负荷条件下注意力分配策略对情境意识的影响

doi:10.7527/S1000-6893.2019.23307

流体力学与飞行力学

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

负荷条件下注意力分配策略对情境意识的影响

冯传宴¹, 完颜笑如¹, 刘双¹, 陈浩¹, 庄达民¹, 王鑫²

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 出版日期:2020-03-15 发布日期:2019-08-29
通讯作者: 完颜笑如 E-mail:wanyanxiaoru@buaa.edu.cn
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）

Influence of different attention allocation strategies under workloads on situation awareness

FENG Chuanyan¹, WANYAN Xiaoru¹, LIU Shuang¹, CHEN Hao¹, ZHUANG Damin¹, WANG Xin²

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:2019-07-23 Revised:2019-10-10 Online:2020-03-15 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)

摘要/Abstract

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

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

中图分类号:

V7
R857.1

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.

FENG Chuanyan, WANYAN Xiaoru, LIU Shuang, CHEN Hao, ZHUANG Damin, WANG Xin. Influence of different attention allocation strategies under workloads on situation awareness[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(3): 123307-123307.

参考文献 39

[1]	FENG C Y, WANYAN X R, YANG K, et al. A comprehensive prediction and evaluation method of pilot workload[J]. Technology and Health Care, 2018, 26(S1):S65-S78.
[2]	ENDSLEY M R. A taxonomy of situation awareness errors[J]. Human Factors in Aviation Operations, 1995, 3(2):287-292.
[3]	ENDSLEY M R. Toward a theory of situation awareness in dynamic systems[J]. Human Factors, 1995, 37(1):32-64.
[4]	WICKENS C D, MCCARLEY J S, ALEXANDER A L, et al. Attention-situation awareness (A-SA) model of pilot error:AHFD-04-15/NASA-04-5[R]. Washington, D.C.:NASA Ames Research Center, 2005.
[5]	WEI H Y, ZHUANG D M, WANYAN X R, et al. An experimental analysis of situation awareness for cockpit display interface evaluation based on flight simulation[J]. Chinese Journal of Aeronautics, 2013, 26(4):884-889.
[6]	WANYAN X, ZHUANG D, LIN Y, et al. Influence of mental workload on detecting information varieties revealed by mismatch negativity during flight simulation[J]. International Journal of Industrial Ergonomics, 2018, 64:1-7.
[7]	SALMON P M, LENNÉ M G, YOUNG K L, et al. An on-road network analysis-based approach to studying driver situation awareness at rail level crossings[J]. Accident Analysis & Prevention, 2013, 58:195-205.
[8]	YUAN X, SHE M, LI Z, et al. Mutual awareness:Enhanced by interface design and improving team performance in incident diagnosis under computerized working environment[J]. International Journal of Industrial Ergonomics, 2016, 54:65-72.
[9]	WICKENS C D, ALEXANDER A L. Attentional tunneling and task management in synthetic vision displays[J]. The International Journal of Aviation Psychology, 2009, 19(2):182-199.
[10]	DURANTIN G, GAGNON J F, TREMBLAY S, et al. Using near infrared spectroscopy and heart rate variability to detect mental overload[J]. Behavioural Brain Research, 2014, 259:16-23.
[11]	SEBOK A, WICKENS C D. Implementing lumberjacks and black swans into model-based tools to support human-automation interaction[J]. Human Factors, 2017, 59(2):189-203.
[12]	完颜笑如, 庄达民. 飞行员脑力负荷测量与应用[M]. 北京:科学出版社, 2014:43-44. WANYAN X R, ZHUANG D M. Measurement and application of pilot mental workload[M]. Beijing:Science Press, 2014:43-44 (in Chinese).
[13]	冯传宴, 完颜笑如, 陈浩, 等. 基于多资源负荷理论的情境意识模型与应用[J]. 北京航空航天大学学报,2018,44(7):1438-1446. FENG C Y, WANYAN X R, CHEN H, et al. Situation awareness model based on multi-resource load theory and its application[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(7):1438-1446 (in Chinese).
[14]	VIDULICH M A, TSANG P S. The confluence of situation awareness and mental workload for adaptable human-machine systems[J]. Journal of Cognitive Engineering and Decision Making, 2015, 9(1):95-97.
[15]	HEIKOOP D D, DE WINTER J C F, VAN AREM B, et al. Effects of mental demands on situation awareness during platooning:A driving simulator study[J]. Transportation Research Part F:Traffic Psychology and Behaviour, 2018, 58:193-209.
[16]	LIN L W, LU M S. Empirical research on the relationship between helicopter pilots' mental workloads and situation awareness levels[J]. Journal of the American Helicopter Society, 2016, 61(3):1-8.
[17]	BHAVSAR P, SRINIVASAN B, SRINIVASAN R. Quantifying situation awareness of control room operators using eye-gaze behavior[J]. Computers & Chemical Engineering, 2017, 106:191-201.
[18]	YU C, WANG E M, LI W C, et al. Pilots' visual scan patterns and situation awareness in flight operations[J]. Aviation, Space, and Environmental Medicine, 2014, 85(7):708-714.
[19]	WU X, WANYAN X R, ZHUANG D M. Pilot's visual attention allocation modeling under fatigue[J]. Technology and Health Care, 2015, 23(S2):S373-S381.
[20]	SALMON P M, STANTON N A, WALKER G H, et al. Measuring situation awareness in complex systems:Comparison of measures study[J]. International Journal of Industrial Ergonomics, 2009, 39(3):490-500.
[21]	ENDSLEY M R. Measurement of situation awareness in dynamic systems[J]. Human Factors, 1995, 37(1):65-84.
[22]	VAN DE MERWE K, VAN DIJK H, ZON R. Eye movements as an indicator of situation awareness in a flight simulator experiment[J]. The International Journal of Aviation Psychology, 2012, 22(1):78-95.
[23]	靳慧斌, 刘文辉, 陈健. 塔台管制中最邻近指数注视指数与情境意识的相关性研究[J]. 科学技术与工程, 2016, 16(26):135-139. JIN H B, LIU W H, CHEN J. Correlation research between nni fixation index and situation awareness in tower control[J]. Science Technology & Engineering, 2016, 16(26):135-139 (in Chinese).
[24]	DE WINTER J C F, EISMA Y B, CABRALL C D D, et al. Situation awareness based on eye movements in relation to the task environment[J]. Cognition, Technology & Work, 2019, 21(1):99-111.
[25]	VIDULICH M A, STRATTON M, CRABTREE M, et al. Performance-based and physiological measures of situational awareness[J]. Aviation, Space, and Environmental Medicine, 1994, 65(S5):A7.
[26]	JAP B T, LAL S, FISCHER P, et al. Using EEG spectral components to assess algorithms for detecting fatigue[J]. Expert Systems with Applications, 2009, 36(2):2352-2359.
[27]	ZHAO C, ZHAO M, LIU J, et al. Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator[J]. Accident Analysis & Prevention, 2012, 45:83-90.
[28]	CATHERWOOD D, EDGAR G K, NIKOLLA D, et al. Mapping brain activity during loss of situation awareness:an EEG investigation of a basis for top-down influence on perception[J]. Human factors, 2014, 56(8):1428-1452.
[29]	WICKENS C D, GUTZWILLER R S, VIEANE A, et al. Time sharing between robotics and process control:Validating a model of attention switching[J]. Human Factors, 2016, 58(2):322-343.
[30]	WICKENS C D, GOH J, HELLEBERG J, et al. Attentional models of multitask pilot performance using advanced display technology[J]. Human Factors, 2003, 45(3):360-380.
[31]	MILLER S M, KIRLIK A, KOSORUKOFF A, et al. Ecological validity as a mediator of visual attention allocation in human-machine systems:AHFD-04-17/NASA-04-6[R]. Washington, D.C.:NASA Ames Research Center, 2004.
[32]	曾庆新, 庄达民, 马银香. 脑力负荷与目标辨认[J]. 航空学报, 2007, 28(S1):76-80. ZENG Q X, ZHUANG D M, MA Y X. Mental workload and target identification[J]. Acta Aeronautica et Astronautica Sinica, 2007,28(S1):76-80 (in Chinese).
[33]	WEI Z, ZHUANG D, WANYAN X, et al. A model for discrimination and prediction of mental workload of aircraft cockpit display interface[J]. Chinese Journal of Aeronautics, 2014, 27(5):1070-1077.
[34]	DI NOCERA F, CAMILLI M, TERENZI M. A random glance at the flight deck:Pilots' scanning strategies and the real-time assessment of mental workload[J]. Journal of Cognitive Engineering and Decision Making, 2007, 1(3):271-285.
[35]	LIU S, WANYAN X R, ZHUANG D M. Modeling the situation awareness by the analysis of cognitive process[J]. Bio-medical Materials and Engineering, 2014, 24(6):2311-2318.
[36]	BORGHINI G, ASTOLFI L, VECCHIATO G, et al. Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness[J]. Neuroscience & Biobehavioral Reviews, 2014, 44:58-75.
[37]	GOPHER D, KRAMER A, WIEGMANN D, et al. Emphasis change as a training protocol for high-demand tasks[J]. Attention:From Theory to Practice, 2007, 101:209-224.
[38]	BOOT W R, BASAK C, ERICKSON K I, et al. Transfer of skill engendered by complex task training under conditions of variable priority[J]. Acta Psychologica, 2010, 135(3):349-357.
[39]	WICKENS C D. Situation awareness and workload in aviation[J]. Current Directions in Psychological Science, 2002, 11(4):128-133.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

