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首页> 外文会议>28th European Rotorcraft Forum >PILOT WORKLOAD ASSESSMENT USING FLIGHT SIMULATION
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PILOT WORKLOAD ASSESSMENT USING FLIGHT SIMULATION

机译：使用飞行模拟进行飞行员工作量评估

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A vital aspect of aircraft acceptability is its ability to operate under extreme conditions without requiring an excessive pilot workload. In recent years, the ability to predict this somewhat esoteric quantity using computational techniques has been pursued. Apart from enabling these tasks to be carried out with improved efficiency and safety, it has also provided the ability to perform tasks under tightly controlled flight conditions. This is of major importance to operation in severe atmospheric conditions where flight in proximity to vertical surfaces is common. Rapidly increasing computing power has allowed flight simulation to become available at increasingly modest costs. Consequently, the capability to examine the performance of an aircraft in relation to the corresponding pilot workload can be realistically achieved at an early stage of the design. The research to be described in this paper comprises an investigation into using such low cost simulation software and combining it with advanced processing techniques to arrive at a method of quickly estimating pilot workload and thereby rapidly assessing the implications of design modifications. The method described records the lateral and longitudinal control stick inputs the pilot makes to perform an aircraft manoeuvre for a variety of flight conditions and handling qualities. This process inevitably produces large amount of data which will require efficient processing. In order to achieve this, the data is then smoothed and reduced using Fourier and wavelet analysis technique. It was considered that conversion of these results to a workload rating would be an ideal candidate for a neural network, due to the fuzzy and subjective nature of this assessment. This neural network is trained with the results obtained from the signal breakdown as inputs and the pilot's assessment of workload as the target output. This process is validated by presenting previously unseen data to the network and continuing the training until suitably accurate workload ratings are predicted, resulting in a system capable of measuring workload given just control inputs. The advantages of this method over existing methods relying on direct pilot feedback are clear. Workload can be estimated at an early stage of the design process using simulator software, and responses to changes given almost instantly using a real-time display of workload. The novel use of a neural network makes the method adaptive to changes, and the ability to function correctly with a variety of aircraft and pilots without requiring fundamental changes to the algorithm, or any in-depth technical knowledge of this research. The study has shown promise, in that it corresponds well with the Bedford rating given by the pilot, and it therefore warrants further investigation.
机译：飞机可接受性的一个重要方面是其在极端条件下运行的能力，而无需过多的飞行员工作量。近年来，已经寻求使用计算技术来预测该多少深奥的量的能力。除了可以提高效率和安全性来执行这些任务外，它还提供了在严格控制的飞行条件下执行任务的能力。这对于在恶劣的大气条件下运行非常重要，在恶劣的大气条件下，通常会在垂直表面附近飞行。快速增加的计算能力使飞行模拟变得越来越便宜。因此，在设计的早期阶段就可以切实地实现检查飞机性能的能力。本文将要描述的研究包括对使用这种低成本仿真软件并将其与先进的处理技术结合起来的研究，以得出一种快速估计飞行员工作量，从而快速评估设计修改含义的方法。所描述的方法记录了飞行员为进行各种飞行条件和操纵质量而执行飞机操纵的横向和纵向操纵杆输入。该过程不可避免地产生大量数据，这将需要有效的处理。为了实现这一点，然后使用傅立叶和小波分析技术对数据进行平滑和缩减。人们认为，由于这种评估的模糊性和主观性，将这些结果转换为工作量等级将是神经网络的理想候选者。使用从信号分解中获得的结果作为输入并以飞行员对工作量的评估作为目标输出来训练该神经网络。通过向网络呈现以前看不见的数据并继续进行训练，直到预测出适当的准确工作负荷等级，从而使系统能够在仅提供控制输入的情况下就能够测量工作负荷，从而验证了此过程。与依靠直接导频反馈的现有方法相比，该方法的优势显而易见。可以在设计过程的早期使用模拟器软件来估算工作量，并使用实时显示的工作量几乎立即给出对更改的响应。神经网络的新颖用法使该方法能够适应变化，并具有在各种飞机和飞行员中正常运行的能力，而无需对该算法进行根本性更改，也无需任何深入的技术知识。该研究显示出了希望，因为它与飞行员给出的贝德福德评级非常吻合，因此值得进一步研究。

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