Ghaffarpasand Omid, Almojarkesh Anwar, Morris Sophie, Stephens Elizabeth, Chalabi Alaa, Almojarkesh Usamah, Almojarkesh Zenah, Pope Francis D
School of Geography, Earth, and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK.
Innovation Factory Limited, Birmingham B7 4BP, UK.
Sensors (Basel). 2023 Aug 5;23(15):6964. doi: 10.3390/s23156964.
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.
在此，我们介绍“交通耳”，这是一种声学传感器组件，能够在不干扰交通流的情况下确定每辆过往车辆的发动机噪音。该设备由一组麦克风与一台计算机视觉摄像头组成。利用声波分析、图像处理和机器学习算法来估计过往车辆的类别和速度。我们将通过“交通耳”传感器估算出的交通构成与使用自动车牌识别（ANPR）摄像头记录的交通构成进行了比较，发现两种确定车辆类型和燃料的方法之间具有高度一致性，不确定性为1%-4%。我们还开发了一种新的自下而上的评估方法，该方法利用“交通耳”传感器提供的噪音分析以及使用城市机动性地理空间和时间映射（GeoSTMUM）方法生成的详细城市机动性地图。它被应用于在英国西米德兰兹地区道路上行驶的车辆。结果表明，在整个研究道路上，高峰时段交通发动机噪音的降低幅度超过8%，而工作日-周末效应的恶化效应几乎达到一半。与其他研究道路相比，高速公路上每辆车的交通噪音因素（分贝/米）几乎总是更高。
