面向HUD的飞行员注意力分配影响因素量化研究

Quantitative research on impact factors of pilot's attention allocation on HUD

基于SEEV模型,从人类知觉信息加工的2种方式入手,开展面向平视显示器(HUD)的飞行员注意力分配影响因素量化研究。利用GL Studio软件和Vega Prime软件建立平视显示系统,从该系统的HUD界面模型中提取图像,输入到改进的ITTI模型中,以像素点灰度值作为图像突显性的度量标准,从而确定图像局部突显性。针对最终进近着陆阶段,通过分析注意力分配侧重点对各兴趣域的预期进行量化,得到的数据符合"顺序分级法";应用注意力分配侧重点分析,量化SEEV模型中的价值,并采用Beringer问卷调查数据与量化结果进行比较,结果表明根据注意力分配侧重点分析确定价值的方法简便、有效。本研究对注意力分配影响因素的量化,不仅为HUD界面设计提供科学依据,也为后续建立注意力分配模型提供了基础。

Based on SEEV model and two modes of human information processing, a quantitative research on the impact fac- tors of pilot＇s attention allocation is conducted on head-up display （HUD）. An image from HUD interface model explored by GL Studio and Vega Prime is input to the improved ITI＇I model to determine the local salience of the image, meanwhile, the image salience is measured by gray value of pixel. Value and expectancy, the two factors of SEEV model, are quantified by focus analysis of attention allocation on HUD in the final approach and landing phases. Data show that the expectancy value is consistent to the ordinal ranking system. The value is compared to the data of Beringer＇ s questionnaire, indicating that quantifying value with focus analysis of attention allocation is simple and effective. The quantification of pilot＇s attention impact factors in the current research will not only provide the scientific proof for HUD design, but also build foundation for attention allocation model.