Pilot Dependence on Imperfect Diagnostic Automation in Simulated UAV Flights: An Attentional Visual Scanning Analysis.
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TL;DR
An unmanned air vehicle (UAV) simulation was designed to reveal the effects of imperfectly reliable diagnostic automation a monitor of system health parameters on pilot attention, as the latter was assessed via visual scanning.
Abstract
An unmanned air vehicle (UAV) simulation was designed to reveal the effects of imperfectly reliable diagnostic automation – a monitor of system health parameters – on pilot attention, as the latter was assessed via visual scanning. Four groups of participants flew a series of legs under different automation conditions: a baseline (no automation) control, and automation which was either 100% reliable, 60% reliable with a low-threshold bias to produce false alerts, and 60% reliable with a high threshold to produce misses. A high workload mission completion task and ground surveillance task were simultaneously imposed. Consistent with the reliance-compliance model of imperfect automation developed by Meyer (2001), miss-prone automation removed visual attention from the surveillance task, while FA-prone automation delayed the alert-driven attention shift to the system monitoring task.