基于認(rèn)知特性的飛行員視覺注意力分配建模與實(shí)驗(yàn)研究

莊達(dá)民 完顏笑如

摘 要：該研究以飛機(jī)駕駛艙人機(jī)界面設(shè)計(jì)為應(yīng)用背景，通過結(jié)合具體飛行任務(wù)開展復(fù)雜人機(jī)界面環(huán)境下，飛行員視覺注意機(jī)制的數(shù)學(xué)建模研究，以期對(duì)飛行員的視覺注意力分配行為進(jìn)行事前預(yù)測(cè)，先后提出了基于混合熵最大化的注意力分配模型和多因素條件下的注意力分配模型。并且根據(jù)工效學(xué)仿真實(shí)驗(yàn)對(duì)所提出的注意力分配模型進(jìn)行可用性驗(yàn)證，從而為飛機(jī)駕駛艙的人機(jī)界面設(shè)計(jì)提供理論支持和技術(shù)手段。研究針對(duì)飛行員視覺注意力分配機(jī)制進(jìn)行數(shù)學(xué)建模，并基于飛機(jī)仿真顯示界面開展工效學(xué)驗(yàn)證實(shí)驗(yàn)，結(jié)合紅外眼動(dòng)裝置對(duì)注視點(diǎn)分布的測(cè)量，應(yīng)用回歸分析的統(tǒng)計(jì)方法驗(yàn)證模型。基于混合熵最大化的注意力分配模型是以飛行員的儀表掃視行為為主要應(yīng)用情境而建立，以一組視覺加工信息為研究對(duì)象，以認(rèn)知工程、模糊數(shù)學(xué)和廣義信息論為主要理論基礎(chǔ)。為驗(yàn)證數(shù)學(xué)模型的可用性，根據(jù)注意力分配理論模型可計(jì)算出作業(yè)人員對(duì)各儀表信息的注意力分配比例理論值；通過開展注意力分配仿真實(shí)驗(yàn)，注意力分配比例的行為學(xué)實(shí)驗(yàn)值通過作業(yè)人員對(duì)不同儀表信息的正確操作率進(jìn)行統(tǒng)計(jì)獲得；注意力分配比例的生理學(xué)實(shí)驗(yàn)值通過作業(yè)人員對(duì)不同儀表信息的注視點(diǎn)數(shù)量進(jìn)行統(tǒng)計(jì)獲得。通過將注意力分配比例的理論值與各實(shí)驗(yàn)值進(jìn)行對(duì)比，得出在腦力負(fù)荷適中情況下所建模型具有一定可用性的結(jié)論。雖然基于混合熵的注意力分配模型較好的量化了認(rèn)知過程中的模糊性和隨機(jī)性，但是由于模型本身對(duì)于影響因素的結(jié)算需要對(duì)信息檢出效率進(jìn)行事先測(cè)量，從而降低了模型的預(yù)測(cè)能力。為了進(jìn)一步完善和優(yōu)化注意力分配模型，在混合熵模型和SEEV模型的基礎(chǔ)上提出了多因素條件下注意力分配數(shù)學(xué)模型。多因素模型從基于飛行員的儀表掃視行為所反映的認(rèn)知特性分析出發(fā)，密切結(jié)合航空任務(wù)情境，對(duì)前人的模型進(jìn)行了重新的解釋、整合和詳細(xì)地公式推導(dǎo)，并結(jié)合之前在視覺信息編碼方面所開展的工作，將“信息檢出效率”這一因素也引入到注意力分配模型中，從而提出了一個(gè)新的注意力分配模型，該模型在混合熵的理論基礎(chǔ)上，綜合考慮了信息價(jià)值、人為失誤以及信息檢出效率等因素對(duì)飛行員注意力分配策略的影響。為將所建模型應(yīng)用于航空信息顯示界面優(yōu)化設(shè)計(jì)并驗(yàn)證其有效性，基于飛機(jī)平視顯示器仿真模型，通過測(cè)量被試者對(duì)所監(jiān)視視覺目標(biāo)的識(shí)別績(jī)效，同時(shí)結(jié)合眼動(dòng)儀的實(shí)時(shí)觀測(cè)數(shù)據(jù)，分析了被試者的實(shí)際注意力分配情況。實(shí)驗(yàn)結(jié)果初步驗(yàn)證了該注意力分配模型在復(fù)雜人機(jī)界面下的有效性。

關(guān)鍵詞：視覺注意力分配 數(shù)學(xué)建模 工效實(shí)驗(yàn) 認(rèn)知特性

Abstract：In this research， pilot attention allocation mechanism under complex human-machine interface environment was studied and analyzed in a mathematical fashion in the application background of aircraft cockpit interface design.To predict pilot attention allocation， a serial of mathematical models were established which contained one model based on hybrid entropy and the other under multiple factors condition. In validation of these models，ergonomics simulation experiments were designed and carried out to verify the effectiveness of the models，which provided both theoretical basis and technological method to optimal design of human-machine interface in aircraft cockpit.Quantitative research into a pilots attention allocation mechanism is required in the optimization design of an aircraft human-machine interface and system evaluation.After making a comprehensive consideration of several factors，including the importance of information， information detective efficiency and human errors，a pilot attention allocation model was built on the basis of hybrid entropy. To verify this model，a simulation model of a head-up display used to present flight indicators was developed. The experiments on the key-press response and eye-movement tracking were designed and carried out under the cruise and hold modes.As the experiment results are in good agreement with the theoretical model， the effectiveness of the pilot attention allocation model based on fuzzy theory is confirmed.However，the former model required to quantify the information detection efficiency which reduced its prediction ability.A new forecast model of attention allocation is established on the basis of information priority using fuzzy mathematics.The new model was built on four trade-off factors，including information priority，occurring probability， salient and effort， which involved both channels of information processing.To validate this model，sixteen participants were recruited to perform an instrument monitoring task under different conditions.The participants were required to concentrate on the flight indicators presented on the simulation interface of head-up display and respond to abnormal information by pressing the corresponding button on the keyboard. The regression analysis revealed good agreement between fixation distribution and model prediction results.

Key Words：Visual attention allocation；Mathematical modeling；Ergonomics experiment；Cognitive characteristics

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