Evaluating Multi-UAV Operator's Cognitive Workload Using Eye Tracking Data

被引：0

作者：

Gao, Haowen ^{[1
]}

Niu, Jiaxin ^{[1
]}

Wang, Chang ^{[1
]}

Xie, Yijia ^{[1
]}

Niu, Yifeng ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Intelligence Sci & Technol, Changsha 410073, Peoples R China

来源：

PROCEEDINGS OF 2022 INTERNATIONAL CONFERENCE ON AUTONOMOUS UNMANNED SYSTEMS, ICAUS 2022 | 2023年 / 1010卷

关键词：

Eye tracking; Global monitoring; Cognitive workload; Supervisory control;

D O I：

10.1007/978-981-99-0479-2_202

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to solve the problem of crowded task flowoutput in the process of multi-UAV task monitoring, this paper evaluates the cognitive load by analyzing the operator's eye movement data to feedback the task flow status. Based on our previous work, we expand the feature dimension of the eye tracking data, improve the eye tracking classification, and optimize the evaluation of cognitive busy states. Then, we gradually increase the number of UAVs, analyze the characteristics of human operation and their attention distribution in different numbers and operation modes. A cognitive workload assessment method is proposed that takes the task participation time as the main evaluation feature. Finally, we validate the two proposed methods in a word search game.

引用

页码：2167 / 2177

页数：11

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