ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 1

NASA ASAS Activities: Decision Support for

Airborne Trajectory Management & Self-Separation

National Aeronautics and Space Administration

Next Generation Air Transportation System Airspace Project

Robert A. VivonaAOP Lead EngineerL-3 Communications

Billerica, MA

Presentation Overview

• Background– Airborne trajectory management

• Autonomous Operations Planner (AOP)– Provided ASAS functions– System interface– Capabilities

• AOP Experimental Performance

• Concluding Remarks

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 3

Background: Airborne Trajectory Management

Concept• Trajectory-oriented operations

– En route & transition to terminal• Aircraft self-optimization• Mixed environment

– Self-separating & ground managed aircraft

Self-separating aircraft:• Flight-deck decision support

equipped– Autonomous Operations Planner

• “Autonomous Flight Rules”– Self-separate (traffic & area hazards)– Conform to flow constraints– Don’t generate conflicts within 5 mins

• Broadcast state & intent data• FMS & air/ground data link equipped

Ground managed aircraft• Similar to today’s operations• Broadcast state (and intent) data

En Route Airspace

Ground managed

Self-separating

ATSP Responsibilities• Manage airspace resources

– Generate flow constraints– Datalink to autonomous aircraft

• Control ground managed aircraft

Terminal Airspace (Merging & Spacing)

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 4

Autonomous Operations Planner (AOP)

Purpose: enable trajectory management• Conformance to constraints

– Separation from traffic aircraft– Avoidance of special use airspace– Minimum penetration of weather hazards– Conformance to time-based flow

constraints• Path optimization• Supports navigation & guidance decisions

Concept of use• Detects & alerts need to modify trajectory• Supports trajectory modifications:

– Strategic & tactical maneuver alternatives– “What-if” maneuver analysis

• Generates user-optimal paths• Automatically adapts to flight-crew

chosen guidance mode

Tactical ManeuverRestriction Region

Area of ConflictAlong CurrentFMS Route

Resolution ManeuverUploaded to FMS as

Mod Route

ConflictAircraft

Navigation Display

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 5

AOP: Provided ASAS Functions

ASAS Functions* AOP Approach

Traffic Data Identify Reference Aircraft Primary Function: Uses ADS-B and TIS-B information to track and predict traffic aircraft behavior.

Track Reference Aircraft

Provide Reference Aircraft’s Trajectory

Assessing Initiation Criteria Not supported (though could be). Not yet required for current research efforts.

Assessing Continuation Criteria

Assessing Termination Criteria

Merge Compute Maneuvers to Merge Not required. Separate system (PDS) at Langley provides merging & spacing capability.

Compute Merge Location

Follow Compute Dependent Following Trajectory

Manage Interval

Compute Speeds to Achieve and Maintain Interval

Monitor Interval Conformance

Separation Maintenance

Monitor Maintenance of Separation Secondary Function: Uses state-based CD&R for blunder protection.

Compute Guidance to Maintain Separation

Conflict Detection

Probe Trajectory For Conflicts Primary Function: Uses both intent-based and state-based approaches.

Alert Crew to Conflicts

Conflict Resolution

Compute Vertical Maneuvers to Provide Separation Primary Function: Uses both strategic and tactical approaches.

Compute Lateral Maneuvers to Provide Separation

Compute User-Preferred Trajectory to Provide Separation

Trajectory Optimization

Compute Traffic-Constrained User-Preferred Trajectory Primary Function: Provided by provisional trajectory analysis.

Compute Aircraft Performance

Compute Maneuvering Flexibility Primary Function: Looks within and outside resolution horizon.*Source: FAA/Eurocontrol Cooperative R&D AP23

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 6

AOP: System Interface

AV

ION

ICS

DA

TA

BU

S

AutonomousOperations

Planner (AOP)

Mode Control Panel (MCP)

AOPOutputs

Multi-Function Control& Display Unit (MCDU)

Navigation Display Primary Flight Display (PFD)

Flight ManagementSystem (FMS)

Flight ControlComputer (FCC)

