Automation Technology and Human Performance: Current Research and Trends

By Mark W. Scerbo | Go to book overview

expected trends across the high-low-high task load profile. Thus, the tracking difficulty manipulation was successful in inducing greater levels of mental workload during the early and late phases of the simulation, as they would be during the takeoff and landing phases of actual flight.

Overall performance on all three sub-tasks was significantly higher (p<.01 in each case) in the workload-matched adaptive group than in the other two groups. In addition, subjective workload was significantly lower (p<.05) in this group than in the other groups. The performance benefits of workload- matched adaptation were most marked for the EICAS task. The detection rate of automation failures was significantly (p<.001) higher for the workload-matched adaptive group than for the other two groups. As Figure 3 shows, the performance benefit of ATA-H persisted beyond the period of manual control (middle 20-minute phase) to the last 20-minute phase when the EICAS task was returned to automated control. This result is consistent with the previous findings of Parasuraman et al. ( 1996).

Figure 3. Detection rate of automation failures in the EICAS task for the workload-matched adaptive group, the "clumsy-automation" group, and the nonadaptive control group.

The workload and performance levels of the clumsy-automation adaptive group did not differ significantly from those of the nonadaptive control group. The performance levels for this group were equivalent to or in some cases lower than those of the control group. Figure 3 shows that the monitoring performance benefits of workload-matched adaptation did not accrue to the clumsy-automation group.

These results validate a design approach to adaptive automation involving adaptation matched to operator workload ( Hancock et al., 1985; Parasuraman et al., 1992). Under these conditions, adaptive aiding and adaptive task allocation both enhance performance. The results also show, however, that performance benefits are eliminated if adaptive automation is implemented in a clumsy manner.


REFERENCES

Billings C. E., & Woods D. D. ( 1994). Concerns about adaptive automation in aviation systems. In R. Parasuraman & M. Mouloua (Eds.), Human performance in automated systems: Current researchand trends

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