Dixon Stephen R, Wickens Christopher D, Chang Dervon
University of Illinois, Institute of Aviation, Aviation Human Factors Division, Savoy 61874, USA.
Hum Factors. 2005 Fall;47(3):479-87. doi: 10.1518/001872005774860005.
With unmanned aerial vehicles (UAVs), 36 licensed pilots flew both single-UAV and dual-UAV simulated military missions. Pilots were required to navigate each UAV through a series of mission legs in one of the following three conditions: a baseline condition, an auditory autoalert condition, and an autopilot condition. Pilots were responsible for (a) mission completion, (b) target search, and (c) systems monitoring. Results revealed that both the autoalert and the autopilot automation improved overall performance by reducing task interference and alleviating workload. The autoalert system benefited performance both in the automated task and mission completion task, whereas the autopilot system benefited performance in the automated task, the mission completion task, and the target search task. Practical implications for the study include the suggestion that reliable automation can help alleviate task interference and reduce workload, thereby allowing pilots to better handle concurrent tasks during single- and multiple-UAV flight control.
36名有执照的飞行员驾驶无人驾驶飞机（UAV）执行单架无人机和双架无人机模拟军事任务。飞行员需要在以下三种条件之一的一系列任务航段中操控每架无人机：基线条件、听觉自动警报条件和自动驾驶条件。飞行员负责（a）任务完成、（b）目标搜索和（c）系统监控。结果显示，自动警报和自动驾驶自动化都通过减少任务干扰和减轻工作量提高了整体性能。自动警报系统在自动化任务和任务完成任务中都有利于提高性能，而自动驾驶系统在自动化任务、任务完成任务和目标搜索任务中都有利于提高性能。该研究的实际意义包括这样的建议，即可靠的自动化有助于减轻任务干扰和减少工作量，从而使飞行员在单架和多架无人机飞行控制期间能够更好地处理并发任务。
