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Probabilistic Risk-Based Operational Safety Bound for Rotary-Wing Unmanned Aircraft Systems Traffic Management

机译:旋翼无人机系统交通管理的概率基于风险的运营安全限制

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摘要

A novel method to determine probabilistic operational safety bound for rotary-wing unmanned aircraft systems (UAS) traffic management is proposed in this paper. The key idea is to combine a deterministic model for rotary-wing UAS flying distance estimation to avoid conflict and a probabilistic uncertainty quantification methodology to evaluate the risk level (defined as the probability of failure) of separation loss between UAS. The proposed methodology results in a dynamic and probabilistic airspace reservation to ensure the safety and efficiency for future UAS operations. The model includes UAS performance, system updating frequency and accuracy, and weather conditions. Also, the parameterized probabilistic model includes various uncertainties from different sources and develops an anisotropic operational safety bound. Monte Carlo simulations are used to illustrate the operational safety bound determination with a specified risk level (i.e., probability of failure). It is known that uncertainty plays an important role in determining the operational safety bound size, and the proposed methodology provides a simple and efficient quantification of uncertainty impact on the safety bound with a prescribed risk level. It is also providing a useful tool to quantify uncertainty reduction with additional information and measurements in future UAS operations.
机译:本文提出了一种确定旋翼无人机系统(UAS)交通管理的概率运行安全界定的新方法。关键思想是将旋转翼UA飞行距离估计的确定性模型组合,以避免冲突和概率不确定性量化方法,以评估UA之间的分离损耗的风险级别(定义为失败的概率)。所提出的方法导致动态和概率的空域预留,以确保未来UAS操作的安全性和效率。该模型包括UAS性能,系统更新频率和准确性,以及天气条件。此外,参数化概率模型包括来自不同来源的各种不确定性,并产生各向异性操作安全绑定。 Monte Carlo模拟用于说明具有指定风险级别的操作安全绑定确定(即失败的可能性)。众所周知,不确定性在确定操作安全束缚尺寸方面发挥着重要作用,并且所提出的方法提供了对具有规定风险级别的安全限制的简单有效量化的不确定性影响。它还提供了一种有用的工具,可以在未来的UAS操作中通过附加信息和测量来量化不确定性降低。

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  • 来源
    《Current Organic Synthesis》 |2020年第3期|共11页
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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 有机化学;
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  • 入库时间 2022-08-20 00:17:23

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