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Modelling the effect of stress on Human Behaviour May 12 1999 LTSS51 Orlando

Modelling the effect of stress on Human Behaviour May 12 1999 LTSS51 Orlando. Andy Belyavin CHS DERA. Aims of the presentation. Outline the scope of the problem from a modelling perspective Sketch a structure in which the problem might be solved Outline implementation in IPME

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Modelling the effect of stress on Human Behaviour May 12 1999 LTSS51 Orlando

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  1. Modelling the effect of stress on Human BehaviourMay 12 1999LTSS51 Orlando Andy Belyavin CHS DERA

  2. Aims of the presentation • Outline the scope of the problem from a modelling perspective • Sketch a structure in which the problem might be solved • Outline implementation in IPME • Generalise the approach to broader class of architectures • Man as system of systems - possible solutions

  3. Aims of the presentation • Outline the scope of the problem from a modelling perspective • Sketch a structure in which the problem might be solved • Outline implementation in IPME • Generalise the approach to broader class of architectures • Man as system of systems - possible solutions

  4. Role of constructive simulation • Entities involved in man-in-the-loop virtual simulation for training • In future analysis of military systems it can be anticipated that there will be more use of man-in-the-loop virtual simulation • This will be effective for managing the burden of the analysis of tactics and outline questions on crewing and systems definition • It will not support the analysis of system performance in all contexts • There will be a large role for the constructive simulation of human behaviour under stress

  5. Constructive modelling of human performance • Based on a structure of what the crew has to do • Task analysis leading to task networks • IMPRINT • MicroSAINT • Task frames in SAFs • ModSAF • Rule bases in command agents coupled to SAFs

  6. Classical approach to stress representation • Define task taxonomy • Cognitive task • Perceptual task • Physical task etc. • Map environmental stress to task types • ‘Arousal’ affects cognitive performance etc. • Model effect as a crude degradation • Adjust task time and precision

  7. Long term strategy for stress description • Three things have to be achieved: • Define the phenomenon we are trying to represent • Define the stressors we need to consider • Define nature of best scientific knowledge • Review current approaches • How is it done in current tools? • SAFs, IMPRINT, IPME • Project how these methods should develop

  8. Aims of the presentation • Outline the scope of the problem from a modelling perspective • Sketch a structure in which the problem might be solved • Outline implementation in IPME • Generalise the approach to broader class of architectures • Man as system of systems - possible solutions

  9. Environmental stressors • A 1994 review at DERA identified more than 40 stressors • These include both regular environmental factors and social effects • Suggest that even a concise list of the most important is 10 long

  10. Environmental stressors (2) • Sleep loss fatigue / circadian effects and time on task • Physical fatigue • Thermal effects (Thermal strain / dehydration / discomfort) • Visual environment • Fear / Anxiety / Morale • Task demand - workload • Noise (continuous and impulse) • Vibration • Hypoxia (Loss of oxygen in high flying fast jets) • High G (Fast jets only)

  11. Metrics of “behaviour” • What is the crew / operator going to do? • Generally domain of cognitive analysis – possibly open ended • How good is Situation Awareness? • What course of action is selected? • Given what the crew /operator does, how well do they do it? • Generally domain of task analysis and task performance • How fast is the task completed? • Is the task performed accurately?

  12. Relationship between Environment and Performance Environment State Change Operator/ Crew State Change Operator / Crew Performance Change

  13. Effect of sleep loss / Time of dayon performance • Sleep loss and time of day affect operator state • State variable is “Mental Alertness” • Mental Alertness affects performance • Different effects for different tasks • Current analysis covers “Vigilance” and “Cognitive” tasks

  14. Alertness Model CircadianEffects (time of day) ‘S’ Effects (time since sleep)

  15. Resultant Alertness

  16. Alertness effectVigilance Misses TG5 WP 1997

  17. CHS Whole body thermal model • Solves diffusion equation for linked cylinders • Represents blood flow inside the body in moderate detail • Handles radiation / evaporation / conduction at surface • Handles active controllers: • Sweating • Shivering • Blood flow modification • Handles sweat evaporation through dry clothing • Coupled to IPME through socket interface

  18. Thermal strain and performance • Preliminary indications • Dehydration affects error rate on cognitive tasks • Dehydration affects physical performance • High temperature speeds performance • Discomfort slows performance • Dehydration slows performance

