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Traffic Manager (TMX) Modifications to Support NextGen Studies at NASA-Langley Research Center

Traffic Manager (TMX) Modifications to Support NextGen Studies at NASA-Langley Research Center. Kurt W. Neitzke NASA Langley Research Center Innovations in NAS-Wide Simulation George Mason University, VA 27-28 January 2010. Outline. TMX Background & Overview Development History

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Traffic Manager (TMX) Modifications to Support NextGen Studies at NASA-Langley Research Center

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  1. Traffic Manager (TMX) Modifications to Support NextGen Studies at NASA-Langley Research Center Kurt W. Neitzke NASA Langley Research Center Innovations in NAS-Wide Simulation George Mason University, VA 27-28 January 2010 GMU-SIM-JCS, January 2010

  2. Outline • TMX Background & Overview • Development History • Architecture • Supported Research Studies • Current enhancements • Remaining Gaps GMU-SIM-JCS, January 2010

  3. Background** • TMX development began in 1996 by National Aerospace Laboratory of the Netherlands (NLR) to study “Free Flight”, where: • Properly equipped aircraft allowed to choose own flight path • While maintaining separation from all other aircraft (airborne separation assistance system (ASAS)) • Originally designed to support human in the loop (HITL) studies related to Free Flight to develop and compare different conflict resolution algorithms • TMX updated periodically to date, by NASA Langley and NLR to support specific research studies primarily related to airborne separation assistance • Evolved capabilities now include: • Stand alone Fast-time or Batch simulator • Links readily to other air traffic simulations (e.g. Airspace and Traffic Operations Simulation (ATOS) at NASA-LaRC) ** Source: Traffic Manager: A Flexible Desktop simulation Tool Enabling Future ATM Research; Bussink, F.J.L., et. al., 2005 IEEE GMU-SIM-JCS, January 2010

  4. TMX Overview TMX features Include: • Operates on single computer platform, Windows OS • Capable of ~ 2000 aircraft simultaneously aloft (typ. supporting regional, not NAS-wide studies) • BADA performance models (200 aircraft reference fleet) • Autopilot model (with basic altitude, speed and heading modes as well as the FMS coupled LNAV (lateral) and VNAV (vertical & speed) modes • Conflict detection & resolution (CD&R) system selectable from up to 10 variants or none, including state, and intent based • Conflict Prevention System (P-ASAS) – “Go – No-Go” bands on cockpit display to prevent pilot maneuvering into short-term (< 5 min. typically) conflicts • A 4D-FMS with route following, & Required Time of Arrival (RTA) meeting (closed loop) capability • Pilot model with parameters for reaction time, scheduling effects and recovery manoeuvres • ADS-B models • Separate transmit & receive models • Includes range limits & signal drop-out (simple) • Winds (truth & forecast) • Surveillance view or pilot viewpoint GUI (can disable for batch sim’s) Source: Traffic Manager User’s Manual, Version 5.31; Hoekstra, J. GMU-SIM-JCS, January 2010

  5. TMX Architecture Source: Traffic Manager: A Flexible Desktop simulation Tool Enabling Future ATM Research; Bussink, F.J.L., et. al., 2005 IEEE GMU-SIM-JCS, January 2010

  6. TMX Surveillance View Source: Traffic Manager User’s Manual, Version 5.31; Hoekstra, J. GMU-SIM-JCS, January 2010

  7. TMX Surveillance View AFR aircraft (green) and IFR aircraft (blue) GMU-SIM-JCS, January 2010

  8. Research Studies Supported • 2008; A Performance Assessment of a Tactical Airborne Separation Assistance System Using Realistic, Complex Traffic; Smith, J.C. et. al.,, The 26th Congress of International Council of the Aeronautical Sciences (ICAS) • 2004; Fast-time study of Airborne Merging and Spacing for Terminal Arrivals (AMSTAR) • 2004; HITL experiment supporting integrated air/ground operations feasibility under the En Route Free Maneuvering component of Distributed Air/Ground - Traffic Management (DAG-TM) Concept • 2004;In-FlightTraffic Simulation for Self-Separation and Sequencing (SSS) Flight Experiment conducted by NASA LaRC as part of the Small Aircraft Transportation System (SATS) project • traffic generation, conflict detection and prevention, visual and audio alerts and was used as a decision support tool in support of self-separation operations • Integral part of Air Traffic Operations Laboratory (ATOL) at NASA-LaRC • Interactive background air traffic GMU-SIM-JCS, January 2010

  9. TMX Enhancements • Integration of Airborne Coordinated Conflict Resolution and Detection (ACCoRD) based CP-Bands • Integration of Strategic, Intent-based CD&R capability StratWay (Strategic Waypoint adjustment program) • Integration of NASA TFM functionality • Outline approach for future integration of weather data into TMX • Create a distributed architecture version of TMX to enable NAS-Wide simulation and higher traffic volumes (compared with stand-alone TMX) GMU-SIM-JCS, January 2010

