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Considering the ever-increasing use of drones in a plentitude of application areas, the risk is that also an ever-increasing number of drone incidents would be observed. Research has shown that a large majority of all incidents with drones is due not to technological, but to human error. An advanced risk-reduction methodology, focusing on the human element, is thus required in order to allow for the safe use of drones. In this paper, we therefore introduce a novel concept to pro-vide a qualitative and quantitative assessment of the performance of the drone op-erator. The proposed methodology is based on one hand upon the development of standardized test methodologies and on the other hand on human performance modeling of the drone operators in a highly realistic simulation environment.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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| downloads | 13 |

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