Other Sources:• GNSS Clock• ADS-B• TIS-B• FIS-B

AOPInputs

Inputs:• Guidance settings• Traffic data• Weather data• AOP MCDU data

Outputs:• Conflict alerts• FMS route mods• MCP setting mods• AOP MCDU data

Integrates withExisting Avionics& Displays

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 7

AOP: Capabilities

• Conflict management– Probe multiple maneuvers for situation awareness– Conflict detection and resolution details

• Intent-based and state-based approaches

• Maneuver without conflict (conflict prevention)– Provisional (“what-if”) planning– Maneuver restriction bands

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 8

Conflict Management

• Approach:– Probe all relevant maneuvers (trajectories) requiring evaluation by flight crew

• Display all conflicts to provide complete situation awareness– Provide resolution capabilities for each maneuver

• AOP can simultaneously predict/evaluate multiple ownship maneuvers– Maintaining current guidance (Commanded Prediction)

– Evaluate impact of current guidance settings– “What happens if I don’t change the guidance settings?”

– Reconnecting to strategic route (Planning Prediction)– Advise & evaluate maneuver to re-establish FMS active route– “How do I get back to my long-range plan?”

– Stop maneuvering (State-vector projection)– Evaluate impact of maintaining current state– “What happens if I stop or don’t start/continue maneuvering?” (e.g., blunder)

• Not all maneuvers always relevant

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 9

Conflict Management

MCP altitude limit

State vector projection

Commanded prediction

Planning prediction

Active RouteAltitude Constraint

Commanded Prediction• Predicts impact of current guidance mode settings

• Initiates VNAV PATH descent• Predicts guidance switch to VNAV ALT at MCP altitude

• Primary CR impacts active guidance

FMS PredictedTop-of-Descent

Planning Prediction• Predicts impact of most strategic path

• Predicts VNAV PATH descent• Ignores MCP altitude

• Secondary CR impacts non-active path

State vector projection• Predicts impact of not initiating descent

•State projection at cruise altitude• Point out / override CD&R

Primary CD Alerting Secondary CD Alerting

VNAV PATHVNAV PATH

VNAV PATHVNAV PATH

VNAV ALTVNAV ALT

LNAV/VNAV

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 10

Conflict Management

• Primary conflicts on the commanded prediction• Secondary conflicts on planning and blunder (state-vector)

predictions

LNAV

On path

TRACK HOLD

Off pathWithin capture

TRACK HOLD

Off pathBeyond capture

BlunderProtection

Planning

Commanded

Commanded Commanded

FirstLOSFirstLOS

LastLOSLastLOS

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 11

Conflict Management:Conflict Detection & Resolution

• Intent-based conflict detection– Trajectory prediction

• Ownship

• Traffic

– Trajectory prediction uncertainty buffers

• Intent-based conflict resolution– Strategic & tactical

• State-based CD&R

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 12

• 1xN probing of ownship versus all hazards (traffic and area)– Probes ownship 4D trajectory against all traffic aircraft 4D

trajectories and area hazard geometries

• Configurable research parameters– Required separation zone

• Independent values for AFR & IFR traffic– Look-ahead

• Typically 10 minutes

• Uses prediction uncertainty bounds– Independent definitions for

• ownship and traffic• different maneuvers (flight modes)

– Conflict = predicted loss between uncertainty regions

Conflict Management: Intent-Based CD

ownship

traffic

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 13

Intent-Based CD: Trajectory Prediction

• Ownship– Generated from aircraft guidance

settings– Primarily based on

• Sensors: initial condition• MCP, FMS, FCC, MCDU

settings– Numerical integration using internal

trajectory predictor• FMS quality prediction for all

guidance modes– Trajectory generated for CD

application (commanded, etc.)

