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引用次数: 8
摘要
NASA UTM项目首席研究员Parimal Kopardekar博士在2016年DASC的全体会议上强调了理解体积、噪声和频谱在空域需求-容量建模中的作用,这是UTM开发人员向航空电子研究社区b[1]提出的三个要求。本文针对无人机在人口密集地区上空低空不受控制空域运行的情况,提出了对这三个要求的初步答案:我们根据以交通量可管理性、无人机噪声污染和频谱需求为中心的几个指标来估计空域容量。我们的工作有助于弥合监管机构和行业,为政策制定者提供决策支持工具,帮助量化制造商必须遵循的技术要求,以确保小型无人机系统(sUAS)在城市空域的无缝运行。
Sampling-based capacity estimation for unmanned traffic management
The plenary talk at DASC 2016 by Dr. Parimal Kopardekar, the Principal Investigator of NASA UTM program, highlighted understanding the role of volume, noise and spectrum considerations in airspace demand-capacity modeling as the three requests from UTM developers to the avionics research community [1]. This paper proposes initial answers to all three requests, for the case of unmanned aerial vehicles (UAVs) operating in low-altitude uncontrolled airspace above populated areas: we estimate airspace capacity under several metrics centered on traffic volume manageability, drones noise pollution and spectrum demand. Our work aids in bridging regulators and the industry, by providing policy makers with decision support tools which help to quantify technological requirements which the manufacturers must follow in order to ensure seamless operation of small unmanned aerial systems (sUAS) in an urban airspace.