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National Aeronautics and Space Administration. Next Generation Air Transportation System Airspace Project. NASA ASAS Activities: Decision Support for Airborne Trajectory Management & Self-Separation. Robert A. Vivona AOP Lead Engineer L-3 Communications Billerica, MA.

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NASA ASAS Activities: Decision Support for Airborne Trajectory Management & Self-Separation


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nasa asas activities decision support for airborne trajectory management self separation

National Aeronautics and Space Administration

Next Generation Air Transportation System

Airspace Project

NASA ASAS Activities:Decision Support forAirborne Trajectory Management & Self-Separation

Robert A. Vivona

AOP Lead Engineer

L-3 Communications

Billerica, MA

presentation overview
Presentation Overview
  • Background
    • Airborne trajectory management
  • Autonomous Operations Planner (AOP)
    • Provided ASAS functions
    • System interface
    • Capabilities
  • AOP Experimental Performance
  • Concluding Remarks
background airborne trajectory management

En Route Airspace

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Q

Self-separating

Q

Ground managed

Q

Q

Q

Q

Q

Q

Q

Q

Q

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

Terminal Airspace (Merging & Spacing)

  • ATSP Responsibilities
  • Manage airspace resources
    • Generate flow constraints
    • Datalink to autonomous aircraft
  • Control ground managed aircraft
autonomous operations planner aop

Tactical ManeuverRestriction Region

Resolution ManeuverUploaded to FMS asMod Route

Area of ConflictAlong CurrentFMS Route

Conflict

Aircraft

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

Navigation Display

aop provided asas functions
AOP: Provided ASAS Functions

*Source: FAA/Eurocontrol Cooperative R&D AP23

aop system interface

Flight Management

System (FMS)

Flight Control

Computer (FCC)

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

Autonomous

Operations

Planner (AOP)

AVIONICS DATA BUS

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

Mode Control Panel (MCP)

AOP

Inputs

Multi-Function Control

& Display Unit (MCDU)

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

AOP

Outputs

Integrates with

Existing Avionics

& Displays

Navigation Display

Primary Flight Display (PFD)

aop capabilities
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

7

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

conflict management
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
conflict management9
Conflict Management

FMS Predicted

Top-of-Descent

State vector projection

VNAV PATH

LNAV/VNAV

VNAV ALT

Commanded prediction

MCP altitude limit

Planning prediction

VNAV PATH

Active Route

Altitude Constraint

Secondary CD Alerting

Primary CD Alerting

  • 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
  • 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
conflict management10

LNAV

TRACK HOLD

TRACK HOLD

On path

Off path

Within capture

Off path

Beyond capture

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

Commanded

Commanded

Blunder

Protection

Commanded

Last

LOS

Planning

First

LOS

conflict management conflict detection resolution
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
conflict management intent based cd
Conflict Management: Intent-Based CD
  • 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

ownship

traffic

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)

State Vector Report (SVR)

Mode Status Report (MSR)

Air Referenced Velocity Report (ARV)

Target State Report (TSR)

Trajectory Change Report (TCR)

Intent-Based CD: Trajectory Prediction

ADS-B

intent based cd trajectory prediction uncertainty buffers

Time

Altitude

Cross-track

Intent-Based CD:Trajectory Prediction Uncertainty Buffers

Vertical

Cross-track

Time

  • 4D “tube” around 4D trajectory
  • Encapsulates prediction uncertainties unique to each segment type

Time

Lateral path

conflict management intent based conflict resolution
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
conflict management intent based conflict resolution16

Altitude

Advisory

Track

Advisory

Vertical Rate

Advisory

Primary Flight

Display

Nav Display

Conflict Management:Intent-Based Conflict Resolution

Active Route: Magenta

Resolution Route: Blue

Nav Display

Strategic Intent-Based CR

Tactical Intent-Based CR

conflict management state based cd r
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 Potential

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

FMS

Provisional

Conflict

Lateral MR

Band

MCP

Provisional

Conflict

Maneuvering Without Conflict(Conflict Prevention)

Manual MOD

Route in FMS

Non-active

Change in MCP

Track Setting

(e.g., in LNAV)

aop experimental performance

2x 3

10x

AOP Experimental Performance

Experiment 1: Lateral Only, Random Routes, All Autonomous

10X playback speed

Lateral Strategic CR Only

NASA Air Traffic Operations Lab

All aircraft co-altitude, circle diameter 160 NM

Sustained Mean Density1 17.18

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.

aop experimental performance20
AOP Experimental Performance

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

Lateral Strategic CR Only

(CPA < 0.02 nmi)

(*)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 the

Safety Performance of Airborne Separation. ATIO 2008.

aop performance batch experiment 2

Number of intruder aircraft per conflict resolutions.

AOP Performance: Batch Experiment 2

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

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

AOP Intent-Based CD&R Studied

Under Highly Complex Traffic Scenarios

concluding remarks current nasa efforts
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
concluding remarks aop references
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.
demonstration
Demo

~10x traffic density

10x playback speed

Long range display

No display filtering

Demonstration

Lateral Intent-Based CR

Navigation

Display