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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 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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  1. 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

  2. Presentation Overview • Background • Airborne trajectory management • Autonomous Operations Planner (AOP) • Provided ASAS functions • System interface • Capabilities • AOP Experimental Performance • Concluding Remarks

  3. 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

  4. 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

  5. AOP: Provided ASAS Functions *Source: FAA/Eurocontrol Cooperative R&D AP23

  6. 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)

  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 7 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

  9. 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

  10. 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

  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

  12. 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

  13. 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

  14. 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

  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

  16. 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

  17. 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

  18. 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)

  19. 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.

  20. 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.

  21. 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

  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

  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.

  24. Demo ~10x traffic density 10x playback speed Long range display No display filtering Demonstration Lateral Intent-Based CR Navigation Display

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