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隧道建设(中英文) ›› 2019, Vol. 39 ›› Issue (12): 1957-.DOI: 10.3973/j.issn.2096-4498.2019.12.005

• 研究与探索 • 上一篇    下一篇

基于麦克风阵列车辆检测的公路隧道照明控制方法及系统研究

黎  恒, 杨玉琳, 陈大华, 韦泽贤, 王玲容, 唐文娟   

  1. (广西交通科学研究院有限公司, 广西 南宁  530007)
  • 收稿日期:2019-08-08 出版日期:2019-12-20 发布日期:2019-12-20
  • 作者简介:黎恒(1982—),男,广西北流人,2016年毕业于西安电子科技大学,测试计量技术及仪器专业,博士,工程师,现从事音频信号处理、交 通机电设备研发工作。 E-mail: 59150601@qq.com。
  • 基金资助:

    广西科技计划项目(桂科AB17292006); 南宁市科学研究与技术开发计划项目(20183044-2)

Lighting Control Method and System for Highway Tunnel Based on Microphone Array Vehicle Detection

LI Heng, YANG Yulin, CHEN Dahua, WEI Zexian, WANG Lingrong, TANG Wenjuan   

  1. (Guangxi Transportation Research & Consulting Co., Ltd., Nanning 530007, Guangxi, China)
  • Received:2019-08-08 Online:2019-12-20 Published:2019-12-20

摘要:

: 针对雷达、视频、感应线圈等车辆感知装置难以同时满足低成本、高精度、易安装维护的问题,提出基于麦克风阵列车辆检测 的公路隧道照明节能方法及系统研究,实现精准照明节能。 具体方案包括: 1)采用成本较低、非地埋的基于麦克风阵列车辆检测 装置替代已有接触式感知技术; 2)在音频装置中,通过改进的MVDR算法对麦克风阵列拾取到的信号进行降噪去混响,并融合基 于卷积神经网络交通事件识别方法,实现隧道内精细、分段车辆感知; 3)提出基于环境传感的多信息协同控制方法,根据环境与隧 道内车辆行驶信息,进行无级调光控制器多信息联动,智能调节隧道内灯照明亮度与时长。 试验分析表明,提出的基于麦克风阵列 音频车检技术单独事件检测精度高于98%,混合事件检测精度高于95%。 工程实践表明,与常规LED无级调光隧道节能技术相 比,该技术使隧道综合能耗降低约20%,极大地降低了安装维护成本,具有很好的应用价值。

关键词: 麦克风阵列, MVDR算法, 卷积神经网络, 智能控制, 隧道照明节能

Abstract:

: The radar, video, induction coil, etc. are generally used for vehicle perception of conventional tunnel lighting energy-saving technology, which cannot meet the requirements of low cost, high precision and easy installation and maintenance. Therefore, a method and system with precision lighting for energy-saving of highway tunnel lighting based on microphone array vehicle detection is proposed. The specific schemes include: (1) The existing contact sensing technology is replaced by low-cost and non-buried vehicle detection device based on microphone array. (2) The improved MVDR algorithm is used to de-noise and de-reverberate the signals picked up by microphone array in audio devices, and the accurate and sectioned vehicle sense in tunnel is realized based on the convolutional neural networkbased traffic incident recognition method. (3) A multi-information cooperative control method based on environmental sensing is proposed, which intelligently adjusts the illumination brightness and time of the tunnel lights by multiinformation linkage of stepless dimming controller according to the environment and vehicle driving information in the tunnel. The experimental analysis shows that the proposed microphone array audio vehicle detection technology has a detection accuracy of more than 98% for single event and a detection accuracy of more than 95% for mixed events. The engineering practice shows that the comprehensive energy consumption of system mentioned-above is 20% less than that of conventional LED stepless dimming technology, it is worth popularizing.

Key words: microphone array, MVDR algorithm, convolutional neural network, intelligent control, energy saving of tunnel lighting

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