系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (10): 3473-3484.doi: 10.12305/j.issn.1001-506X.2026.10.19

• 系统工程 • 上一篇    

自动化水平及依赖对多域指挥认知增强的影响

曲昊1,2(), 吴晓莉1,2(), 晏彪1,2(), 张欣悦1,2(), 武愈涵1,2(), 吴传宇1,2(), 欧依琳1,2()   

  1. 1. 南京理工大学人机融合与智能交互研究中心,江苏 南京 210094
    2. 语言信息智能处理及应用工信部重点实验室,江苏 南京 210094
  • 收稿日期:2025-09-24 接受日期:2026-02-11 出版日期:2026-10-25 发布日期:2026-09-30
  • 通讯作者: 吴晓莉 E-mail:quhao_1218@163.com;wuxl@njust.edu.cn;yanbiao0109@163.com;969264885@qq.com;15951975551@163.com;chuanyuw213@163.com;oulihn@163.com
  • 作者简介:曲 昊(2001—),女,硕士研究生,主要研究方向为认知增强
    晏 彪(1996—),男,博士研究生,主要研究方向为人机交互
    张欣悦(2001—),女,硕士研究生,主要研究方向为多模态交互
    武愈涵(2001—),女,硕士研究生,主要研究方向为人机交互
    吴传宇(2002—),男,硕士研究生,主要研究方向为多模态生理测评
    欧依琳(2001—),女,硕士研究生,主要研究方向为人机交互
  • 基金资助:
    江苏省自然科学基金(BK20221490);国家自然科学基金(52175469)资助课题

Impact of automation levels and dependency on cognitive enhancement for multi-domain command

Hao Qu1,2(), Xiaoli Wu1,2(), Biao Yan1,2(), Xinyue Zhang1,2(), Yuhan Wu1,2(), Chuanyu Wu1,2(), Yilin Ou1,2()   

  1. 1. Research Centre of Human Cyber Physical Integration and Intelligent Interaction,Nanjing University of Science and Technology,Nanjing 210094,China
    2. Key Laboratory of Ministry Industry and Information Technology for Language Information Processing and Application,Nanjing 210094,China
  • Received:2025-09-24 Accepted:2026-02-11 Online:2026-10-25 Published:2026-09-30
  • Contact: Xiaoli Wu E-mail:quhao_1218@163.com;wuxl@njust.edu.cn;yanbiao0109@163.com;969264885@qq.com;15951975551@163.com;chuanyuw213@163.com;oulihn@163.com

摘要:

在舰上多域协同作战环境中,自动化水平对指挥员认知表现具有显著影响。针对自动化水平对指挥员认知表现影响机制尚不明确的问题,提出一种基于多源数据融合的认知评估方法。该方法首先构建典型舰上多域指挥任务并设置四级自动化水平,然后采集被试的行为数据、眼动数据与主观负荷评分,最后对不同自动化条件下的认知表现进行综合分析,识别最优配置区间。实验结果显示,低自动化条件下被试认知参与度较高但负荷较重,高自动化条件下任务效率提升但正确率有所下降,并出现一定程度的自动化依赖。结果表明二级自动化在效率与认知增强之间实现较优平衡,为舰上指挥系统人机协同设计提供参考。

关键词: 人机协同, 认知增强, 舰上指挥任务, 自动化水平, 主动思维, 眼动追踪

Abstract:

In shipboard multi-domain collaborative operational environment, the level of automation exerts a significant influence on commanders’ cognitive performance. To address the unclear mechanism by which automation levels influence cognitive performance, this study proposes a cognitive evaluation method based on multi-source data fusion. The method first constructs a typical shipboard multi-domain command task with four levels of automation. Then it collects behavioral data, eye-tracking data, and subjective workload ratings from participants. Finally, it conducts a comprehensive analysis of cognitive performance under different automation conditions to identify the optimal configuration range. Experimental results indicate that lower levels of automation are associated with higher cognitive engagement but heavier workload, whereas higher levels improve task efficiency while reducing accuracy and leading to a certain degree of automation dependency. Overall, Level 2 automation provides an optimal balance between efficiency and cognitive enhancement, offering practical guidance for the human-machine collaboration design of shipboard command systems.

Key words: human-machine collaboration, cognitive enhancement, shipboard command task, level of automation, active thinking, eye tracking

中图分类号: