Tencent Technology, Shanghai, China.
University of Michigan, Ann Arbor, MI, USA.
Hum Factors. 2024 Jan;66(1):234-257. doi: 10.1177/00187208211063991. Epub 2022 Jan 10.
The aim of this study was to establish the effects of simultaneous and asynchronous masking on the detection and identification of visual and auditory alarms in close temporal proximity.
In complex and highly coupled systems, malfunctions can trigger numerous alarms within a short period of time. During such alarm floods, operators may fail to detect and identify alarms due to asynchronous and simultaneous masking. To date, the effects of masking on detection and identification have been studied almost exclusively for two alarms during single-task performance. This research examines 1) how masking affects alarm detection and identification in multitask environments and 2) whether those effects increase as a function of the number of alarms.
Two experiments were conducted using a simulation of a drone-based package delivery service. Participants were required to ensure package delivery and respond to visual and auditory alarms associated with eight drones. The alarms were presented at various stimulus onset asynchronies (SOAs). The dependent measures included alarm detection rate, identification accuracy, and response time.
Masking was observed intramodally and cross-modally for visual and auditory alarms. The SOAs at which asynchronous masking occurred were longer than reported in basic research on masking. The effects of asynchronous and, even more so, simultaneous masking became stronger as the number of alarms increased.
Masking can lead to breakdowns in the detection and identification of alarms in close temporal proximity in complex data-rich domains.
The findings from this research provide guidance for the design of alarm systems.
本研究旨在确定在时间接近的情况下，同时和异步掩蔽对视觉和听觉警报的检测和识别的影响。
在复杂且高度耦合的系统中，故障可能会在短时间内引发大量警报。在这种警报泛滥的情况下，由于异步和同时掩蔽，操作人员可能无法检测和识别警报。迄今为止，掩蔽对检测和识别的影响几乎仅在单任务性能下对两个警报进行了研究。本研究考察了 1）掩蔽如何在多任务环境中影响警报检测和识别，2）随着警报数量的增加，这些影响是否会增加。
使用基于无人机的包裹投递服务的模拟进行了两项实验。要求参与者确保包裹投递并响应与八架无人机相关的视觉和听觉警报。警报以各种刺激呈现时间间隔（SOA）呈现。因变量包括警报检测率、识别准确率和响应时间。
在视觉和听觉警报中观察到了同模态和跨模态掩蔽。异步掩蔽发生的 SOA 比掩蔽基本研究中报告的要长。随着警报数量的增加，异步掩蔽的影响，甚至更明显的是同时掩蔽的影响变得更强。
在复杂的数据密集型领域中，掩蔽可能导致时间接近的警报的检测和识别失败。
本研究的结果为警报系统的设计提供了指导。
