基于多资源负荷理论的情境意识模型与应用

冯传宴; 完颜笑如; 陈浩; 庄达民

doi:10.13700/j.bh.1001-5965.2017.0532

基于多资源负荷理论的情境意识模型与应用

doi: 10.13700/j.bh.1001-5965.2017.0532

北京航空航天大学航空科学与工程学院, 北京 100083

基金项目:

国家自然科学基金委员会与中国民用航空局联合资助项目 U1733118

国家自然科学基金 71301005

详细信息

作者简介:
冯传宴  男, 博士研究生。主要研究方向:情境意识、脑力负荷、驾驶舱人机工效

完颜笑如  女, 博士, 讲师, 硕士生导师。主要研究方向:航空人机工效与认知工程、人机工效

陈浩  男, 硕士研究生。主要研究方向:驾驶舱人机工效

庄达民  男, 博士, 教授, 博士生导师。主要研究方向:航空人机工效与认知工程、人机工效

通讯作者:
完颜笑如.E-mail:wanyanxiaoru@buaa.edu.cn

中图分类号: R857.1
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- 被引次数: 0
出版历程
- 收稿日期: 2017-08-21
- 录用日期: 2017-11-19
- 网络出版日期: 2018-07-20

Situation awareness model based on multi-resource load theory and its application

School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

Funds:

National Natural Science Foundation of China and Civil Aviation Administration of China Jointly Funded Project U1733118

National Natural Science Foundation of China 71301005

More Information

Corresponding author: WANYAN Xiaoru.E-mail:wanyanxiaoru@buaa.edu.cn

摘要

摘要:
结合多资源负荷理论及信息认知加工理论，在注意-情境意识(A-SA)模型和注意资源分配SA模型基础上，提出了一种新的SA量化模型。该模型中，多资源负荷作用于低层次的注意感知，初期认知资源衰减结合情境激活后内在的高层次规则可用性匹配，最终输出为个体的SA水平。为验证模型可用性，采用15名被试在不同情境下开展飞行任务模拟，并结合主观的十维度情境意识测评技术(10-D SART)和客观的飞行绩效、情境意识全面测量技术(SAGAT)以及生理测量(心电、皮电及呼吸)进行实验测评。实验分析表明，模型计算的理论值变化趋势与实验结果显著相关，提出的SA量化模型对于指导驾驶舱人机界面设计和优化飞行任务分配具有一定的参考价值。
- 情境意识(SA) /
- 多资源负荷 /
- 认知建模 /
- 脑力负荷 /
- 界面设计 /
- 人机工效
Abstract:
Based on the attention-situation awareness (A-SA) model and the attention resource allocation situation awareness model, a new quantitative model of situation awareness was put forward, which considers the multi-resource load and information recognition theory. In this model, the multi-resource load was applied to the low-level attention perception. The individual's situational awareness was composed of the damping of initial cognitive resource and the inherent deep-level rule availability matching after the activation of situation. In order to verify the usability of the model, 15 subjects were selected to complete the simulated flight task in different situations, and the subjective 10-dimensional situational awareness rating technology (10-D SART) and objective flight performance, situational awareness global assessment technique (SAGAT), and physiological measurement (electrocardiogram, electrodermal activity and respiration) were combined to carry out the experimental test. The experimental analysis indicates that the trend of the theoretical value predicted by the model is significantly related to the experimental results. The proposed situation awareness quantitative model can give some reference to guide the design of man-machine interface in the cockpit and to optimize the flight task assignment.
- situation awareness (SA) /
- multi-resource load /
- cognitive modeling /
- mental workload /
- interface design /
- ergonomic

HTML全文

图 1 基于多资源负荷的SA模型

Figure 1. SA model based on multi-resource load

下载: 全尺寸图片幻灯片

图 2 HUD显示AOI划分及实验场景

Figure 2. Divisions of AOI on HUD display and experimental scenario

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图 3 3种情境下SA预测值和实验测量指标变化趋势

Figure 3. Predicted SA values and change tendency of experimental measurement indices in 3 situations

