基于认知过程的飞行员脑力负荷动态预测

Pilots’mental workload dynamic prediction based on cognitive process

现代军用飞机座舱驾驶系统信息高度密集、任务复杂多变。为探讨信息加工类型与多任务协同对飞行员脑力负荷的影响,依据ACT-R认知模块与脑力负荷决定性因素的关联性,将飞行员的脑力负荷划分为感知负荷与认知负荷,并基于四维多资源干扰理论,考虑多任务协同作用时的资源干扰对脑力负荷的影响,提出了基于认知过程的飞行员脑力负荷动态预测模型。为校验所提模型,选取16名被试完成4种模拟飞行任务的脑力负荷评价实验,结果显示:不同飞行任务在飞行绩效、NASA-TLX主观评价、平均扫视时间与扫视频率下的主效应显著(P<0.05),总脑力负荷预测值与NASA-TLX主观评价、扫视频率和心率呈显著正相关,平均脑力负荷预测值与飞行绩效、瞳孔直径和平均扫视时间呈显著正相关。所提模型对飞行员脑力负荷的动态预测与评价具有应用价值。

Modern military flight systems are highly information-intensive and their tasks are complex and changeable.In order to explore the influence of information processing types and multi-task coordination on pilots’mental workload,a quantitative prediction model based on the cognitive process was proposed.The ACT-R cognitive module and the mental workload determinants were used to separate the pilot’s mental workload into perceptual workload and cognitive burden.The multi-task resource interference for mental workload was calculated based on multiple resources.16 subjects were selected to complete the multi-factor mental workload experiment.The results showed that the main effects of flight performance,NASA-TLX,average saccade time and scanning rate were significant(P<0.05).Subjective evaluation,RRCV and HR were significantly positively correlated with the total mental workload.And the average mental workload was significantly positively correlated with flight performance,pupil diameter and average saccade time.In order to anticipate and assess the mental workload of pilots,the prediction model offered a certain application value.