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Human detection of drone invasion in a low‐altitude airspace: An application of signal detection theory
Author(s) -
Li Kai Way,
Peng Lu,
Zhao Caijun
Publication year - 2019
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20759
Subject(s) - drone , quadcopter , aeronautics , altitude (triangle) , computer science , aerospace engineering , engineering , biology , mathematics , genetics , geometry
A field study was conducted to investigate the sensitivity of human participants in detecting the invasion of a drone in the airspace. A Phantom 4 quadcopter was remotely controlled to hovering at air locations inside or outside of a stadium. Twenty participants were requested to determine whether the drone has invaded in the test field or not on a five‐point scale. The participants also responded whether they have heard the sound of the drone. The nonparametric measures of the sensitivity of drone invasion detection, or P ( A ), were calculated. The results indicated that the distance between the drone and the boundary of the airspace significantly affected the P ( A ) while the effects of drone altitude were not significant. The participants were not unbiased detectors. They tended to respond “probably yes,” in general, when they spotted a drone near the airspace. The hearing of the sound of the drone provided partial cues in drone invasion detection.