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用于城市道路交通噪声烦恼度计算的噪声敏感度和响度导数指标

Noise sensitivity and loudness derivative index for urban road traffic noise annoyance computation.

作者信息

Gille Laure-Anne, Marquis-Favre Catherine, Weber Reinhard

机构信息

Centre d'étude et d'expertise sur les risques, l'environnement, la mobilité et l'aménagement (CEREMA), Direction Territoriale Île-de-France, 21-23 rue Miollis, Paris Cedex 15, 75732, France.

Univ Lyon, Ecole Nationale des Travaux Publics de l'Etat (ENTPE), Laboratoire Génie Civil et Bâtiment, 3 rue Maurice Audin, Vaulx-en-Velin, F-69518, France.

出版信息

J Acoust Soc Am. 2016 Dec;140(6):4307. doi: 10.1121/1.4971329.

Abstract

Urban road traffic composed of powered-two-wheelers (PTWs), buses, heavy, and light vehicles is a major source of noise annoyance. In order to assess annoyance models considering different acoustical and non-acoustical factors, a laboratory experiment on short-term annoyance due to urban road traffic noise was conducted. At the end of the experiment, participants were asked to rate their noise sensitivity and to describe the noise sequences they heard. This verbalization task highlights that annoyance ratings are highly influenced by the presence of PTWs and by different acoustical features: noise intensity, irregular temporal amplitude variation, regular amplitude modulation, and spectral content. These features, except irregular temporal amplitude variation, are satisfactorily characterized by the loudness, the total energy of tonal components and the sputtering and nasal indices. Introduction of the temporal derivative of loudness allows successful modeling of perceived amplitude variations. Its contribution to the tested annoyance models is high and seems to be higher than the contribution of mean loudness index. A multilevel regression is performed to assess annoyance models using selected acoustical indices and noise sensitivity. Three models are found to be promising for further studies that aim to enhance current annoyance models.

摘要

由电动两轮车(PTW)、公交车、重型和轻型车辆组成的城市道路交通是噪声烦恼的主要来源。为了评估考虑不同声学和非声学因素的烦恼模型,进行了一项关于城市道路交通噪声引起的短期烦恼的实验室实验。在实验结束时,要求参与者对他们的噪声敏感性进行评分,并描述他们听到的噪声序列。这项言语化任务突出表明,烦恼评分受到电动两轮车的存在以及不同声学特征的高度影响:噪声强度、不规则的时间幅度变化、规则的幅度调制和频谱内容。除了不规则的时间幅度变化外,这些特征通过响度、音调成分的总能量以及飞溅和鼻音指数得到了令人满意的表征。引入响度的时间导数可以成功地对感知到的幅度变化进行建模。它对测试的烦恼模型的贡献很大,似乎比平均响度指数的贡献还要高。使用选定的声学指标和噪声敏感性进行多级回归,以评估烦恼模型。发现有三个模型对于旨在改进当前烦恼模型的进一步研究很有前景。

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