  10. TMX Conflict Prevention System GMU-SIM-JCS, January 2010 10

  11. Integration of Airborne Coordinated Conflict Resolution and Detection (ACCoRD) based CP-Bands • Conflict Prevention System displays “bands” to pilot to indicate trajectory changes that will cause a short-term conflict (yellow ~ 3-5 minutes; red~ <3 min.) • CP Bands on: • Heading changes • Vertical speed changes • Horizontal speed changes • Trajectory changes may be due to conflict resolution or part of the flight plan • Can be used by pilot model (in batch study, or as background traffic in HITL experiment) or directly by human pilot in HITL experiment • Includes formal methods proof of “correctness” of the CP-Bands algorithms • Replaces existing CP-Bands developed by NLR GMU-SIM-JCS, January 2010 GMU-SIM-JCS, January 2010 11

  12. Integration of Airborne Coordinated Conflict Resolution and Detection (ACCoRD) based CP-Bands • Conflict Bands algorithm uses ACCoRD to determine conflict envelope • Supports multiple conflict regions • Deterministic, formal V&V Heading conflict zone corrected with altitude and time Resolution with multiple simultaneous conflicts GMU-SIM-JCS, January 2010 GMU-SIM-JCS, January 2010 12

  13. Integration of Strategic, Intent-based CD&R capability StratWay (Strategic Waypoint adjustment program) GMU-SIM-JCS, January 2010 GMU-SIM-JCS, January 2010 Strategic CD&R algorithm under development is “StratWay” (Strategic Waypoint adjustment program) Performs piece-wise inspection of planned waypoints Uses Bands algorithms for conflict detection and resolution options Moves minimum number of waypoints to de-conflict 13

  14. Integration of NASA TFM Functionality ** • Concept to manage air traffic flow under uncertainty in airspace capacity and demand • Sequential optimization method • Integrates deterministic integer programming model for assigning delays to aircraft under en route capacity constraints • Reactively accounts for system uncertainties • Assigns only departure controls • Two additional elements associated with the ref. TFM Capability related to tactical weather re-routing, and airborne holding will not be integrated into TMX at this time ** Source: Sequential Traffic Flow Optimization with Tactical Flight Control Heuristics; Grabbe, Shon, et. al., 2008, AIAA Guidance Navigation and Control Conference and Exhibit GMU-SIM-JCS, January 2010 GMU-SIM-JCS, January 2010 14

  15. Integration of NASA TFM Functionality ~ Not included in current TMX mod’s Source: Sequential Traffic Flow Optimization with Tactical Flight Control Heuristics; Grabbe, Shon, et. al., 2008, AIAA Guidance Navigation and Control Conference and Exhibit GMU-SIM-JCS, January 2010 GMU-SIM-JCS, January 2010 15

  16. Define approach for integrating weather data into TMX • Purpose: allow the evaluation of different strategic weather mitigation approaches using TMX • Current, simple TMX weather avoidance capability uses CP-Bands to tactically avoid 3-D weather poly-spaces • New Weather databases available soon via NRA; Realistic Weather Data to Support NextGen ATM Concept Simulations (two NRA awards: Sensis, & Raytheon) • provide recorded real-world and simulated weather data • Provide associated software tools to manage the data and create appropriate scenarios GMU-SIM-JCS, January 2010 GMU-SIM-JCS, January 2010 16

  17. Distributed TMX Architecture TMX Node TMX Node TMX Node TMX Node ADS-B CD&R Scheduling Time Synchronization Output Recording Distributed TMX Nodes Trafficdata Time Sync. Resolutions Central Control Node

  18. Distributed TMX Architecture; Development Objectives • Capability to handle NAS-wide simulation • 20,000+ aircraft simultaneously aloft • Handle full range of mixed AFR-IFR aircraft • Improve code efficiency • Shorten simulation run-time GMU-SIM-JCS, January 2010 GMU-SIM-JCS, January 2010 18 18

  19. Distributed TMX Status Start/stop TMX nodes Receive TRAFFIC data Traffic range computations ADS-B updates Conflict detection checks Conflict resolution computations Send resolutions to TMX nodes

  20. Distributed TMX Validation Two A/C case TMX vs. 1-node D-TMX 1000 A/C case TMX vs. 1-node D-TMX 1000 A/C case TMX vs. multi-node D-TMX (250 A/C per TMX node) Detailed (1000 A/C) case checking trajectories and resolutions

  21. Remaining Gaps (fr. Presenter’s perspective) NAS-Wide simulation tools have matured greatly over the past five years – however: They span a broad system - The NAS! (can the World be far behind?) Determining a “prudent mix” of which NAS systems will be explicitly vs. implicitly modeled to deliver the desired information is study-dependent often Understanding the validity bounds of results is difficult, and typically “in the eye of the beholder” Don’t know whether current simulation capabilities are sufficient to answer highest priority NextGen research questions right now or not Need to enter vigorous period of exercising the tools to reveal their capability shortcomings Use multiple tools to simulate the same scenario and compare results Synthesize comparison to formulate future tools & methods development plan How can broader, lower detail simulations (like NAS-wide) be more directly complementary to narrower, more detailed simulations (and vice versa?) Do NAS-Wide Simulations need to – “do it all”?

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