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Open AccessArticle

Collision Detection for UAVs Based on GeoSOT-3D Grids

Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
Zhengzhou Institute of Surveying and Mapping, Zhengzhou 450001, China
College of Engineering, Peking University, Beijing 100871, China
Beijing Institute of Big Data Research, Beijing 100871, China
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(7), 299;
Received: 7 May 2019 / Revised: 24 June 2019 / Accepted: 13 July 2019 / Published: 15 July 2019
(This article belongs to the Special Issue Global Grid Systems)
PDF [3748 KB, uploaded 15 July 2019]


The increasing number of unmanned aerial vehicles (UAVs) has led to challenges related to solving the collision problem to ensure air traffic safety. The traditional approaches employed for collision detection suffer from two main drawbacks: first, the computational burden of a pairwise calculation increases exponentially with an increasing number of spatial entities; second, existing grid-based approaches are unsuitable for complicated scenarios with a large number of objects moving at high speeds. In the proposed model, we first identified UAVs and other spatial objects with GeoSOT-3D grids. Second, the nonrelational spatial database was initialized with a multitable strategy, and spatiotemporal data were inserted with the GeoSOT-3D grid codes as the primary key. Third, the collision detection procedure was transformed from a pairwise calculation to a multilevel query. Four simulation experiments were conducted to verify the feasibility and efficiency of the proposed collision detection model for UAVs in different environments. The results also indicated that 64 m GeoSOT-3D grids are the most suitable basic grid size, and the reduction in the time consumption compared with traditional methods reached approximately 50–80% in different scenarios. View Full-Text
Keywords: collision detection; unmanned aircraft vehicles; GeoSOT-3D collision detection; unmanned aircraft vehicles; GeoSOT-3D

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Zhai, W.; Tong, X.; Miao, S.; Cheng, C.; Ren, F. Collision Detection for UAVs Based on GeoSOT-3D Grids. ISPRS Int. J. Geo-Inf. 2019, 8, 299.

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