Traffic Noise Assessment Using Intelligent Acoustic Sensors (Traffic Ear) and Vehicle Telematics Data.
Traffic Noise Assessment Using Intelligent Acoustic Sensors (Traffic Ear) and Vehicle Telematics Data.
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DOI：
10.3390/s23156964
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发表时间：
2023-08-05
期刊：
影响因子：
--
通讯作者：
Pope FD
中科院分区：
文献类型：
--
作者：
Ghaffarpasand O;Almojarkesh A;Morris S;Stephens E;Chalabi A;Almojarkesh U;Almojarkesh Z;Pope FD
在这里，我们介绍了交通耳，这是一种声学传感器组件，可以在不中断交通流量的情况下确定每一辆过往车辆的发动机噪音。该设备由一组麦克风和一个计算机视觉摄像头组成。使用声波分析、图像处理和机器学习算法来估计过往车辆的类别和速度。我们将交通耳传感器估计的交通成分与自动车牌识别(ANPR)摄像头记录的交通成分进行了比较，发现这两种方法在确定车辆类型和燃料方面具有很高的一致性，不确定度为1-4%。我们还开发了一种新的自下而上的评估方法，该方法使用交通耳朵传感器提供的噪音分析，以及使用城市交通地理空间和时间地图(GeoSTMUM)方法生成的广泛详细的城市交通地图。它适用于英国西米德兰兹地区道路上行驶的车辆。结果表明，在高峰时段，整个研究道路的交通发动机噪声降低了8%以上，而平日-周末效应的恶化效果几乎是一半。高速公路上每辆车的交通噪音系数(分贝/米)几乎总是高于其他被研究的道路。
Here, we introduce Traffic Ear, an acoustic sensor pack that determines the engine noise of each passing vehicle without interrupting traffic flow. The device consists of an array of microphones combined with a computer vision camera. The class and speed of passing vehicles were estimated using sound wave analysis, image processing, and machine learning algorithms. We compared the traffic composition estimated with the Traffic Ear sensor with that recorded using an automatic number plate recognition (ANPR) camera and found a high level of agreement between the two approaches for determining the vehicle type and fuel, with uncertainties of 1–4%. We also developed a new bottom-up assessment approach that used the noise analysis provided by the Traffic Ear sensor along with the extensively detailed urban mobility maps that were produced using the geospatial and temporal mapping of urban mobility (GeoSTMUM) approach. It was applied to vehicles travelling on roads in the West Midlands region of the UK. The results showed that the reduction in traffic engine noise over the whole of the study road was over 8% during rush hours, while the weekday–weekend effect had a deterioration effect of almost half. Traffic noise factors (dB/m) on a per-vehicle basis were almost always higher on motorways compared the other roads studied.
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DOI：
10.3390/s21165337
发表时间：
2021-08-07
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Kotus J;Szwoch G
通讯作者：
Szwoch G
影响因子：
2.9
作者：
Cifuentes, Felipe;Gonzalez, Carlos M.;Aristizabal, Beatriz H.
通讯作者：
Aristizabal, Beatriz H.
影响因子：
9.8
作者：
Ghaffarpasand, Omid;Pope, Francis D.
通讯作者：
Pope, Francis D.
DOI：
10.1016/j.trd.2021.102796
发表时间：
2021-03-21
影响因子：
7.6
作者：
Lan, Ziqin;Cai, Ming
通讯作者：
Cai, Ming
基于高分辨率人口分布和网格级噪声数据的道路交通噪声暴露评估
影响因子：
7.4
作者：
Cai, Ming;Lan, Ziqin;Wang, Haibo
通讯作者：
Wang, Haibo