使用智能声学传感器 (交通耳朵) 和车辆远程数据的交通噪音评估
Omid Ghaffarpasand1, Anwar Almojarkesh2, Sophie Morris3
1School of Geography, Earth, and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
交通耳,一个声学传感器,通过分析发动机噪音和图像,准确地识别车辆类型和燃料. 这项技术使新的交通噪声评估成为可能,在高峰时段显著降低噪声.
科学领域:
- 环境声学环境声学
- 运输工程 运输工程 运输工程
- 机器学习应用程序 机器学习应用程序
背景情况:
- 交通噪音污染是一个重要的环境问题.
- 准确的车辆分类和燃料类型识别对于噪音和排放评估至关重要.
- 现有的交通监控方法可能是侵入性的或缺乏详细的声学数据.
研究的目的:
- 推出交通耳朵,一种用于非侵入性交通监控的新型声学传感器系统.
- 用声音和图像分析来评估交通耳朵在分类车辆类型和燃料方面的准确性.
- 开发和应用一种新的自下而上的方法来评估使用交通耳朵数据和城市移动地图的交通噪声.
主要方法:
- 开发一个声学传感器包 (交通耳朵),集成麦克风和计算机视觉摄像头.
- 声波分析,图像处理和机器学习算法的应用,用于车辆类别和速度估计.
- 交通耳朵数据与自动识别车牌 (ANPR) 摄像头数据进行验证.
- 整合交通耳声噪声分析与城市流动 (GeoSTMUM) 的地理空间和时间映射数据进行噪声评估.
主要成果:
- 交通耳和ANPR之间在车辆类型和燃料确定方面达成高度一致 (1-4%的不确定性).
- 在西米德兰,英国,在高峰时间减少8%以上的交通发动机噪音的演示.
- 对交通噪音的显著工作日-周末影响的量化,几乎将好处减半.
- 观察到高速公路上的交通噪声因子 (dB/m) 与其他道路类型相比始终更高.
结论:
- 交通耳朵为车辆声学监测提供了一种准确而非侵入性的方法.
- 开发的自下而上的评估方法有效地使用集成数据源量化交通噪音影响.
- 调查结果强调了减少交通噪音策略的潜力,以及需要考虑道路类型和周日等因素的必要性.
相关概念视频
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