Urban road traffic condition detection method based on voting of network sorter
A technology of road traffic and traffic status, applied in traffic flow detection, neural learning methods, biological neural network models, etc., can solve problems such as poor accuracy, and achieve the effect of improving detection accuracy
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[0043] The present invention will be further described below in conjunction with the accompanying drawings.
[0044] refer to Figure 1 ~ Figure 3 , an urban road traffic state detection method that integrates SVM and BP neural network. The traffic characteristic parameters mainly include vehicle average speed, traffic volume, vehicle time occupancy rate, etc. There are many methods for traffic parameter detection, mainly including ultrasonic detection, infrared detection, ring induction loop detection, and computer vision detection. Ultrasonic detection accuracy is not high, it is easily affected by vehicle occlusion and pedestrians, and the detection distance is short (generally no more than 12m). Infrared detection is affected by the heat source of the vehicle itself, the ability to resist noise is not strong, and the detection accuracy is not high. The ring sensor has high detection accuracy, but it is required to be installed in the civil structure of the road surface, ...
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