Abstract
With the rapid development of unmanned aerial vehicle (UAV), they have been used in various fields such as logistics systems, agriculture system, and etc. As the consumption of UAV increases, unmanned aircraft traffic management (UTM) system has become necessary. For now, there are few studies on the UTM system for small UAVs. In this paper, we suggest congestion control model in air space by using GPS in real time. We consider the congestion in two ways such as density and traffic jam. When a UAV enters at the range of GCS, GCS figures out whether it is authorized or not. After then, GCS receives the GPS data from each UAVs. With GPS data, GCS calculates density and shows the current situation of density. In order to calculate speed and direction, we use the GPS tracking data. Depending on these data, we can predict the traffic jam. Our proposed method can help to improve navigation system of UAV and to establish UTM system.
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Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2015R1C1A1A01052491, NRF-2017R1D1A3B03032637).
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Choi, JI., Seo, SH., Cho, T. (2018). The Congestion Control Model for Unmanned Aircraft System Traffic Management. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_187
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DOI: https://doi.org/10.1007/978-981-10-7605-3_187
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