCE

RESPONSE

COMMS

DETECTION

PILOT (i)

SURVEILLANCE

RESPONSE

DETECTION

AIRCRAFTSTATES, Xi

MODIFIEDAIRCRAFT BEHAVIOR

CLOSESTPOINT OF

APPROACHSTATISTICS

VIOLATIONGENERATOR

EXPOSURESTATISTICS

MIT ICATMIT ICATSIMMOD MODELING OF RUNWAY INCURSIONS AT LAX

MIT ICATMIT ICATDETECTION / RESPONSE RESULTS

Percent of Transgressions with Timely Detection/Response

Base CaseEnhancedIntruder

EnhancedController

EnhancedIntr & Cntr

By Intruder 4% 28% 7% 27%

By Evader 24% 15% 19% 13%

By Controller 3% 3% 11% 7%

Total 31% 46% 37% 47%

(105 of 341) (159 of 342) (130 of 351) (168 of 354)

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)

MIT ICATMIT ICATInformation 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

MIT ICATMIT ICATATM Tactical Information Architecture

Pilot

Controller

Supervisor

Dispatcher

Controller Controller

Company

Pilot/Controller

ATC Facility

Airline

Pilot/Airline

Controller/ControllerIntra-Facility

Controller/ControllerCross-Facility

CPCP

CCCCCI

PA

PA

CCC

CCI

AA

Airline/ATM AA

MIT ICATMIT ICATATM Strategic Information Architecture

Airline C

AirlineOperationsCenter

CentralFlow

Control

Host

TMC

Tower C

Tower B

TMC

Tower A

Supervisor

TMC

TRACON C

TRACON B

TMC

TRACON A

SupervisorTMC

ARTCC C

ARTCC B

TMC

ARTCC A

Supervisor

Airline B

AirlineOperationsCenter

Airline A

AirlineOperationsCenter

MIT ICATMIT ICATFlight Object Organization

FlightAs

Filed

FlightAs

Cleared

FlightAs

Flown

Flight

Object

Current

History Plannedor Projected

Current

History Plannedor Projected

Current

History Plannedor Projected

Information from NAS User Personnel and Tools

Information from Air Traffic

Management Personnel and Tools

Information from

Sensors and Pilot Reports

Abstraction Example from MITRE CAASD

MIT ICATMIT ICATFlight Object Interaction with the Host

Host provides information element to flight object

Host uses information element from flight object

Flight AsFiled

Current

History Plannedor Projected

Current

History Plannedor Projected

Flight AsFlown

Current

Plannedor Projected

Flight AsCleared

History

FFP1 TimeframeFFP2 TimeframeBeyond FFP2 Timeframe (TBD)

(From filed flight plan)Aircraft identifier

Aircraft typeFiled route

Filed cruise altitudeFiled cruise speed

OriginDestination

Scheduled departure timeEstimated time en route

Estimated arrival timeEquipment in use

Computer identifierRoute, altitude, and speed

(cleared flight plan information and

amendments as known to Host*)

Radar track positionCalculated speed and direction

Altitude report (from Mode C)

Aircraft identifierAircraft typeFiled routeFiled cruise altitudeFiled cruise speedOriginDestinationScheduled departure timeEstimated time en routeEstimated arrival timeEquipment in use

*Clearances made using voice communications, such as interim altitude duration and radar vector clearances, may not be available electronically.

Computer identifierRoute, altitude, and speed Radar track position

Calculated speed and directionAltitude report

Baseline FFP1 FFP2

Estimated time at downstream fixes (based on flight plan and position reports)

Estimated time at next waypoint (based on flight plan and position reports)

MIT ICATMIT ICATSuggested 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