Abstract
Small unmanned aerial vehicles (sUAV) have becoming widespread both in commercial and for entertainment usages. They have been used in both business and entertainment purposes. There are sUAV-induced problems. sUAV trespassing into prohibited areas has been the major one of them. A sUAV was guided using a remote controller to suspending in the air. The sUAV may enter a prohibited public area. It may also enter private areas unwelcomed. We conducted a study to quantify human subjects’ sensitivity in discovering the trespassing of a sUAV into a specific area. Twenty human subjects were requested to determine whether the sUAV has trespassed in the test field or not by answering the question “whether the sUAV is inside the test field?” by replying a score from 1- definitely yes to 5- definitely no. The conditional probabilities of finding trespassing of the sUAV were calculated. A receivers’ operating characteristics curve was plotted. The P(A) was calculated and was adopted to represent the sensitivity of the subjects in detecting the trespassing of the drone. The outcomes of the analysis of variance testing the effects of the direction on the probabilities of replying “definitely yes” and “definitely or probably yes” were both insignificant. Neither were the effects of direction on the P(A) significant.
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References
Global UAV net. Trend and predictions of UAV market in China. Retrieved from http://www.81uav.cn/uav-news/201609/06/19009.html/ (in Chinese)
Luppicini, R., So, A.: A technoethical review of commercial drone use in the context of governance, ethics, and privacy. Technol. Soc. 46, 109–119 (2016)
Federal Aviation Administration. FAA aerospace forecast: Fiscal years 2016–2036. Retrieved from http://www.faa.gov/news/updates/?newsId=85227&cid=TW414/
Williams, K.W.: A summary of unmanned aircraft accident/incident data: human factors implications. Technical report DOT/FAA/AM-04/24, Federal Aviation Administration, US Department of Transportation
Democrat & Chronicle. Domestic drone accidents. Democrat & Chronicle. Retrieved from http://rochester.nydatabases.com/map/domestic-drone-accidents/
Forest C.12 drone disasters that show why the FAA hates drones, TechRepublic webpage. Retrieved from https://www.techrepublic.com/article/12-drone-disasters-that-show-why-the-faa-hates-drones/
Rao, B., Gopi, G.A., Maione, R.: The societal impact of commercial drones. Technol. Soc. 45, 83–90 (2016)
Loffi, J.M., Wallace, R.J., Jacob, J.D., Dunlap, J.C.: Seeing the threat: pilot visual detection of small unmanned aircraft systems in visual meteorological conditions. Int. J. Aviat., Aeronaut., Aerosp. 3(3), 1–26 (2016)
Civil Aeronautics Administration. No-fly and restricted fly zones for unmanned aircraft vehicles near airports (2017). Retrieved from https://www.caa.gov.tw/en/search/searchResult.asp?cx=000286267817699135961%3Akpxubvxz79m&ie=UTF-8&q=UAV&x=0&y=0&as_fid=4aOZ4neHn5QXzKmNf55/
Li, X.C.: Summaries of 10 dangerous UAV flying cases. Retrieved from http://www.gg-robot.com/asdisp2-65b095fb-59748-.html (in Chinese)
McNicol, D.: A primer of signal detection theory. Allen & Unwin, London (1972)
Federal Aviation Administration. Pilots’ role in collision avoidance. Retrieved from http://www.faa.gov/documentLibrary/media/Advisory_Circular/AC_90-48D.pdf
Acknowledgements
This research was financially supported by a grant from the Ministry of Science & Technology (MOST) of the Republic of China (under contract MOST106-2221-E-216-008-MY3).
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Li, K.W., Chang, S.J., Peng, L., Zhao, C. (2020). Visual Detection of Trespassing of a Small Unmanned Aerial Vehicle into an Airspace. In: Chen, J. (eds) Advances in Human Factors in Robots and Unmanned Systems. AHFE 2019. Advances in Intelligent Systems and Computing, vol 962. Springer, Cham. https://doi.org/10.1007/978-3-030-20467-9_21
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DOI: https://doi.org/10.1007/978-3-030-20467-9_21
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