  19. Nature of states • Candidate examples: • Anxiety • Possibly influences whether the Operator / Crew may or may not participate • Possibly influences nature of Situational Awareness etc. • Motivation • Possibly influences participation / course of action • Alertness / Arousal • Influences performance and errors • Influences decision to act • In extreme case leads to falling asleep

  20. Task demand • Military operations frequently involve high task demand reflected by the need to do more than one thing at once • Classically represented by a “state” – workload • Workload then determines allocation of priorities and performance of the task and / or choice of action • Two models do not involve state • DERA Prediction of Operator Performance (POP) model • Canadian Information Processing / Perceptual Control Theory (IP / PCT) model • Both based on interference effects

  21. Relation between Environment and Performance / behaviour • Original proposed simple model: • Environment toState toPerformance / Behaviour • Incomplete • More complex model needed • Add interference between tasks and its effects • Multiple states have to be considered • Initial evidence is that interaction effects can be ignored

  22. Aims of the presentation • Outline the scope of the problem from a modelling perspective • Sketch a structure in which the problem might be solved • Outline implementation in IPME • Generalise the approach to broader class of architectures • Man as system of systems - possible solutions

  23. System information • Background environment information • Scenario details (Threats) • Conditions (Temperature, Duty pattern etc.) • Team characteristics • Fatigue state • Training etc. • Performance modifiers • Fatigue degaradations etc. • Determined by task taxonomy etc.

  24. Task data required • Time distribution • Probability of failure • Consequences of failure • Who is doing the task • Nature of the task according to the taxonomy • Associated task demand (optional)

  25. Performance shaping model Environment State Operator Trait Operator State Task Execution Feedback (Workload) Operator Performance

  26. Areas covered and under studyunder IPME project • Effects of circadian / sleep loss cycle (CHS alertness model) • Effects of heat / dehydration / discomfort on task performance (Cognitive and physical) • Effects of visual environment on performance • Effects of terrain on movement speed • Effect of task demand (workload) on task performance (POP model) • Alternative model of stressor degradation (interference hypothesis - applied to anxiety)

  27. Aims of the presentation • Outline the scope of the problem from a modelling perspective • Sketch a structure in which the problem might be solved • Outline implementation in IPME • Generalise the approach to broader class of architectures • Man as system of systems - possible solutions

  28. Possible structure Task demand Interference model Cognition / Perception Model Performance / Action Model Crew / Operator States Environment / state Model 1 Environment / state Model 2

  29. Five classes of model identified • Model of cognition / perception • Situational Awareness • Perception of environmental information (Sensory models) • Model of course of action / performance • Decision making (NDM / Rule base / task network) • Model of task interference effects (“Workload”) • Model of influence of state on first two models • Performance degradation • Choice of action modification • Model of influence of environment on state

  30. Environment to state • Models of relationship between environment and state can be complex • Full CHS Alertness model taking account of shift work / time zone shift involves solution of differential equations • Wide range of thermal models with varying degrees of complexity • Interpolation formulae to full systems of differential equations • Different applications demand different levels of detail and complexity • Argues for a modular solution to this component

  31. Task demand • Range of solutions of varying degrees of complexity • Simple compounding models based on task characteristics (VACP) • More complex models handling interference effects (DERA POP) • Yet more complex models handle prioritisation and modifications to courses of action (IP / PCT) • Again the level of complexity dictated by the application arguing for a modular approach

  32. Effects of state • Less well developed topic • Some simple interpolation formulae available for task performance • Some more complex models of impact of state on perception • Few well developed models of effects of state on course of action • Last point important to overall effectiveness • Non-participation / suppression a very important effect

  33. Crew as system of systems • Many highly developed models of aspects of human behaviour • Varying levels of complexity and applicability • Re-use and long term development argues strongly for a modular design with a standard interface between the models • HLA architecture can be applied below the level of the system to the crew

  34. Aims of the presentation • Outline the scope of the problem from a modelling perspective • Sketch a structure in which the problem might be solved • Outline implementation in IPME • Generalise the approach to broader class of architectures • Man as system of systems - possible solutions

  35. Strategic solution • Modular replaceable blocks: • Perceptual engine – take account of state • Cognitive engine – take account of state • Possibly use NDM pattern recogniser and ignore state • State predictors from environment can be simple or complex • Task demand managers can be simple or complex • Re-use of existing models implied

  36. Major issues for future • Definition of modular architecture • Defining set of states which we need to recognise • Defining how state interacts with cognition and perception • Defining relationship between environment and state • Defining relationship between traits and state

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