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Psychophysiological aspects of Human-System Integration i C4 and operation safety
This document discusses psychophysiological challenges in integrating humans with communication, control, and command systems, and how this relates to operational safety. It covers: 1. Current trends in autonomous weapons systems like drones and challenges in integrating humans into complex automated systems. 2. A new HSI (Human-System Integration) paradigm that treats humans not as a source of errors but as key to system reliability. 3. Examples of how considering human factors like cognition can improve system design and decision making, illustrated through drone operator selection and training systems using techniques like augmented cognition and reality and biofeedback.
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Psychophysiological aspects of Human-System Integration i C4 and operation safety
- 1. „Psychofizjologiczne problemy integracji człowiekaz systemami: łączności, sterowania i dowodzenia a bezpieczeostwo operacji” • Jerzy Achimowicz, Olaf Truszczyoski, Grzegorz Nowicki • Zakład Bezpieczeostwa Lotów i Klinika • Wojskowy Instytut Medycyny Lotniczej • Ul. Krasioskiego 54, 01-755 Warszawa, 6. KONFERENCJA URZĄDZENIA I SYSTEMY RADIOELEKTRONICZNE POD PATRONATEM Komitetu Elektroniki i Telekomunikacji Polskiej Akademii Nauk Komitetu Narodowego Międzynarodowej Unii Nauk Radiowych
- 2. STRESZCZENIE • • Autorzy pracy dokonująprzeglądu aktualnych tendencji rozwojowych i problemów badawczych pojawiających się na skutek szybkiego rozwoju autonomicznych systemów uzbrojenia takich jak bezzałogowe pojazdy latające i naziemne oraz podwodne roboty pola walki. • Mimo powszechnej automatyzacji systemów sterowania systemami pozwalającymi na rozpoznanie pola walki, prowadzenie działao bojowych oraz dowodzenie rożnymi rodzajami wojsk z zapewnieniem interoperacyjnosci w systemie NATO, rola czynnika ludzkiego staje się coraz ważniejsza. • Z doświadczeo NASA w zakresie projektowania i realizacji złożonych misji/projektów takich jak np. nowy system kontroli lotów lotnictwa cywilnego i wojskowego wynika ze można osiągnąd większe bezpieczeostwo operacji jeżeli zmieni się tradycyjne podejście do integracji człowieka ze złożonymi systemami już na etapie ich projektowania. W tzw. modelu HSI (Human-System Integration) człowieka nie traktuje się jako potencjalne źródło problemów/błędów ale jako główny element systemu zapewniający jego niezawodnośd. • W związku z tym w procesie projektowania np. centrów dowodzenia misją uwzględnia aktualne osiągnięcia w dziedzinie psychofizjologii przede wszystkim umożliwiające określenie zdolności poznawczych człowieka o raz ich zwiększanie prowadzące do efektywnego podejmowania trafnych decyzji. • Powyższe podejście zostanie zilustrowane na przekładzie systemów selekcji i szkolenia operatorów dronów, projektowania ich systemów pilotażu wykorzystujących takie techniki jak augmented cognition and reality raz biofeedback AFTE ( Autogenic Feedback Traing Exercise) i BCI (Brain Computer Interface). •
- 5. Human Systems Integrationin Maintenance A technician performs maintenance on a Space Shuttle Main Engine (SSME) in building 3202 in preparation for a test firing at the NASA Stennis Space Center. (ca. 2002) 5
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- 7. A View ofthe Human-Machine Interface INTERPRETATION SITUATION ASSESSMENT DECISION MAKING PERCEPTION ACTION EXECUTION SYTEM CONTROL HMIs RECEIVE INPUT PROVIDE FEEDBACK TO USER MACHINE OPERATIONS 7 Information Processing Model Wickens 1992
- 8. Conceptual Shift From Human–Machine Interface • From humans as a source of error… • To humans as a source of resilience To a new paradighm – HSI • (Human System Integration) 8
- 9. New approach: HSIand Automation Human Systems Integration • Iterative technology requirements • Resilience and error implications • Complex environment • Task requirements Automation and Computer Science 10/31/2013 9 9
- 10. Adapted from HSIchart by Based on DoD HSI Acquisition Approach (e.g., Army’s MANPRINT) Human-Systems Integration: Systems Engineering Motivation Reduced Maintainability Reduced Life-Cycle Cost and Improved Safety and Mission Success Reduced Staff Improved Human Productivity and System Performance Fewer Errors (Fewer Mishaps, Reduced Scrap, Fewer Delays) Together, these building blocks produce Optimal* Human Performance System and Task Design Human Capabilities And Competencies Human Workload Fitness for Duty Human-System Interfaces Adequate Knowledge, Skills, and Abilities Staffing and Work Distribution Human is Qualified, Rested, Motivated, and Healthy Human Factors Engineering Personnel Selection Training Manpower 10 Human-Systems Integration Personnel Safety and Survivability Habitability 10
- 11. HSI Research Philosophy HumanPerformance Model-Based Requirements & Standards Human Performance Metrics & Models Requirements/Needs Technologies & Capabilities System Design Generative Mechanisms of Human Performance 11 11
- 12. Psychophysiology: from understanding functions todeveloping countermeasures for a more resilient system and hence greater operation safety AUGMENTED REALITY AND AUGMENTED COGNITION 12
- 13. Flight Deck DisplayResearch Laboratory General Research Focus • Human-centered concepts of operation for the Next Generation Air Transportation System automation that promote – Situation Awareness – Transparent Automation – Seamlessly Shared Authority The major element of our work is the Cockpit Situation Display
- 14. UAV Ground StationInterface Advanced Flight Deck Interface The Flight Deck Display Research Laboratory (FDDRL) develops advanced display concepts and prototypes to support the Next Generation Air Transportation System.
