Investigation of Metrics for Assessing Human Response to Drone Noise.
Investigation of Metrics for Assessing Human Response to Drone Noise.
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DOI：
10.3390/ijerph19063152
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发表时间：
2022-03-08
影响因子：
--
通讯作者：
Nicholls RK
中科院分区：
文献类型：
--
作者：
Torija AJ;Nicholls RK
新型电动航空运输正在成为一个行业，可以通过融入基础设施和服务，帮助改善生活在大都市和农村地区的人们的生活。然而，随着这一新的无障碍资源的势头越来越强，调查对公众健康的任何潜在不利影响的必要性变得至关重要。本文详细研究了可用的噪声指标和声质量指标（SQM）评估无人机噪声感知的有效性。进行了一项主观实验，以收集人类对一组全面的无人机声音反应的数据，并调查感知烦恼、感知响度和感知音调与关键心理声学因素之间的关系。基于统计分析，获得了无人机噪声的感知烦恼度、响度和音高的主观模型。这些模型提供了对关键心理声学特征的理解，以便在决策中考虑，以减轻无人机噪音的影响。对于本文中测试的无人机声音，感知烦恼的主要贡献者是感知噪声水平（PNL）和锐度;感知响度是PNL和波动强度;感知音高是锐度，粗糙度和Aures音调。对无人机声音的反应被发现对无人机和接收器之间的距离高度敏感，以地面以上的高度（HAGL）测量。所有这些发现都可以为无人机操作条件的优化提供信息，以减轻社区噪音。
Novel electric air transportation is emerging as an industry that could help to improve the lives of people living in both metropolitan and rural areas through integration into infrastructure and services. However, as this new resource of accessibility increases in momentum, the need to investigate any potential adverse health impacts on the public becomes paramount. This paper details research investigating the effectiveness of available noise metrics and sound quality metrics (SQMs) for assessing perception of drone noise. A subjective experiment was undertaken to gather data on human response to a comprehensive set of drone sounds and to investigate the relationship between perceived annoyance, perceived loudness and perceived pitch and key psychoacoustic factors. Based on statistical analyses, subjective models were obtained for perceived annoyance, loudness and pitch of drone noise. These models provide understanding on key psychoacoustic features to consider in decision making in order to mitigate the impact of drone noise. For the drone sounds tested in this paper, the main contributors to perceived annoyance are perceived noise level (PNL) and sharpness; for perceived loudness are PNL and fluctuation strength; and for perceived pitch are sharpness, roughness and Aures tonality. Responses for the drone sounds tested were found to be highly sensitive to the distance between drone and receiver, measured in terms of height above ground level (HAGL). All these findings could inform the optimisation of drone operating conditions in order to mitigate community noise.
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DOI：
10.3390/ijerph18126202
发表时间：
2021-06-08
影响因子：
--
作者：
Ivošević J;Ganić E;Petošić A;Radišić T
通讯作者：
Radišić T
DOI：
10.3390/ijerph15030519
发表时间：
2018-03-14
影响因子：
--
作者：
Basner M;McGuire S
通讯作者：
McGuire S
DOI：
10.3390/ijerph18178893
发表时间：
2021-08-24
影响因子：
--
作者：
Hui CTJ;Kingan MJ;Hioka Y;Schmid G;Dodd G;Dirks KN;Edlin S;Mascarenhas S;Shim YM
通讯作者：
Shim YM
影响因子：
6.6
作者：
Duporge, Isla;Spiegel, Marcus P.;Klinck, Holger
通讯作者：
Klinck, Holger
影响因子：
1.7
作者：
Iannace, Gino;Ciaburro, Giuseppe;Trematerra, Amelia
通讯作者：
Trematerra, Amelia