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How to assess the capacity of urban airspace: A topological approach using keep-in and keep-out geofence

机译:如何评估城市空域的容量:使用保持和保持地理围栏的拓扑方法

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The anticipated proliferation of small Unmanned Aerial Vehicles (sUAVs) in urban areas has garnered greater interest in capacity estimation of the low-altitude airspace. As a first step to assess such capacity, we propose a topological analysis framework to identify free versus usable airspace in a 3D environment filled with abundant geometric elements. To incorporate the underlying geospatial complexity as well as vehicle operational requirements, two types of geofence (-) keep-out and keep-in (-) are utilized. The keep-out geofence defines a boundary around static objects to keep sUAV out. The keep-in geofence is a 3-D sphere to keep a vehicle in. While the keep-out mainly focuses on public assurance as a mitigation measure against collision and privacy risk, the keep-in mainly concerns the operational feasibility of a vehicle. Three scenarios of keep-out, keep-in, and dual geofencing were applied and compared in a hypothetical case study as well as in the real 3-D environment of Seoul, South Korea. The results show that the keep-in usability is an upperbound of the keep-out, due to its unique capability to identify corridor segments using the alpha shape method. The dual scenario demonstrated tradeoffs between two types of geofence in a built-up environment, in which the keep-in exhibited more robust behavior than the keep-out. It is evident that both geofencing methods need to be considered in parallel in urban areas. In addition, decisions on the geofence parameters should be made in accordance with the geospatial complexity and flight purposes, rather than relying on fixed values. The proposed framework is not only capable of evaluating airspace availability in an adaptive and intelligent manner, but also has the potentials to identify departure/arrival locations and design ascent/descent routes.
机译:小型无人飞行器(sUAV)在城市地区的预期扩散已引起人们对低空空域容量估计的更大兴趣。作为评估这种能力的第一步,我们提出了一种拓扑分析框架,以在充满丰富几何元素的3D环境中识别自由空间与可用空间。为了结合潜在的地理空间复杂性和车辆运行要求,使用了两种类型的地理围栏(-)保持和保持(-)。保持地理围栏定义了静态对象周围的边界,以防止sUAV进入。保持型地理围栏是用于保留车辆的3D球体。尽管保持型主要关注于公共保证,作为缓解碰撞和隐私风险的缓解措施,但保持型主要涉及车辆的操作可行性。在假设的案例研究中以及在韩国首尔的真实3D环境中,应用了三种保留,保留和双重地理围墙场景,并进行了比较。结果表明,保持保持可用性是保持保持的上限,这是因为保持保持可用性是使用alpha形状方法识别走廊段的独特功能。双重场景展示了在构建环境中两种类型的地理围栏之间的权衡,在这种环境中,保留区比保留区显示出更强大的行为。显然,在城市地区需要同时考虑两种地理围栏方法。此外,应根据地理空间复杂性和飞行目的来决定地理围栏参数,而不要依赖固定值。所提出的框架不仅能够以自适应和智能的方式评估空域可用性,而且具有识别出发/到达位置和设计上升/下降路线的潜力。

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