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A modified noise-prediction model for highways with significant motorcycle traffic

机译:具有重要摩托车交通的高速公路改进的噪声预测模型

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摘要

One of the undesirable outcomes of the rapid travel of a large number of vehicles on highways is the high level of noise pollution. Tehran is the most noise-polluted city in Iran, where the contribution of motorcycles to noise pollution is significant. In this paper, the equivalent sound pressure levels (L-Aeq,L-1h) were measured alongside seven highways in Tehran and were compared with the environmental guidelines. The traffic-noise-prediction model for highways proposed by the government (IR-TNM) was also evaluated based on the collected data from field measurements. The findings reveal that traffic noise levels at measured points exceeded the maximum noise level allowed by Iran's Department of the Environment. Also, there was a significant difference between the results of the prediction model and measured values at the measured points. As highway access for motorcycles in Tehran is not prohibited and their impact on highway noise is not considered in the IR-TNM prediction model, a modification of the model, considering the motorcycle traffic and re-estimating the coefficients, was performed using the Gauss-Newton method, which led to a better fit to the observed data both for the calibration and validation data sets.
机译:大量车辆在高速公路上快速行动的不良结果之一是高水平的噪音污染。德黑兰是伊朗最喧嚣的城市,摩托车对噪音污染的贡献是显着的。在本文中,在德黑兰的七大高速公路上测量了等效声压水平(L-AEQ,L-1H),并与环境指南进行了比较。政府(IR-TNM)提出的高速公路的交通噪声预测模型也基于来自现场测量的收集的数据进行评估。结果表明,测量点处的交通噪声水平超过了伊朗环境部门允许的最大噪声水平。此外,预测模型的结果与测量点的测量值之间存在显着差异。由于不禁止德黑兰摩托车的公路访问,并且在IR-TNM预测模型中不考虑它们对公路噪声的影响,考虑到摩托车交通和重新估算系数的模型的修改是使用高斯 - Newton方法,它导致校准和验证数据集的观察数据更好。

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