智能化设计与信息加工通道复杂度对装甲车乘员脑力负荷的影响

doi:10.3969/j.issn.1000-1093.2021.02.002

摘要/Abstract

摘要： 合理的装甲车辆智能化与信息化设计对于降低乘员脑力负荷水平、提高乘员综合作战效能具有重要意义。为探讨智能化设计与信息加工通道复杂度对装甲车乘员脑力负荷的影响，基于某新型装甲车仿真平台，面向装甲车指挥员典型作业任务，选择20名被试人员开展了乘员脑力负荷影响因素综合实验。实验结果显示：高智能化任务相较于低智能化任务具有更低的美国国家航空航天局任务负荷指数量表得分、alpha波段的绝对功率、任务误操作率以及更高的平均扫视峰值速度；视听双通道任务相较于视觉单通道任务具有更高的美国国家航空航天局任务负荷指数量表得分、theta波段的绝对功率和平均瞳孔直径。研究结果表明：高智能化设计条件下乘员的脑力负荷显著低于低智能化设计条件，人机系统的自动化操作与智能人机交互模式可有效降低高信息需求下乘员的工作负荷；视听双通道加工条件下乘员的脑力负荷显著高于视觉单通道加工条件，但使用视听双通道信息加工模式在多任务需求下有利于维持乘员作业绩效；不同生理测量指标对于脑力负荷影响因素具有差异化的敏感性和诊断性。

关键词: 装甲车辆, 乘员, 脑力负荷, 智能化设计, 多通道加工, 人机工效

Abstract: Rational intelligent and information design of armored vehicles is of great significance to reduce the mental workload and improve the effectiveness of armored vehicle occupants. In order to investigate the influences of intelligent design and complexity of information processing modality on occupant mental workload, and based on a new armored vehicle simulation platform, 20 subjects were selected to carry out a comprehensive experiment on the influencing factors of occupant mental workload according to the typical operational task of armored vehicle commander. The test results show that the NASA-TLX rating scale score, alpha band absolute power and task false operation rate under the condition of high-intelligent task are lower than those under the condition of low-intelligent task, and the saccade average peak speed under the condition of high-intelligent task is higher than that under the condition of low-intelligent task; in the audio-visual dual modalities task, higher NASA-TLX rating scale score, theta band absolute power and average pupil diameter are observed compared with the single visual modality task. The occupant mental workload under the condition of high-intelligent design is significantly lower than that under the condition of low-intelligent design, and the automation operation and intelligent human-computer interaction mode can effectively reduce the occupant workload of occupant under the high demand for information. The occupant mental workload under the condition of audio-visual dual modalities task is significantly increased compared with the single visual modality task, while the use of dual audio-visual modalities information processing mode is conducive to ensure a better performance under multi-task demands. In addition, the different physiological measurement indices have distinguished sensitivity and diagnostic ability to the influencing factors of mental workload.

Key words: armoredvehicle, occupant, mentalworkload, intelligentdesign, multi-modalityprocessing, ergonomics

中图分类号:

TJ810.2

郭司南，完颜笑如，刘双，梁超然，陈浩. 智能化设计与信息加工通道复杂度对装甲车乘员脑力负荷的影响[J]. 兵工学报, 2021, 42(2): 234-241.

GUO Sinan， WANYAN Xiaoru， LIU Shuang， LIANG Chaoran， CHEN Hao. Influences of Intelligent Design and Information Processing Modality Complexity on Occupant Mental Workload[J]. Acta Armamentarii, 2021, 42(2): 234-241.

