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Abstract

Objective:

We attempted to understand the latent structure underlying the systems pilots use to operate in situations involving human-automation interaction (HAI).

Background:

HAI is an important characteristic of many modern work situations. Of course, the cognitive subsystems are not immediately apparent by observing a functioning system, but correlations between variables may reveal important relations.

Method:

The current report examined pilot judgments of 11 HAI dimensions (e.g., Workload, Task Management, Stress/Nervousness, Monitoring Automation, and Cross-Checking Automation) across 48 scenarios that required airline pilots to interact with automation on the flight deck.

Results:

We found three major clusters of the dimensions identifying subsystems on the flight deck: a workload subsystem, a management subsystem, and an awareness subsystem.

Discussion:

Relationships characterized by simple correlations cohered in ways that suggested underlying subsystems consistent with those that had previously been theorized.

Application:

Understanding the relationship among dimensions affecting HAI is an important aspect in determining how a new piece of automation designed to affect one dimension will affect other dimensions as well.

Keywords

automation aviation and aerospace pilot decision making human-automation interaction expert systems cognitive structure cognition knowledge elicitation/acquisition methods and skills

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Exploring Relationships of Human-Automation Interaction Consequences on Pilots

Abstract

Objective:

Background:

Method:

Results:

Discussion:

Application:

Keywords

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References