The invention discloses a machine learning-based traffic flow intelligent monitoring control system comprising a computer terminal which is communicated with a virtual coil video detection unit, a ground induction traffic flow detection unit and a radar traffic flow detection unit. The virtual coil video detection unit, the ground induction traffic flow detection unit and the radar traffic flow detection unit are all communicated with a function control main unit. Through the comprehensive advantages of video detection, radar vehicle detection and ground induction vehicle detection, a signal lamp timing strategy is optimized in a machine learning mode, timing is more efficient when multiple detection technologies are used at the same time; when one detection technology breaks down, wrong data generated by the fault detection technology can be automatically judged and eliminated, and wrong timing cannot occur.
本发明公开了一种机器学习的车流量智能监测控制系统,包括计算机终端,计算机终端分别与虚拟线圈视频检测单元、地感车流量检测单元以及雷达车流量检测单元连通,虚拟线圈视频检测单元、地感车流量检测单元以及雷达车流量检测单元均与功能控制总单元连通。通过视频检测、雷达车检、地感车检的综合优势,利用机器学习的方式优化信号灯配时策略,多种检测技术同时使用时配时更高效,一种检测技术故障时,可自动判断并排除故障的检测技术所生成的错误数据,不会出现错误的配时。
Machine learning-based traffic flow intelligent monitoring control system
一种机器学习的车流量智能监测控制系统
2020-12-04
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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