- 15. Cockpit Situation Display(CSD) This presentation is a brief overview of the CSD, a prototype display developed by the FDDRL to support: Integrated Traffic Awareness Terrain Awareness Weather Awareness Trajectory Management Based upon availability of high quality information on traffic, weather and terrain 15
- 16. Weather Display Goal isto develop an intuitive 3D convective weather display. Today: Classic Airborne Radar 2D – Storm tops not displayed, must use tilt Range Limited – More tactical view Immediate NextRad 2D – Storm tops still not typically displayed Range unlimited - Strategic Updates every 5-10 min Today/Tomorrow: FAA is investing in “4D Weather Cube” Range Unlimited - Stragetic 3D – Storm top information available 4D – Forecast information available Updates every 1 min 16
- 17. Terrain Display Goal isto develop a strategic trajectory-based terrain hazard display • USGS SDTS DEM 30 meter Data • 3D extruded terrain for low altitude 3D viewing • 2D projection for high altitude 3D viewing • Trajectory based terrain alerting American Sierra Nevada range approach Tahoe Nevada 17
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- 19. LS3 Program &AlpaDog
- 20. • Tag TeamThreat-recognition Technology Incorporates Mind, Machine • September 18, 2012 • DARPA links human brainwaves, improved sensors, cognitive algorithms to improve target detection • http://www.darpa.mil/NewsEvents/Releases/2012/09/18.aspx Read more: http://www.digitaltrends.com/cool-tech/this-is-your-brain-onsilicon/#ixzz2hv529y8z Follow us: @digitaltrends on Twitter | digitaltrendsftw on Facebook
- 21. BCI – BrainComputer Interface Basically, a soldier wears an electroencephalogram (EEG) cap that monitors his brain signals as he watches the feed from a 120-megapixel, tripod-mounted, electro-optical video camera with a 120-degree field of view. (Translation: incredible detail in a huge range of vision.)
- 23. AFTE- Autogenic FeedbackTraining Exercise
- 24. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. Blood Volume Pulseleft hand Blood Volume Pulse right hand Respiration Rate AFTE Heart Rate Skin Conductance Level Hand temperature Blood flow – head Blood flow – toe EMG – left arm EMG – right arm EMG – left leg EMG right leg Systolic Blood Pressure Diastolic Blood Pressure Mean Arterial Pressure Thoracic Fluid Volume Stroke Volume Cardiac Output Total Peripheral Resistance Vagal Tone Trainer Controls 20 Displays
- 25. Typical Preflight AFTESession Heart Rate 85 20 liters/min ohms/cm 65 160 55 Cardiac Output 16 200 75 bpm Stroke Volume 240 12 8 120 4 45 80 Skin Conductance Level Mean Arterial Pressure 110 Total Peripheral Resistance 20 40 16 90 35 units micromhos mmHg 100 12 30 8 80 25 70 20 4 1 25 49 73 97 121 15-second means 145 169 1 1 25 49 73 97 121 15-second means 145 169 25 49 73 97 121 145 169 15-second averages
- 26. BioHarness and Software Measures BioHarness •Electrocardiography • Respiration • Chest Skin Temperature • Posture • Activity • Acceleration (XYZ), minimum and peak • Requires non-skin contact sensors • Can interface with a PC or cell phone • No sensors for skin conductance, hand temperature, and blood flow, EMG
- 27. • Sustained Operations: Fatigue,vigilance, sleep loss, contribute to human error accidents A Autonomous Mode Behavior: condition when a high state of physiological arousal is accompanied by a narrowing of the focus of attention
- 28. Performance x Phasesof Flight flight 1 (pre-training) vs flight 2 (post-training): AFTE Performance Dimensions Crew Coordination Planning and and Situational Communication Awareness Checklist execution Stress Management Aircraft Handling * Taxi/takeoff Initial cruise Touch & go + Cruise search & rescue Emergency initiation * Emergency return to base Emergency approach & landing * * * * * * * * * * flight 1 vs flight 2 for Controls were not significant, except a lower score for touch and go (+) on flight 2 * * p <0.05
- 32. Future Applications ofAFTE Transfer NASA Technology and Validation Studies • • • • Training of Polish Military Pilots Training of U.S. Naval Pilots for Airsickness Mitigation Training of U.S. Veterans as a Treatment for PostTraumatic Stress Syndrome Training of Astronauts and Cosmonauts Develop/ Test New Monitoring and Training Capabilities • Stream-line software • Neuro-feedback and autonomic coherence • Unobtrusive physiological Monitoring
