Traffic jam monitoring forecast method based on macroscopic traffic flow model with dissipation item
A macro-traffic flow and traffic congestion technology, applied in the direction of traffic flow detection, etc., can solve the problem that traffic congestion cannot be predicted in time
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[0032] 1. When obtaining the vehicle speed, density and flow information through the video images of the surveillance cameras, considering that the actual surveillance cameras work at the intersection all the year round, it is impossible to manually correct the image processing algorithm, according to the comprehensive error performance index of the whole process of image processing as follows Choose an image processing algorithm:
[0033] min(e z )=min{e para {e seg [e pre (e samp )]}}
[0034] =k samp k pre k seg e para
[0035] In the formula, e z The overall error of extracting traffic parameters for the image, min(e z ) is e obtained by selecting different combinations of image processing methods z minimum value, e samp is the image sampling error, e pre is the image and processing error, e seg is the vehicle segmentation error in the image, e para is the error of extracting traffic parameters according to the segmented image, k samp >1 is the image sampl...
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