Automation Technology and Human Performance: Current Research and Trends

By Mark W. Scerbo | Go to book overview
humans are more efficient. For severe problems, SAA is more effective in managing fluid loss during faults, whether or not the displayed information is reliable.

The experiment has also shown the need for autonomy which comes between levels 6 and 7 (say, level 6.5) in Table 1. Level 6.5 autonomy is defined as: "The computer executes automatically after telling human what it will do. No veto is allowed for the human." This type of autonomy may be effective to avoid automation surprises ( Sarter & Woods, 1995; Wickens, 1994) induced by safety-related actions by automation under high time-criticality.


CONCLUSION

This paper has shown, through a mathematical analysis and an experiment, how authority can be traded between human and automation in a situation-adaptive manner. The situation-adaptive autonomy is closely related to the adaptive automation: See ( Scerbo, 1996) for a survey. We need further research for validation of those concepts, because effectiveness may be dependent on task context.


ACKNOWLEDGEMENTS

This work has been done jointly with Neville Moray of the University of Surrey and Makoto ltoh of the University of Tsukuba. This work has been supported by the Center for TARA (Tsukuba Advanced Research Alliance) at the University of Tsukuba, Grants-in-Aid 08650458 and 09650437 of the Japanese Ministry of Education, and the First Toyota High-Tech Research Grant Program.


REFERENCES

Billings C. E. ( 1991). Human-Centered Aircraft Automation. NASA TM-103885.

Inagaki T. & Johannsen G. ( 1991). Human-computer interaction and cooperation for supervisory control of large- complex systems. In Pichler & Moreno Diaz (Eds.), Computer Aided System Theory, LNCS 585, Springer- Verlag, 281-294.

Inagaki T. ( 1993). Situation-adaptive degree of automation for system safety. Proc. 2nd IEEE Int. Workshop on Robot and Human Communication, 231-236.

Inagaki T. ( 1995). Situation-adaptive responsibility allocation for human-centered automation. Trans. SICK of Japan, 31( 3), 292-298.

Inagaki T. ( 1997a). To go or not to go: Decision under time criticality and situation-adaptive autonomy for takeoff safety, Proc. IASTED Int. Conf. Appl. Modeling & Simul, 144-147.

Inagaki T. & Itoh M. ( 1997b) Situation-adaptive autonomy: The potential for improving takeoff safety, Proc. 6th IEEE Int. Workshop on Robot and Human Communication, 302-307.

Inagaki T., Moray N., & Itoh M. ( 1997) Trust and time-criticality: Their effects on the situation-adaptive autonomy, Proc. Int. Symp. AIR-IHAS, 93-103.

Lee J. & N. Moray ( 1992). Trust, control strategies and allocation of function in human-machine systems. Ergonomics, 35( 10), 1243-1270.

Sarter N. & Woods D. D. ( 1995). Autonomy, authority, and observability: Properties of advanced automation and their impact on human-machine coordination, Proc. IFAC MMS, 149-152.

Scerbo M. W. ( 1996). Theoretical perspectives on adaptive automation. In R. Parasuraman & M. Mouloua (Eds.), Automation and human performance: Theory and applications (pp. 37-63). Mahwah, NJ: Erlbaum.

Sheridan T. ( 1992). Telerobotics, automation, and human supervisory control. MIT Press.

Wickens C. D. ( 1994). Designing for situation awareness and trust in automation. Proc. IFAC Integrated Systems Engineering, 77-82.

Woods D. ( 1989). The effects of automation on human's role: Experience from non-aviation industries. In Norman and Orlady (Eds.), Flight Deck Automation: Promises and Realities. NASA CP- 10036, 61 -85.

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