走向一个动态的国家运输噪声地图:模拟交通量时间变化的交通量
Mylan R Cook1, Kent L Gee1, Mark K Transtrum1
1Department of Physics and Astronomy, Brigham Young University, Provo, Utah 84602, USA.
The Journal of the Acoustical Society of America
|November 9, 2023
概括
这项研究引入了VROOM模型,该模型使用交通量数据在全国范围内预测每小时的交通噪声. VROOM提供比国家运输噪声地图更准确的噪声预测,改进了时间噪声映射.
科学领域:
- 环境声学环境声学
- 运输工程 运输工程 运输工程
- 数据科学是数据科学.
背景情况:
- 目前的交通噪音测绘依赖于年均值,无法捕捉显著的时间变化.
- 准确,时间变化的噪音数据对于有效的环境和城市规划至关重要.
研究的目的:
- 开发和验证交通量模型 (VROOM) 以预测美国大陆每小时的交通噪声 (CONUS).
- 将VROOM的准确性与现有的噪声测绘方法比较,例如国家交通噪声地图 (NTNM).
主要方法:
- 利用来自CONUS的众多监控站的每小时流量数据.
- 应用福里埃分析来识别每日,每周和每年的流量周期.
- 采用了对无光谱的主要组件分析 (PCA) 来捕捉占主导地位的流量模式.
- 开发了VROOM以使用九个主要组件和预测系数在全国范围内表示每小时的流量.
主要成果:
- VROOM准确地预测每小时的交通噪音,典型的声音水平误差在几分贝内.
- 现有的NTNM表现出严重的不准确性,错误往往超过10分贝.
- 通过福里埃和PCA识别出不同的每日,每周和每年的流量周期.
结论:
- 与目前的方法相比,VROOM在预测暂时变化的运输噪声方面取得了重大进展.
- 这个模型是创建一个动态,光谱可变的国家交通噪音地图的基本步骤.
- 准确的每小时噪音预测可以使环境影响评估和城市规划更加精细.
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