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A Distributed Networked Capability for Simulations of Current Day and NextGen Airspace Environments Thomas Z. Strybel Center for Human Factors in Advanced.

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Presentation on theme: "A Distributed Networked Capability for Simulations of Current Day and NextGen Airspace Environments Thomas Z. Strybel Center for Human Factors in Advanced."— Presentation transcript:

1 A Distributed Networked Capability for Simulations of Current Day and NextGen Airspace Environments Thomas Z. Strybel Center for Human Factors in Advanced Aeronautics Technologies (CHAAT) A NASA University Research Center August 15, 2011

2 Overview What is CHAAT Why distributed simulations? NASA Software Involved: – AOL and FDDRL Benefits to NASA –Remote support –Onsite support Benefits to CHAAT –Education experiences –Research Acknowledgements

3 A NASA University Research Center  Achieve broad-based, competitive aerospace research capability among the nation's minority institutions  Foster new aerospace science and technology concepts and expand the nation's base for aerospace R & D  Increase the participation of socially and economically disadvantaged students in STEM careers What is CHAAT? CHAAT Research Goals Metrics for operator situation awareness, workload and performance in NextGen Part-task simulations for identifying the most promising automation concepts Information requirements and critical task components for training future NextGen operators Design recommendations for human- machine interfaces CHAAT Education Goals Attract and train more students in NASA- relevant majors (especially minority and underrepresented groups ) Inspire K-12 students to pursue STEM careers. Opportunities for faculty collaborations between NASA and other universities

4 Overview: NextGen NextGen changes: Roles and responsibilities between air and ground operators Automation technologies CONOPS Increased reliance on automation Changes affect: Situation awareness Workload Performance CHAAT: Metrics for operator situation awareness, workload and performance in NextGen Part-task simulations for identifying the most promising automation concepts Information requirements and critical task components for training future NextGen operators Design recommendations for human-machine interfaces Comprehensive Overhaul of NAS increase capacity improve safety increase reliability

5 Distributed Simulation? *Lee, A.T. (2005). Flight Simulation: Virtual Environments in Aviation. Vermont: Ashgate ** Prevot, T. (2002). Exploring the many perspectives of distributed air traffic management: The multi aircraft control system MACS. International Conference on Human-Computer Interaction in Aeronautics, HCI-Aero 2002, October, MIT, Cambridge, MA.. Why: Cognitive Fidelity* Degree to which the simulated task environment places cognitive demands on operators that are comparable to those experienced in operational settings Implications for Human-in-the-Loop (HIL) Simulations Simulations must place demands on information acquisition and integration, decision making, problem solving, etc. Involves simulators and task environment NextGen Simulations** Cognitive fidelity achieved by: Automating roles that are not the focus of the research Adding more role players to the simulation Educational Benefit A valuable tool for training the future workforce in human factors and NASA-relevant STEM technologies What: Human-in-the-loop simulations over the internet when operators and/or participants are located at remote sites

6 Distributed Simulation CHAAT- FDDRL

7 Multi-aircraft Control System (MACS) Used for simulations, rapid prototyping, and concept evaluation Can be configured for several operating modes: ATC en route, ATC TRACON, pilot, pseudopilot, simulation manager, etc.) Aeronautical Datalink and Radar Simulator (ADRS) Routes information amongst client processes during a simulation Provides data about precise aircraft positions and states, flight plans, etc. Software: MACS and ADRS from NASA AOL (Prevot, 2002) MACS DSR Mode MACS Simulation MangerMACS Single Pilot Mode

8 Software: 3D-CSD and DagVoice from FDDRL 3D Cockpit Situation Display (CSD) (Grandada et al., 2005) Volumetric representation of the surrounding 3D traffic environment, Terrain, weather, CD&R, spacing DAGVoice (Canton et al., 2005) Multicast, multichannel, voiceIP communication system Emulates pilot and ATC radio communications

9 Distributed Master - FDDRL (George Lawton) Capabilities Integrates simulation system start-up using single interface Send commands using script-based code Provides system-wide status feedback Updates simulation software on all stations Finds, copies, and transfers data to file server Advantages Reduces number of points of failure Provides control over system start-up and shutdown Provides basic system error alerting Enables minimally-intrusive remote troubleshooting and system restart control Easy and consistent data archiving function

10 CHAAT Simulation Capability Benefits NASA A flexible high-cognitive-fidelity HIL simulation capability at a reduced cost NASA FDDRL has expanded its flight deck simulation capability by adding pseudopilot stations and an ATC center for its simulations of flight deck automation tools without adding physical components and personnel –CHAAT has served as ground control for several FDDRL simulations of pilot merging and spacing operations in the presence of weather. –Hardware, software, and trained operators available for all simulation roles –Operators obtained from retired ATCs in the community, student ATCs from MtSAC, and students at CSULB who are studying human factors

11 CHAAT Remote-Site Support of NASA FDDRL Simulations Distributed Simulation of UAS’s Flying in Terminal Airspace (2006) Trajectory Oriented Operations with Limited Delegation during Convective Weather (TOOWiLDx) Simulation Demonstrations (2008) Evaluation of Automated Spacing Support Tools for Interval Management Operations under Hazardous Weather Conditions (2009) Situation Awareness and Workload with Trajectory Oriented Operation in Weather I and II (2009)

12 Situation Awareness and Workload in Trajectory Oriented Operations with Weather 777 Cockpit Simulator Desktop Cockpits Simulation Manager Distributed Master En route ATCs Ghost ATCs Pseudopilots CHAAT CSULB NASA FDDRL ADRS Pseudopilots A Distributed Simulation: NASA and Three Universities

13 CHAAT On-Site Support of NASA Simulations FDDRL –Five students support FDDRL simulation project WATERSHED (2011) –Four students and faculty support FDDRL simulation project SAFARI (2010) –Three students support FDDRL Audio Twitter simulation project (2009) FDDRL and AOL –Three students support air-ground simulation of off-nominal events (2008) Aviation Systems Division –One student supports UAVs flying in high altitude airspace simulation (Access-5)

14 Educational Benefits of Distributed Simulation Distributed Simulation “Hands On” Distance Learning CHAAT Students Interact with NASA scientists remotely and directly E.g., CHAAT interns trained at CSULB prior to arriving at NASA Students graduate with expertise and experience in Basic and applied research and experimental design Airspace operations (air and ground) Simulation development and analysis Scenario development Airspace human factors NASA and aerospace industry get workforce with “known” capabilities

15 CHAAT Students Benefit from NASA Software 4 student theses in progress based on MACS and CSD Over 40 graduate/undergraduate students trained in NASA software, simulation techniques, airspace operations and human factors Over 60 students from MtSAC have gained radar experience prior to entering the FAA Academy Approximately 20 eighth-grade girls were exposed to ATC operations and NASA software

16 Acknowledgements We at CSULB and CHAAT thank NASA for their continued support of our distributed simulation capability, research and training programs. Walter Johnson Vern Battiste Joel Lachter Arik-Quang Dao Riva Canton Dominic Wong Richard Mogford Summer Brandt George Lawton Jay Shively Tom Prevot Ev Palmer Joey Mercer Paul Lee Nancy Smith Jeff Homola Dave McNally P.K. Kopardekar Michelle Eschow Patty Jones Todd Callentine John Robinson Mary Connors Savvy Verma Brenda Collins Maria Lopez Katrina Emery Thank You!!


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