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表 1 不同飞行情境仪表重要度和信息期望

Table 1. Importance and information expectancy of instrument in various flight situations

重要度和信息期望	情境	俯仰	速度	高度	滚转	航向
重要度	情境1	0.87	0.07	0.47	0.13	0.27
	情境2	0.47	0.07	0.87	0.13	0.27
	情境3	0.20	0.07	0.20	0.80	0.53
信息期望	情境1	0.38	0.13	0.25	0.13	0.13
	情境2	0.20	0.10	0.40	0.10	0.20
	情境3	0.10	0.10	0.10	0.40	0.30

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表 2 不同情境下飞行操作

Table 2. Flight operation in various situations

情境	操作要求
情境1	爬升至15 000 ft; 保持15°俯仰角, 保持航向298°, 滚转0°
情境2	巡航高度为15 000 ft; 保持航向298°, 滚转0°
情境3	航向由298°转为118°; 保持滚转左20°, 保持高度15 000 ft
注:1 ft=304.8 mm。

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表 3 界面编码显示属性

Table 3. Display attributes of interface coding

显示属性	俯仰	空速	高度	滚转	航向	权重
字符大小	60.65	60.65	60.65	60.65	60.65	0.22
颜色匹配	29.15	29.15	29.15	29.15	29.15	0.23
布局位置	82.81	57.29	60.42	46.88	14.58	0.35
突显性	0	0	0	0	0	0.22
界面编码	48.41	39.57	40.66	35.97	24.78

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表 4 高层次情境认知表征

Table 4. Deep-level situation cognition representation

情境	注意资源消耗之和A_i	平均负荷水平/min	平均持续时间/s	规则可用性
情境1	0.322 4	50.37	154	0.280 2
情境2	0.295 0	49.59	217	0.388 8
情境3	0.382 6	51.22	177	0.331 2

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表 5 情境1各AOI注意资源计算

Table 5. Calculation of attention resource in each AOI under situation 1

注意资源元素	俯仰	空速	高度	滚转	航向
界面编码	0.255 6	0.209 0	0.214 7	0.189 9	0.130 9
注意转移	0.145 4	0.219 2	0.225 6	0.195 2	0.214 5
信息价值	0.123 9	0.005 6	0.059 2	0.012 4	0.029 0
信息期望	0.375 0	0.125 0	0.250 0	0.125 0	0.125 0
注意资源消耗A_j	1.250 2	0.015 2	0.305 4	0.041 9	0.129 2

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表 6 SA预测值和主客观测量结果

Table 6. Predicted SA values combined with subjective and objective measurement results

测量指标	情境1	情境2	情境3
SA预测值	0.283 4	0.392 1	0.331 2
飞行绩效/10^-2	0.384 9±0.256 8	0.532 4±0.385 1	0.454 4±0.314 8
SA反应时/ms	5 168.45±1 562.2	4 440.67±844.7	4 958.28±1 253.0
SA正确率/%	66.18±19.14	77.06±12.13	70.00±11.18
10-D SART得分	21.8±6.06	23.8±7.29	22.8±7.86
平均心率/(次·min^-1)	93.77±14.03	90.09±13.34	90.23±12.55
SDNN/ms	47.77±28.04	50.09±22.88	48.84±29.40
呼吸率/(次·min^-1)	21.11±3.29	20.76±3.25	20.28±3.36
EDA/μs	2.45±0.11	2.39±0.08	2.41±0.05

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表 7 SA预测值和测量指标相关性分析

Table 7. Analysis of correlation between predicted SA values and measurement indices

相关系数和显著性值	10-D SART得分	飞行绩效	SA正确率	SA反应时	平均心率	SDNN	呼吸率	EDA
r	0.998^*	0.999^*	0.995	-0.986	-0.848	1.000	-0.351	-0.978
P	0.044	0.023	0.064	0.108	0.356	0.015	0.772	0.134

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