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Simulation-Based Evaluation of the Effects of Varying Degrees of Control Abstraction for Manned-Unmanned Teaming on Mental Workload of Pilots

机译:基于模拟的摩金诺特控制抽取不同程度对飞行员心理工作量的影响的评估

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The future of air combat is expected to evolve significantly to include new technologies and novel concepts of operation. The Manned-Unmanned Teaming concept involves low cost, attritable Unmanned Aerial Vehicles (UAVs) that could be deployed along with a manned aircraft. The UAVs act as a complementary asset and bolster offensive air operations. Given the complexity of future operating environments, the degree of autonomous control required for pilots to concurrently operate multiple UA Vs and their own aircraft is one area of concern. To determine the amount of autonomous control abstraction that has the largest impact in reducing operator workload and increasing system performance, a predictive workload model was developed using the Improved Performance Research Integration Tool (IMPRINT). This research concluded that maned-unmanned teams can increase mission performance and maintain the pilot’s cognitive workload at a manageable level by utilizing higher levels of human control abstraction, where unmanned systems have greater degree of autonomy.
机译:预计空战的未来将显着发展,包括新技术和新的操作概念。令人携带无人驾驶的合作概念涉及低成本,遗失的无人机(无人机),可以与载人飞机一起部署。无人机充当互补资产和支持攻击性空气运营。鉴于未来操作环境的复杂性,飞行员兼容多个UA和其自己飞机的飞行员所需的自主控制程度是一个关注的领域。为了确定对减少操作员工作负载的最大影响以及增加系统性能的自主控制抽象量,使用改进的性能研究集成工具(印记)开发了预测工作负载模型。这项研究得出结论,令人无人驾驶团队可以通过利用更高水平的人类控制抽象,在可管理的水平上增加任务表现,并使飞行员的认知工作量保持在可管理的水平。无人驾驶系统具有更大程度的自主权。

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