负荷条件下注意力分配策略对情境意识的影响

Influence of different attention allocation strategies under workloads on situation awareness

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 39

相关文章 7

编辑推荐

Metrics

本文评价

[1]	王崴, 赵敏睿, 高虹霓, 朱帅, 瞿珏. 基于脑电和眼动信号的人机交互意图识别[J]. 航空学报, 2021, 42(2): 324290-324290.
[2]	贺强, 谭德强, 程林. 民机复合材料目视检查中的眼动与疲劳检测[J]. 航空学报, 2020, 41(5): 223532-223532.
[3]	张洁, 庞丽萍, 完颜笑如, 陈浩, 王鑫, 梁晋. 基于脑电功率谱密度的作业人员脑力负荷评估方法[J]. 航空学报, 2020, 41(10): 123618-123618.
[4]	卜建, 刘银鑫, 王艳军. 空中交通管制员的眼动行为与疲劳关系[J]. 航空学报, 2017, 38(S1): 721525-721525.
[5]	曾庆新;庄达民;马银香. 脑力负荷与目标辨认[J]. 航空学报, 2007, 28(增): 76-80.
[6]	刘伟;袁修干;庄达民;柳忠起. 眼动测量系统及其在工效学中的应用[J]. 航空学报, 2001, 22(5): 385-389.
[7]	谢宝生;徐振勇;许华英;刘光远. +G_y作用下跟踪能力的变化[J]. 航空学报, 1989, 10(7): 394-398.