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16.422 Human Supervisory Control of Automated Systems

Prof. R. John Hansman

Prof. Missy Cummings

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Course Objectives

This is a graduate student class designed to examine the fundamental issues of human supervisory control, wherein humans interact with complex dynamic systems, mediated through various levels of automation. This course will explore how humans interact with automated systems of varying complexities, what decision processes can be encountered in complex man-machine systems, and how automated systems can be designed to support both human strengths and weaknesses. Several case studies will be presented from a variety of domains as illustrations. A secondary objective of this class is to provide an opportunity to improve both oral and written presentation skills.

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Evolution of Cockpit Displays

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Types of Automation

Mechanical Automation (eg Factory > Industrial Revolution)

Mixed ; Information and Mechanical (eg Aircraft)Decision AidSupervisory Control

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Verplank Notions

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Supervisory Control Architecture

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Supervisory Control Examples

Autopilot - Flight Management System

Autonomous Vehicle

Process Control Plant

Thermostat

Word Processing Program

Cruise Control

Automated Steering??

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Sheridan NotionsSpectrum of Automation

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Models

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Tele-Systems

Operator

HumanInteractiveComputer/Interface

Comm Comm

Distance

TaskInteractiveComputer/Autopilot

Aircraft

Bandwidth

Loss of Direct FeedbackCommunications Latency

Task Interactive Computer - Human Interactive Computer

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Tele-System Examples

Autonomous VehicleAircraft, AAV, RPVRover - Mars, BombUnderwater UUV, AUV

Web System

Virtual Presence

Tele-medicine

Other

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Decision Aid Architecture

DisplayDecision Aiding

Logic -Computer

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Decision Aid Examples

Alerting SystemsGear WarningIdiot Light (eg Oil Pressure)TCAS

Automated Planning SystemsPath Planners

SuggestersSpell Check

“What if” ToolsAnalysis Tools

Data AnalysisFiltersInteractive Data Analysis Tools

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Question

What is good design practice for development of human supervisory and decision aiding systems

Distribution of AuthorityArchitectureIntuitiveness of SystemInterface IssuesUsabilityPerformance robustnessSafety Cost Benefit

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Spectrum of Automation

Manual Fully AutonomousManual

Historically - Human required to compensate for limitations of system

Skilled OperatorsTraining

Human limits >>> System Limits

Distribution of Authority (Human vs Automation)

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Humans

StrengthsPattern RecognitionInferenceData AssimilationAdaptationIntuitionJudgmentIntuitionMorality

LimitsLatency - Response timeBandwidthData Input

VisualAudioTactical

Cognitive CapacityInconsistent PerformanceBoredom - SaturationEnduranceLife SupportCostTraining

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Automation

StrengthsCan be fastDoes not get boredConsistentGood for predictable cases

LimitsDumbNeeds rulesAdaptabilityCostInput requirementsInterface with system

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Why Automate ?Enhance Human

Extend, Relieve, Backup Replace

PerformanceSpeed, Accuracy, Strength

Cost2 person crew

Reliability/Repeatability

Hazards to OperatorsUCAV

Human LimitationsG levels, Life Support

Market Perception

Distributed GeographyTelepresece, Web

SafetyTrue?

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Does Automation Increase Safety?

Confounded with other EffectsSystem Improvements

Changes Error ModesAutomation Errors (eg A320)

Workload DistributionCruise decreased, approach increased

System FailureOver-reliance/Dependence on Automation

Complexity Induced Issues

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VLS

Vα Prot

Vα Max

Vα Floor

140

120

CLAirspeed scalescale

α Angle of Attack (AOA)

α Stall: Sudden loss of lift and or aircraft control

Angle of attack reached with full aft stick (max aircraft performance) Angle of attack, where TOGA thrust isautomatically applied by the A/THRAngle of attack from which stick input is converted into angle of attack demand (stick neutral α Prot)

α VLS: Angle of attack reached at approach speed (VLS)

α Max:

α Prot:

α Floor:

High Angle of Attack Protection

CL

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A320 Thrust Control

Thrust levers• Moved manually (no servomotor)• Transmit their position to the respective FADEC (Full Authority Digital Engine Control)