ABSTRACT

Objective

This paper investigates the effects of using different decision-making models on pilots’ performance while facing non-normal flight circumstances.

Background

The captain must quickly make appropriate decisions once an aircraft faces emergency. Usually, human error is one primary cause of accidents, which inevitably affects the captain’s decision progress.

Method

Ten participants carried out a standard non-normal scenario (cargo smoke). Each participant is equipped with simulation experience and executed three sessions using three different decision models: the DOGAM, DECIDE, and CLEAR. After each session, the situation awareness (SA) and perceived workload were assessed using the Situational Awareness Rating Technology (SART) and NASA-TLX. An in-depth interview was also completed to comprehend their subjective perception of decision-making.

Results

Although the CLEAR outperformed the other models in SART and NASA-TLX scores, their performance regarding workload and SA was comparable. The fixing time of DOGAM was the longest, and the other two models were no significant difference. Subjectively, the DECIDE may require a high mental demand by simultaneously processing lots of information and measuring significant changes, whilst the DOGAM may encourage participants follow their own idea, promoting aggressive decisions.

Conclusion

This paper clarifies the importance of incorporating decision models into the cockpit and investigates the relatively feasible decision-making model. Variation across our results illustrated applying different decision models to train pilots and solve problems is suggested, thereby improving flight safety.

中文翻译：

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模拟非正常驾驶舱环境中航空决策模型对飞行学员态势感知和认知工作量的影响

摘要

客观的

本文研究了在面对非正常飞行情况时使用不同决策模型对飞行员表现的影响。

背景

一旦飞机面临紧急情况，机长必须迅速做出适当的决定。通常，人为失误是事故的主要原因之一，这不可避免地影响船长的决策进度。

方法

十名参与者进行了标准的非正常场景（货物烟雾）。每个参与者都具备模拟经验，并使用三种不同的决策模型执行三个会话：DOGAM、DECIDE 和 CLEAR。每次训练结束后，使用态势感知评级技术 (SART) 和 NASA-TLX 评估态势感知 (SA) 和感知工作量。还完成了深入访谈，以了解他们对决策的主观看法。

结果

尽管 CLEAR 在 SART 和 NASA-TLX 分数方面优于其他模型，但它们在工作负载和 SA 方面的性能相当。DOGAM的修复时间最长，其他两种模型无显着差异。主观上，DECIDE 可能需要同时处理大量信息和测量重大变化，从而需要较高的心理需求，而 DOGAM 可能会鼓励参与者遵循自己的想法，促进积极的决策。

结论

本文阐明了将决策模型纳入驾驶舱的重要性，并研究了相对可行的决策模型。我们的结果表明，建议应用不同的决策模型来培训飞行员并解决问题，从而提高飞行安全。