参考文献 27

［1］	傅斌贺, 刘维平, 聂俊峰,等. 考虑认知行为差异的乘员信息作业绩效研究[J]. 兵工学报, 2019, 40(3): 659-665.FU B H, LIU W P, NIE J F, et al. Research on crew's information operation performance with the difference of cognitive behavior[J]. Acta Armamentarii, 2019, 40(3): 659-665.(in Chinese)
[2]	聂俊峰, 刘维平, 傅斌贺,等. 面向装甲车辆乘员信息处理的作业时间预测模型研究[J]. 兵工学报, 2017, 38(2): 233-239.NIE J F, LIU W P, FU B H, et al. Predictive operation time model for information processing task of crew in armored vehicle[J]. Acta Armamentarii, 2017, 38(2): 233-239. ( in Chinese)
[3]	YOUNG M S, BROOKHUIS K A, WICKENS C D, et al. State of science: mental workload in ergonomics[J]. Ergonomics, 2015, 58(1): 1-17.
[4]	WANYAN X R, ZHUANG D M, LIN Y Z, 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.
[5]	RUSNOCK C F, BORGHETTI B J. Workload profiles:a continuous measure of mental workload[J]. International Journal of Industrial Ergonomics, 2018, 63: 49-64.
[6]	JOU Y T, YENN T C, LIN C H J, et al. Evaluation of operators' mental workload of human-system interface automation in the advanced nuclear power plants[J]. Nuclear Engineering and Design, 2009, 239(11): 2537-2542.
[7]	FERRIS T, SARTER N, WICKENS C D. Chapter 15-Cockpit automation: still struggling to catch up…[M]∥Human Factors in Aviation. Pittsburgh,PA, US: Academic Press, 2010: 479-503.
[8]	刘维平, 傅斌贺, 刘西侠,等. 车载显控终端输入方式对乘员信息处理能力影响试验研究[J]. 兵工学报, 2015, 36(11): 2180-2184.LIU W P, FU B H, LIU X X, et al. Experimental study of influences of input modes of vehicle-mounted display and control terminal on crew's information processing capability[J]. Acta Armamentarii, 2015, 36(11): 2180-2184.(in Chinese)
[9]	ALAPETITE A. Speech recognition for the anaesthesia record during crisis scenarios[J]. International Journal of Medical Informa- tics, 2008, 77(7): 448-460.
[10]	MAO M, XIE F, HU J J, et al. Analysis of workload of tank crew under the conditions of informatization[J]. Defence Technology, 2014, 10(1): 17-21.
[11]	刘维平, 聂俊峰, 金毅,等. 基于任务-网络模型的装甲车辆乘员脑力负荷评价方法研究[J]. 兵工学报, 2015, 36(9): 1805-1810.LIU W P, NIE J F, JIN Y, et al. Study on the task division of double-crew armored vehicle based on task network model [J]. Acta Armamentarii, 2015, 36(9): 1805-1810. (in Chinese)
[12]	MOLLOY K, GRIFFITHS T D, CHAIT M, et al. Inattentional deafness: visual load leads to time-specific suppression of auditory evoked responses[J]. Journal of Neuroscience, 2015, 35(49): 16046-16054.
[13]	HART S G, STAVELAND L E. Development of NASA-TLX (task load index): results of empirical and theoretical research[J]. Advances in Psychology, 1988,52: 139-183.
[14]	GAO Q, WANG Y, SONG F, et al. Mental workload measurement for emergency operating procedures in digital nuclear power plants[J]. Ergonomics, 2013, 56(7):1070-1085.
[15]	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.
[16]	冯传宴, 完颜笑如, 刘双,等. 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): 124-133.FENG C Y, WANYAN X R, LIU S, et all. Influence of different attention allocation strategies under workloads on situation awareness[J]. Acta Aeronautica et Astronautica Sinica, 2020,41(3): 124-133. (in Chinese)
[17]	OHTSUKA R, CHIHARA T, YAMANAKA K, et al. Estimation of mental workload during motorcycle operation[J]. Procedia Manufacturing, 2015, 3: 5313-5318.
[18]	AHLSTROM U, FRIEDMAN-BERG F J. Using eye movement activity as a correlate of cognitive workload[J]. International Journal of Industrial Ergonomics, 2006, 36(7): 623-636.
[19]	TSANG P S, VIDULICH M A. Mental workload and situation awareness[M]∥KARWOWSKI W. Handbook of Human Factors and Ergonomics, 3rd ed. Hoboken, NJ, US: John Wiley & Sons Inc., 2006: 243-268.
[20]	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.
[21]	DEL PERCIO C, BABILONI C, BERTOLLO M, et al. Visuo-attentional and sensorimotor alpha rhythms are related to visuo-motor performance in athletes[J]. Human Brain Mapping, 2009, 30(11): 3527-3540.
[22]	DI STASI L L, ANTOL A, CAAS J J. Main sequence: an index for detecting mental workload variation in complex tasks[J]. Applied Ergonomics, 2011, 42(6): 807-813.
[23]	MARQUART G, CABRALL C, DE WINTER J. Review of eye-related measures of drivers' mental workload[J]. Procedia Manufacturing, 2015, 3: 2854-2861.
[24]	RECARTE M A, NUNES L M. Mental workload while driving: effects on visual search, discrimination, and decision making[J]. Journal of Experimental Psychology: Applied, 2003, 9(2): 119-137.
[25]	VAN ACKER B B, BOMBEKE K, DURNEZ W, et al. Mobile pupillometry in manual assembly:a pilot study exploring the wearability and external validity of a renowned mental workload lab measure[J]. International Journal of Industrial Ergonomics, 2020, 75: 102891
[26]	FAIRCLOUGH S H, VENABLES L, TATTERSALL A. The influence of task demand and learning on the psychophysiological response[J]. International Journal of Psychophysiology, 2005, 56(2): 171-184.
[27]	张洁，庞丽萍，完颜笑如，等．基于脑电功率谱密度的作业人员脑力负荷评估方法研究[J]．航空学报, 2020, 41(10): 123618.ZHANG J,PANG L P, WANYAN X R,et al. Research on operator mental workload assessment method based on power spectral density of EEG [J].Acta Aeronautica et Astronautica Sinica, 2020,41(10): 123618. (in Chinese)