• Traffic– Generated from ADS-B data– Primarily based on:

• SVR: initial condition• TCR: represents predicted

trajectory– TCP+N approach

– No numerical integration– Exploring using TSR with integration

for tactical guidance modes– One trajectory per traffic aircraft

(used for all CD applications)

ADS-B

Mode Status Report (MSR)

Air Referenced Velocity Report (ARV)

Trajectory Change Report (TCR)

State Vector Report (SVR)

Target State Report (TSR)

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 14

Intent-Based CD:Trajectory Prediction Uncertainty Buffers

Tim

e

Lateral path

TimeAltitude

Cross-track

Ver

tical

Cro

ss-t

rack

Tim

e

• 4D “tube” around 4D trajectory

• Encapsulates prediction uncertainties unique to each segment type

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 15

Conflict Management:Intent-Based Conflict Resolution

• Strategic– Develops FMS-compatible routes

• Uploaded directly into the FMS– Crew requested (semi-automatic)– Solution:

• Independent lateral and vertical maneuver options– Approach:

• Resolves all conflicts and constraints, non-cooperative (priority rule-based)• Pattern-Based Genetic Algorithm

• Tactical– Develops MCP setting advisories– Automatic when FMS decoupled or short time to conflict– Solution:

• Independent altitude, vertical rate, heading/track options– Approach:

• Resolves all conflicts, non-cooperative (priority rule-based)• Sweep until first conflict free setting found

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 16

Conflict Management:Intent-Based Conflict Resolution

Tactical Intent-Based CRStrategic Intent-Based CR

Nav Display

Active Route: MagentaResolution Route: Blue

Nav Display

Primary FlightDisplay

TrackAdvisory

Vertical RateAdvisory

AltitudeAdvisory

Conflict Management: State-Based CD&R

• Independent system from intent-based CD&R

• Supports– Blunder protection– Override for short term conflicts

• Approach– Two options

• NLR (Modified Voltage Potential)• Langley (KB3D)

– Resolution advisories• Independent MCP settings

– track/heading, vertical rate, altitude• Automatically displayed when needed

– Similar characteristics• Resolves most immediate conflict

– Cooperative/Non-cooperative (configurable)• Maneuver to increase to minimum separation standard• Implicitly coordinated with other traffic maneuvers• CD

– Look-ahead at 5 minutes (configurable)– No area hazard detection– Does not consider uncertainty

Modified Voltage PotentialModified Voltage Potential

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 18

Maneuvering Without Conflict(Conflict Prevention)

• Provisional (what-if) planning– Non-conflict generated maneuver

• Probe for conflicts before execution– FMS provisional

• Automatic probe of FMS MOD route– MCP provisional

• Automatic probe of non-active MCP inputs

• Maneuver restriction (MR) bands– Protect against unallowable maneuvers

• Conflicts generated within 5 mins– Bands show unallowable MCP settings

• Lateral (track/heading)• Vertical (vertical rate)

– Automatically generated for:• Non-active MCP setting change• Switch to tactical guidance mode

Lateral MRBand

MCPProvisional

Conflict

Non-activeChange in MCPTrack Setting(e.g., in LNAV)

FMSProvisional

Conflict

Manual MODRoute in FMS

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 19

AOP Experimental Performance

NASA Air Traffic Operations LabAll aircraft co-altitude, circle diameter 160 NMSustained Mean Density1 17.18

Sustained Mean

Density1

Sim. Hours

Simulated flights

Traffic conflicts

LOS2

1 Aircraft per 10,000 NM2

2 Loss of separation (5 NM)3 Ref. sector ZOA31 – median density, 19 Feb 2004

Consiglio, Hoadley, Wing, Baxley:Safety Performance of Airborne Separation -

Preliminary Baseline Testing. AIAA-2007-7739.

Experiment 1: Lateral Only, Random Routes, All Autonomous

3.45 36 881 195 0

6.11 36 1527 550 0

8.61 36 2195 1018 0

11.64 36 3000 1788 0

15.24 12 1302 963 0

17.18 12 1560 1256 0

Totals 168 10,465 5770 0

10X playback speed

Lateral Strategic CR Only

2x 3

10x

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 20

AOP Experimental Performance

(*)Relative to mean and peak 1X densities of 1.8 and 3 aircraft, normalized to 10000 nmi2, at the most populated flight level of the median-density sector on 19 Feb 2004.

