A Case for Theory-Based Research on Level of Automation and Adaptive Automation

1. A Case for Theory-Based Research on Level of Automation and Adaptive Automation David B. Kaber Department of Industrial Engineering North Carolina State University This work was supported by a grant through the National Aeronautics and Space Administration Langley Research Center. The opinions expressed are those of the author and do not necessarily reflect the views of NASA.

2. Thoughts on the “what”, “how” and “when” of automation: “How?” Level of Automation (LOA) Machine Human/Machine Human “When?” T0 Tn Monitoring Adaptive Automation (AA) Generating Selecting Implementing Stages of Information Processing “What?” Adapted from Endsley (1997).

3. Information Processing and Automation Design Theory: • Qualitative models relating stages of information processing to automation design. • Parasuraman et al. (2000) – Model of types and levels of automation. Information Acquisition Information Analysis Decision-making Action High High High High Degree of Automation Low Low Low Low A model of types and levels of automation (from Parasuraman et al. (2000)).

4. Qualitative Models of Human-Automation Interaction (cont.): • Endsley & Kaber (1999): • Four-stage model of information processing. • Used to define levels of automation or function allocation schemes. Monitoring Generating Selecting Implementing Human Human/Machine Machine Human Human/Machine Machine Human Human/Machine Machine Human Human/Machine Machine Level of Automation Adapted from Endsley and Kaber’s (1999) taxonomy of levels of automation.

5. Taxonomy of Levels of Automation: • Endsley & Kaber (1999): • 10 discrete levels of automation (LOAs) in complex systems control.

6. Bases for Qualitative Models: • Common models of HUMAN information processing (HIP). • Sanders & McCormick (1993) – Multi-stage model identifying functions of humans and machines. Automaticity Sensing - Perception Information Processing Decision-making Action Functions Feedback Adapted from Sanders and McCormick’s (1993) model of human and machine functions in human-machine systems.

7. Another Basis for Current Models: • Wickens (1992) – Model of HIP influential in Parasuraman et al. (2000) model of types and LOAs. Short-term Sensory Store Perception Decision-making Response Execution Long-term Memory Working Memory Feedback Model of human information processing (adapted from Wickens (1992)).

8. Applying Information Processing Models to Automation Design: • Parasuraman et al. (2000) and Endsley & Kaber (1999) models: • Present ways of classifying functions of human-machine systems. Mission Analysis Function Analysis Task Analysis Basic System Concept Initial Function Allocation Dynamic Function Allocation Determine “how” to automate? Determine “what” to automate? Determine “when” to automate? Note: Entire process is similar to Wickens (1992) approach to systems design.

9. Link LOAs to stages of information processing. Types of functions considered are general information processing functions. Compare with Sheridan & Verplank’s (1978) hierarchy of LOAs – Functions primarily represent action states (“gets”, “starts”, etc.) or choice reactions (“selects”). Historical function allocation lists technology-centered (Fitts, 1956): Advances in understanding of out-of-the (control) loop performance (Endsley & Kiris, 1995; Kaber et al., 1998) shifted focus of lists on human abilities. Contemporary taxonomies of LOA (e.g., Endsley & Kaber (1999)) developed by considering performance consequences of automation Complacency, vigilance decrements, loss of SA, skill decay. Unique Aspects of Approach:

10. Importance of Research: • Link general theories on information processing and automation to applications. • Parasuraman et al. (2000) - Application of model to air traffic control (ATC). • Contemporary models of human-automation interaction (HAI) may serve as design rationale for human-centered automation. • Knowledge of performance with systems can be classified according to model and used to further develop general theory on HAI. • Theory may serve to answer several questions: • What stages of information processing are conducive to automation from human perspective? • To what extent can stage be automated safely/effectively? • What stages are robust to automation reliability problems?

11. Theoretical Research Challenges: • Validate processing stages of models in terms of representation of actual functions performed by human-machine systems. • Models can be used for logical function allocation, but practical implications are difficult to predict. • Endsley & Kaber (1999): • Intermediate LOAs moderate workload, maintain situation awareness (SA) and improve performance. • Low level automation produced superior performance, but at cost of SA. • “Good” SA observed under high LOAs. Hypothesis Results

12. Example Model Application: • Applied Endsley & Kaber’s taxonomy of LOAs to advanced commercial aircraft (MD-11) (Tan et al., 2000): • Conducted complex systems analysis. • Developed high-fidelity simulation for evaluation of existing system automation. • Categorized actual modes of automation according to taxonomy.

13. Flight Simulator Displays: Flight Control Panel (FCP) Flight Mode Annunciator (FMA) Out-of-Cockpit View Throttle/attitude control Primary Flight Display (PFD) Navigation Display (ND) Multi-functional Control Display Unit (MCDU)

14. Defining Aircraft Automation in Terms of Taxonomy of LOA: • Taxonomy and example LOA description:

15. Research to Enhance Basic Understanding of Automation: Study AA in high-fidelity simulations, or in context. 1 • Adaptive automation (AA) (or “when” to automate) primarily studied using laboratory simulations of complex systems. • Majority of AA research investigates concept from binary perspective. • Automation is continuous variable made discrete for research purposes. Study AA by considering many points along continuum of automation. 2 Decision Support Full Automation Binary Approach Continuous Approach Supervisory Control Supervisory Control Action Support Automation Manual Control Decision Support “When?” Batch Processing Manual Control T0 Tn

16. Considering Models of HAI in Adaptive Systems Research: Study impact of AA on latter stages of information processing. 3 • Focus of AA research has been on early stages of information processing: • Do not have understanding of effect of AA on decision-making and planning. • People may not adapt well to dynamic allocations of decision functions. • Research has not systematically examined performance and SA effects of dynamic function allocations (DFAs) across stages of information processing. Parasuraman et al. (1993) Study SA and performance effects of AA across functions represented in models of HAI. 4 Study impact of AA applied exclusively to each stage of information processing. 5

17. Final Issues: • Need to determine who (human or automation) should have authority over DFAs: • Computer authority shown to reduce excessive cyclings between control modes (Hilburn et al., 1993). • Automation directed DFAs improve human manual control – operator does not need to evaluate who should be doing what (Kaber & Riley, 1999). • Approach AA research cautiously - complexity of system design may cause mode awareness problems (Sarter & Woods, 1995). Compare voluntary, involuntary and shared DFA management 6 Consider need to keep-track of LOAs in AA studies. 7

18. Conclusions: • Can’t study AA without considering LOA – concepts “like peas and carrots” (F. Gump). • Taxonomies of LOA provide means for systematically studying complexities of automation. • Need to apply models of HAI to real systems to expand theory to design rationales. • Classify systems and understand underlying factors in automated system performance. • Need to develop framework of AA research.