[1]	杜志岐，唐镜. 基于系统工程的装甲车辆总体设计[J]. 兵工学报, 2022, 43(S1): 1-10.
[2]	赵祎乾，吴天宇，顾森，李清晨，李亚军. 牵引加榴炮瞄准机手轮尺寸人机工效评估与优化[J]. 兵工学报, 2021, 42(2): 268-280.
[3]	廖自力，疏歆，高强，李嘉麒. 电传动装甲车辆母线电压双通道补偿控制[J]. 兵工学报, 2021, 42(10): 2082-2091.
[4]	刘春光，陈路明，张运银，张征，徐浩轩. 基于改进灰色马尔可夫链的电传动装甲车辆负载需求功率预测[J]. 兵工学报, 2021, 42(10): 2130-2144.
[5]	蔡立春，廖自力，李嘉麒，张运银，王科淯. 8×8分布式电驱动装甲车辆稳定性直接横摆力矩与转矩矢量控制[J]. 兵工学报, 2021, 42(10): 2196-2205.
[6]	刘越，席军强，田真，张欣. 轮式装甲车辆电驱动轮机电耦合动力学建模与振动特性[J]. 兵工学报, 2021, 42(10): 2260-2267.
[7]	傅斌贺，刘西侠，刘维平，张传清，宋海军. 不同任务需求下军用车辆乘员信息作业适宜性评价指标研究[J]. 兵工学报, 2020, 41(2): 239-245.
[8]	王超，汪国胜，李睿，刘青峰，曹宇. 坦克装甲车辆主动悬挂结构技术发展综述[J]. 兵工学报, 2020, 41(12): 2579-2592.
[9]	傅斌贺，刘维平，刘西侠，宋海军. 装甲车辆信息系统人机工效试验平台设计与开发[J]. 兵工学报, 2019, 40(7): 1537-1545.
[10]	骆清国，赵耀，桂勇，刘红彬，帅刚. 基于多种群协同进化免疫多目标优化算法的百叶窗优化研究[J]. 兵工学报, 2019, 40(4): 689-696.
[11]	傅斌贺，刘维平，聂俊峰，刘西侠. 考虑认知行为差异的乘员信息作业绩效研究[J]. 兵工学报, 2019, 40(3): 659-665.
[12]	徐保荣，刘学工，吴延威，胡伟锋. 基于试验结果可信度的装甲车辆测试性综合评估方法研究[J]. 兵工学报, 2018, 39(6): 1066-1073.
[13]	毛明，刘勇，胡建军. 坦克装甲车辆综合电子信息系统的总体设计研究[J]. 兵工学报, 2017, 38(6): 1192-1202.
[14]	刘维平，聂俊峰，刘西侠. 基于多资源理论的乘员信息处理作业认知行为建模研究[J]. 兵工学报, 2017, 38(6): 1215-1222.
[15]	聂俊峰，刘维平，傅斌贺，张征，杨波. 面向装甲车辆乘员信息处理的作业时间预测模型研究[J]. 兵工学报, 2017, 38(2): 233-239.