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Dynamic No-Fly Zone for Drones

机译:无人驾驶动态无蝇区

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Recently, drones have been widely used for a variety of purposes, such as surveillance, journalism, environmental protection, disaster management and various leisure activities. However, due to the noneffective monitoring of drones, the accidents of drones interfere with low-flying aircrafts and civil aviations emerge in an endless stream, resulting in many issues in safety. In this paper, we have designed the Dynamic No-fly Zone, which is based on a sphere centered on the current flight with a radius, to accurately model the no-fly zone of drones. Furthermore, in order to deal with the big data produced by the dynamically changed positions of flights and aircrafts, we have presented a Two-Level Dynamic Alert Zone. On top of it, a machine learning algorithm named Positive Logic Model (PLM) is proposed for the realization of the Dynamic No-fly Zone for drones. Without extra hardware support, our heuristic model and algorithm are able to solve the problem of drones interfere with low-flying aircrafts and civil aviations. Simulation experimental results demonstrate the effectiveness of our heuristic approach.
机译:最近,无人机已被广泛用于各种目的,如监督,新闻,环境保护,灾害管理和各种休闲活动。然而,由于无人机的无效监测,无人机的事故干扰了低飞行的飞机和民用航空,在无休止的流中出现,导致安全的许多问题。在本文中,我们设计了动态无飞区域,基于以半径为中心的球体,以准确地模拟无人机的无飞带。此外,为了处理由航班和飞机的动态变化的位置产生的大数据,我们提出了一个双层动态警报区域。在其顶部,提出了一种名为肯定逻辑模型(PLM)的机器学习算法,用于实现无人驾驶动态无飞区域。无需额外的硬件支持,我们的启发式模型和算法能够解决旱机干扰低飞行飞机和民用航空的问题。仿真实验结果表明了我们启发式方法的有效性。

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