Department of Psychology, University of Cincinnati, 5140H Edwards Hall 1, Cincinnati, OH 45221, USA.
Behav Res Methods. 2011 Sep;43(3):771-80. doi: 10.3758/s13428-011-0085-9.
Use of unmanned aerial vehicles (UAVs) is an increasingly important element of military missions. However, controlling UAVs may impose high stress and workload on the operator. This study evaluated the use of the RoboFlag simulated environment as a means for profiling multiple dimensions of stress and workload response to a task requiring control of multiple vehicles (robots). It tested the effects of two workload manipulations, environmental uncertainty (i.e., UAV's visual view area) and maneuverability, in 64 participants. The findings confirmed that the task produced substantial workload and elevated distress. Dissociations between the stress and performance effects of the manipulations confirmed the utility of a multivariate approach to assessment. Contrary to expectations, distress and some aspects of workload were highest in the low-uncertainty condition, suggesting that overload of information may be an issue for UAV interface designers. The strengths and limitations of RoboFlag as a methodology for investigating stress and workload responses are discussed.
使用无人机(UAV)是军事任务中越来越重要的元素。然而,控制无人机可能会给操作员带来高压力和高工作量。本研究评估了 RoboFlag 模拟环境作为一种方法的有效性,该方法用于分析需要控制多架飞机(机器人)的任务中压力和工作量反应的多个维度。它在 64 名参与者中测试了两种工作量操作的效果,即环境不确定性(即 UAV 的可视视野)和机动性。研究结果证实,该任务产生了大量的工作量和高度的不适。这些操作的压力和绩效效果之间的分离证实了采用多元方法进行评估的有效性。与预期相反,在低不确定性条件下,不适和一些工作量方面的指标最高,这表明信息过载可能是 UAV 界面设计师需要关注的问题。讨论了 RoboFlag 作为一种研究压力和工作量反应的方法的优缺点。