Massachusetts Institute of Technology, Humans and Automation Laboratory, 77 Massachusetts Ave., Room 33-407, Cambridge, MA 02139, USA.
Hum Factors. 2009 Oct;51(5):718-29. doi: 10.1177/0018720809347106.
This article is an investigation of the effectiveness of sonifications, which are continuous auditory alerts mapped to the state of a monitored task, in supporting unmanned aerial vehicle (UAV) supervisory control.
UAV supervisory control requires monitoring a UAV across multiple tasks (e.g., course maintenance) via a predominantly visual display, which currently is supported with discrete auditory alerts. Sonification has been shown to enhance monitoring performance in domains such as anesthesiology by allowing an operator to immediately determine an entity's (e.g., patient) current and projected states, and is a promising alternative to discrete alerts in UAV control. However, minimal research compares sonification to discrete alerts, and no research assesses the effectiveness of sonification for monitoring multiple entities (e.g., multiple UAVs).
The authors conducted an experiment with 39 military personnel, using a simulated setup. Participants controlled single and multiple UAVs and received sonifications or discrete alerts based on UAV course deviations and late target arrivals.
Regardless of the number of UAVs supervised, the course deviation sonification resulted in reactions to course deviations that were 1.9 s faster, a 19% enhancement, compared with discrete alerts. However, course deviation sonifications interfered with the effectiveness of discrete late arrival alerts in general and with operator responses to late arrivals when supervising multiple vehicles.
Sonifications can outperform discrete alerts when designed to aid operators to predict future states of monitored tasks. However, sonifications may mask other auditory alerts and interfere with other monitoring tasks that require divided attention.
This research has implications for supervisory control display design.
本文旨在研究声信号，即映射到被监测任务状态的连续听觉警报，在支持无人机（UAV）监控方面的有效性。
UAV 监控需要通过主要的视觉显示器监控多个任务（例如，航线维护），目前通过离散的听觉警报来支持。声信号已被证明通过允许操作员立即确定实体（例如，患者）的当前和预计状态，从而提高了监测性能，在麻醉学等领域是离散警报的一种有前途的替代方案。然而，很少有研究将声信号与离散警报进行比较，也没有研究评估声信号在监测多个实体（例如，多架 UAV）方面的有效性。
作者进行了一项涉及 39 名军事人员的实验，使用模拟设置。参与者控制单架和多架 UAV，并根据 UAV 航线偏差和目标延迟到达接收声信号或离散警报。
无论监控的 UAV 数量如何，与离散警报相比，航线偏差声信号导致对航线偏差的反应快 1.9 秒，增强了 19%。然而，航线偏差声信号通常会干扰离散的延迟到达警报的有效性，并干扰操作员对多架车辆的延迟到达的响应。
当设计用于帮助操作员预测被监测任务的未来状态时，声信号可以优于离散警报。然而，声信号可能会掩盖其他听觉警报，并干扰需要注意力分散的其他监测任务。
本研究对监控控制显示设计具有重要意义。
