基于意图推理的驾驶舱人-自动化模式混淆检测

Sangjin Lee, Inseok Hwang, K. Leiden
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引用次数: 15

摘要

本文提出了一种基于意图推理的飞行甲板人-自动化模式混淆检测框架。由于驾驶舱技术的快速发展,人机自动化问题已成为当今航空安全的一个核心领域。先进飞行甲板的复杂性导致了新的安全问题,如人与自动化之间的功能失调互动。为了减少人为自动化问题引起的事故的发生,有必要及时发现它们之间的不良交互。然而,为了实现这一目标,需要对人类和自动化的行为以及它们之间的交互进行建模,这是一项具有挑战性的任务。本文提出了一个混合系统和一个离散事件系统来分别对自动化和导频的复杂行为进行建模。然后,提出了一种意图推理算法,利用行为模型和系统来推断人和自动化的意图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intent Inference-Based Flight-Deck Human-Automation Mode-Confusion Detection
In this paper, a new framework based on intent inference is proposed to detect the flight-deck human-automation mode confusion. Due to the rapid advancement of flight-deck technology, human-automation issues have become a core area of focus in today’s aviation safety. The complexity of the advanced flight deck leads to new safety concerns such as dysfunctional interaction between the human and the automation. To reduce the occurrence of incidents caused by the human-automation issues, it is necessary to detect the undesirable interaction between them in a timely manner. To this end, however, it is required to model the behavior of the human and the automation, as well as the interaction between them, which is a challenging task. In this paper, a hybrid system and a discrete event system are proposed to model the complex behaviors of the automation and the pilot, respectively. An intent inference algorithm is then proposed to infer the intents of the human and the automation using the behavior models and s...
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