Assessment of Drone Noise Within Urban Soundscapes

Abstract

Drones have the potential to be implemented in the infrastructure of metropolitan areas to provide services to the public such as delivery, maintenance, and even blue light services. The scope for drone capability is large, but this comes with the risk of introducing a dominant, unpleasant noise source above urban areas, with potentially adverse health effects. This paper describes research which investigates whether, and to what extent, different urban soundscapes mask noise from drone operations, and using statistical analysis methods such as principal component analysis interrogates which frequency ranges of drone noise should be appropriately masked to reduce perceived annoyance. A subjective experiment was carried out, where participants gave response values to a comprehensive set of drone sounds embedded into differing urban soundscapes. Response values included perceived annoyance, perceived loudness, drone noise dominance and soundscape pleasantness. Critical-band rate specific sound quality metrics were then calculated for the soundscapes with and without each drone sound present, and the metric value differences were used in principle component analysis, with the results suggesting which specific sound quality metrics contribute significantly to the response values.