(**) All 3 LOS events were from high-complexity multi-aircraft conflicts. The 2 LOS events at the 21.4 density involved a 4-aircraft conflict in which one aircraft lost separation with two of the intruders. Consiglio, Hoadley, Wing, Baxley, Allen:

Impact of Pilot Delay and Non-Responsiveness on theSafety Performance of Airborne Separation. ATIO 2008.

Average

Density(*)

Average Pilot

Delays (Seconds)

Flight Hours

Total Conflicts

Total LOS(**)

11.2

5X/3X3.5 240.73 583 0

16.3

8X/5X3.5 90.71 316 1

21.4

12X/7X3.5 572.76 2307 2

Totals: 904.20 3206 3

Lateral Strategic CR Only(CPA < 0.02 nmi)

Experiment 2: Lateral Only, Random Routes, All Autonomous, Pilot Delay

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 21

AOP Performance: Batch Experiment 2

As traffic density increases, so does the number of multi-aircraft conflicts, which reflects increased traffic complexity0

50

100

150

200

250

300

350

Count

Number of Conflicting Pairs

11.2 140 28 3 1 0 0

16.3 210 79 11 1 0 0

21.4 350 136 46 10 2 0

1 2 3 4 5 6

Number of intruder aircraft per conflict resolutions.

Experiment 2: Lateral Only, Random Routes, All Autonomous, Pilot Delay

AOP Intent-Based CD&R StudiedUnder Highly Complex Traffic ScenariosAOP Intent-Based CD&R StudiedUnder Highly Complex Traffic Scenarios

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 22

Concluding Remarks: Current NASA Efforts

• SPAS (Safety Performance of Airborne Separation)– PI: María Consiglio– Studying effects of major error sources (e.g., wind error) on safety

performance

• SPCASO (Safety & Performance Characterization of Airborne Self-Separation Operations)– Prediction uncertainty

• PI: Danette Allen• Studying use of trajectory prediction uncertainty bounds to mitigate

prediction error– Mixed operations

• PI: David Wing• Studying impact of mixed AFR and IFR traffic• Investigating approaches to mitigating traffic complexity using AOP

• ADS-B Performance– PI: Will Johnson– Studying impacts of ADS-B range, interference and limited intent

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 23

Concluding Remarks: AOP References

• System Concept– Ballin, M.G., Sharma, V., Vivona, R.A., Johnson, E.J., and Ramiscal, E.: “A Flight Deck Decision

Support Tool for Autonomous Airborne Operations,” AIAA Guidance, Navigation, and Control Conference, AIAA-2002-4554, August 2002.

• CD&R– Vivona, R., Karr, D., and Roscoe, D., “Pattern-Based Genetic Algorithm for Airborne Conflict

Resolution”, AIAA Guidance, Navigation and Control Conference, AIAA-2006-6060, August 2006. – Karr, D., and Vivona, R., “Conflict Detection Using Variable Four-Dimensional Uncertainty Bounds

to Control Missed Alerts,” AIAA Guidance, Navigation and Control Conference, AIAA-2006-6057, August 2006.

– Mondoloni, S., Ballin, M., and Palmer, M.: “Airborne Conflict Resolution for Flow-Restricted Transition Airspace,” 3rd AIAA Aviation Technology, Integration and Operations (ATIO) Conference, AIAA-2003-6725, November 2003.

• Experiments– Consiglio, M., Hoadley, S., Wing, D., and Baxley, B., “Safety Performance of Airborne Separation:

Preliminary Baseline Testing,” 7th AIAA Aviation Technology, Integration and Operations (ATIO) Conference, AIAA-2007-7739, September 2007.

– Consiglio, M., Hoadley, S., Wing, D., Baxley, B., and Allen, D., “Impact of Pilot Delay and Non-Responsiveness on the Safety Performance of Airborne Separation,” 8th AIAA Aviation Technology, Integration and Operations (ATIO) Conference, AIAA-2008-8882, September 2008.

ASAS TN2.5 Workshop, Rome, Italy, November 13, 2008 24

Demonstration

• Demo– ~10x traffic

density

– 10x playback speed

– Long range display

– No display filtering

NavigationDisplayNavigationDisplay

Lateral Intent-Based CRLateral Intent-Based CR