Hocraffer Amy, Nam Chang S
Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC 27695, USA.
Appl Ergon. 2017 Jan;58:66-80. doi: 10.1016/j.apergo.2016.05.011. Epub 2016 Jun 3.
A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm's level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field.
进行了一项荟萃分析,以系统评估用户控制由无人机或无人驾驶飞行器(UAV)组成的半自主集群的人机系统界面的当前研究状况。无人机集群带来了若干人为因素挑战,例如高认知需求、非直观行为以及错误的严重后果。本文介绍了对27篇专注于人机系统界面和人为因素问题的无人机集群管理论文进行荟萃分析的结果,概述了当前无人机管理界面的优势、挑战和局限性,以及这些界面当前的评估方式。总体而言,允许针对用户界面进行特定用户和任务的定制,并提高集群的自主水平以减轻操作员的认知工作量,是有益的,并且可以提高态势感知(SA)。显然,在这个快速发展的领域中还需要更多的研究。