负荷条件下注意力分配策略对情境意识的影响

冯传宴; 完颜笑如; 刘双; 陈浩; 庄达民; 王鑫

doi:10.7527/S1000-6893.2019.23307

航空学报 >

2020 , Vol. 41 >Issue 3: 123307 - 123307

DOI: https://doi.org/10.7527/S1000-6893.2019.23307

流体力学与飞行力学

负荷条件下注意力分配策略对情境意识的影响

冯传宴 ,
完颜笑如 ,
刘双 ,
陈浩 ,
庄达民 ,
王鑫

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1. 北京航空航天大学航空科学与工程学院, 北京 100083;
2. 中国船舶工业综合技术经济研究院舰船人因工程实验室, 北京 100081

收稿日期: 2019-07-23

修回日期: 2019-10-10

网络出版日期: 2019-08-29

基金资助

国家自然科学基金委员会与中国民用航空局联合基金（U1733118）；航空科学基金（201813300002）；国家自然科学基金（71301005）

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Influence of different attention allocation strategies under workloads on situation awareness

FENG Chuanyan ,
WANYAN Xiaoru ,
LIU Shuang ,
CHEN Hao ,
ZHUANG Damin ,
WANG Xin

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1. School of Aeronautic Science and Engineering, Beihang University, Beijing 100083, China;
2. Marine Human Factors Engineering Lab, China Institute of Marine Technology & Economy, Beijing 100081, China

Received date: 2019-07-23

Revised date: 2019-10-10

Online published: 2019-08-29

Supported by

Jointly Program of National Natural Science Foundation of China and Civil Aviation Administration of China (U1733118);Aeronautical Science Foundation of China (201813300002);National Natural Science Foundation of China (71301005)

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摘要

为探究负荷条件下不同注意力分配策略对情境意识（SA）的影响，招募22名被试开展了3种注意力分配策略（平均分配、主次分配、多级分配）×2种脑力负荷（低负荷、高负荷）条件下的被试内双因素设计的实验任务，记录情境意识全面测量技术（SAGAT）、行为绩效、眼动和脑电（EEG）指标为因变量。实验结果表明，在不同脑力负荷下，相较于多级注意力分配策略和主次注意力分配策略，平均注意力分配策略的SAGAT得分和绩效正确率均更低、最小近邻指数（NNI）更大；在高脑力负荷下，相较于多级注意力分配策略，主次注意力分配策略的SAGAT得分更高、绩效反应时间更短并且NNI值更低；SAGAT得分与平均注视时间、NNI、θ相对功率和α相对功率均存在显著低度相关。本研究结果提示，在不同脑力负荷条件下，采用平均注意力分配策略可能导致作业人员的注意力更为分散，从而产生更差的工作绩效和更低的SA水平；而在高脑力负荷条件下，相比于多级注意力分配策略，主次注意力分配策略更有助于作业人员提取关键信息并维持更好的SA水平，但同时可能存在SA丧失的风险；眼动的平均注视时间和NNI指标以及EEG的θ和α相对功率指标具有较好的表征SA的潜力。

关键词： 情境意识; 注意力分配; 脑力负荷; SAGAT; 眼动; 脑电

本文引用格式

冯传宴 , 完颜笑如 , 刘双 , 陈浩 , 庄达民 , 王鑫 . 负荷条件下注意力分配策略对情境意识的影响[J]. 航空学报, 2020 , 41(3) : 123307 -123307 . DOI: 10.7527/S1000-6893.2019.23307

Abstract

The aim of this study is to examine the influence of different attention allocation strategies under workloads on Situation Awareness (SA). 22 participants are recruited to conduct the 3 attention allocation strategies (equal allocation, primary and secondary allocation, and multilevel allocation)×2 mental workloads (low workload and high workload) two-factor within-subject design tasks. Dependent variables include Situational Awareness Global Assessment Technology (SAGAT), performance measures, eye movement measures, and electroencephalograph (EEG) measures. Statistical results show that under different workloads, compared with the primary and secondary allocation and the multilevel allocation, the equal allocation has significantly lower SAGAT scores, lower accuracy of performance, and higher Nearest Neighbor Index (NNI). Under high workload, compared with the multilevel allocation, the primary and secondary allocation has significantly higher SAGAT scores, shorter response time of performance, and lower NNI. Third, the SAGAT score has lower correlations to mean fixation time, NNI, θ relative power, and α relative power. The above outcomes could draw three conclusions. First of all, under different workloads, the equal attention allocation strategy may result in dispersed attention of the operator, which will then induce a worse performance and lower SA. What’s more, under high workload, compared to the multilevel attention allocation strategy, the primary and secondary attention allocation strategy is beneficial for the operator to extract key information and to maintain a better SA, but remain the risk of loss of SA. Finally, the mean fixation time and the NNI of eye movement, as well as the θ and α of EEG measures have potentials to measure SA.

Key words： situation awareness; attention allocation; mental workload; SAGAT; eye movement; electroencephalograph

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