- 33. Towards a dynamicbalance between humans and automation: authority, ability, responsibility and control in shared and cooperative control situations • Übersicht Flemisch, F.; Heesen, M.; Hesse, T.; Kelsch, J.; Schieben, A.; Beller, J.: Towards a dynamic balance between humans and automation: authority, ability, responsibility and control in shared and cooperative control situations, In: Cognition, Technology & Work (CTW), Springer, Berlin 2011, ISSN 1435-5558, S. 1-16 (online) Kurzfassung Progress enables the creation of more automated and intelligent machines with increasing abilities that open up new roles between humans and machines. Only with a proper design for the resulting cooperative human– machine systems, these advances will make our lives easier, safer and enjoyable rather than harder and miserable. Starting from examples of natural cooperative systems, the paper investigates four cornerstone concepts for the design of such systems: ability, authority, control and responsibility, as well as their relationship to each other and to concepts like levels of automation and autonomy. Consistency in the relations between these concepts is identified as an important quality for the system design. A simple graphical tool is introduced that can help to visualize the cornerstone concepts and their relations in a single diagram. Examples from the automotive domain, where a cooperative guidance and control of highly automated vehicles is under investigation, demonstrate the application of the concepts and the tool. Transitions in authority and control, e.g. initiated by changes in the ability of human or machine, are identified as key challenges. A sufficient consistency of the mental models of human and machines, not only in the system use but also in the design and evaluation, can be a key enabler for a successful dynamic balance between humans and machines. • Schlagworte Assistant systems, Automation, Human-machine cooperation, Adaptive automation, Levels of automation, Balanced automation
Editor's Notes
- #14 NextGenComplex mixture of coevolving operational concepts (roles, responsibilities) for human participants (aircraft and UAV pilots, air traffic controllers, and automation)These concepts result in more responsibilities being distributed to the flight deck and to automation.Automation development often runs ahead – we must anticipate or at least keep up
- #15 The Flight Deck Display Research Laboratory (FDDRL), a part of the Human Systems Integration Division at the NASA Ames Research Center, develops and examines human-centered concepts that address projected changes in roles and responsibilities in the US Air Traffic Management System. As a part of this effort the FDDRL develops prototype display interfaces and, through empirical research (mainly large-scale distributed human-in-the-loop simulations), develops guidelines for the integration of flight deck displays, decision support tools, and automation.The lab's principal product is the Cockpit Situation Display (CSD). The CSD, designed around the lab’s advanced Cockpit Display of Traffic Information (CDTI), was originally built for, and incorporated into, the 2004 Distributed Air-Ground Traffic Management (DAG-TM) simulations. In that project it served as the primary visual interface for both medium-fidelity single and multi-pilot simulators. It also served as the primary visual interface for the high-fidelity full-mission Advanced Concepts Flight Simulator at the Ames Crew Vehicle System Research Facility. Since its inception, many of the lab's part-task experiments have examined, or leveraged, CSD technologies. CSD stations have been deployed at several institutions throughout the country where they have been used collaboratively with the FDDRL to study significant human-in-the-loop (HITL) issues. The CSD has been designed to be easy to configure, allowing its various features and embedded tools to be selectively enabled or disabled. This, in turn, has made it an easily used research platform, and the basis for much experimentation and exploration. Within the FDDRL the CSD forms the basis for fast prototyping and subsequent HITL examination of near and far-term airspace concepts and flight deck procedures.
- #16 The CSD is designed to provide an integrated,but clutter resistant/tolerant 2D-4D visualization With a graphical user interface to the flight management systemthe display is based on a cylindrical container-like metaphor, and the flight crew can simply rotate this cylindrical space into various orientations for preferred viewing angles. Transitions (panning, zooming, etc) are morph-animated to maximize continuous orientation awareness. Weather objects and terrain features not only provide useful positional and hazard cues along a proposed route.
- #17 2D/3D Weather Display. Pilot-selectable 2-D and 3-D depictions of weather objects and terrain features are integrated into the display, and allow intuitive and direct evaluation of the relationship of these hazards to the intended route. We develop our 3D storms either with a tool that allows us freedom to fabricate what we want, or start with recorded NextRad weather files and apply simple rules to do simple instantiations of the weather cells. Mostly we do a bit of both.
- #18 The 3D Terrain Display provides location and strategic hazard cues to pilots.Flight planning incorporates real-time interactive hazard detection of terrain by orange highlighting of proximal regions of terrain along the present path. Route Analysis Tool used to resolve. The terrain conflict color on this route is yellow, to distinguish the conflict along the proposed route from the terrain conflict along the present route (in orange).By manipulating the route we can find a trajectory that is clear and implement it. In this case by altitude change.