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

Inactive Publication Date: 2013-04-10
XIAN FEISIDA AUTOMATION ENG
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Problems solved by technology

[0020] In order to overcome the technical defect that the Burgers traffic flow model is difficult to directly monitor and predict traffic jams, the present invention provides a traffic jam monitoring and forecasting method based on a macroscopic traffic flow model with dissipation items. The method obtains vehicle speed, Density and flow information, according to the newly established traffic congestion model to predict the traffic congestion that will occur, and solve the technical problem that traffic congestion cannot be predicted in time

Method used

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  • Traffic jam monitoring forecast method based on macroscopic traffic flow model with dissipation item
  • Traffic jam monitoring forecast method based on macroscopic traffic flow model with dissipation item
  • Traffic jam monitoring forecast method based on macroscopic traffic flow model with dissipation item

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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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Abstract

The invention provides a traffic jam monitoring forecast method based on a macroscopic traffic flow model with a dissipation item, and aims to overcome the technical defect that the existing traffic flow model is difficult to directly monitor and forecast traffic jams. The method obtains vehicle speed, density and flow information through video images of a monitoring camera, and forecasts traffic jams which will occur according to the newly established traffic jam model to solve the technical problem that the traffic jams cannot be forecasted in time.

Description

technical field [0001] The invention relates to a modeling method, in particular to a traffic congestion monitoring and forecasting method based on a macroscopic traffic flow model with dissipation items. Background technique [0002] Transportation is a major issue closely related to the national economy and people's livelihood. Establishing a smooth and well-developed transportation network is an established goal of national development. The degree of modernization of the transportation system and the advanced degree of traffic management are important symbols for measuring the modernization of a country; therefore, transportation, especially road transportation, is subject to The governments of various countries have attached great importance to it, and it has developed rapidly in recent years; whether the traffic is smooth or not has an important impact on the development of the urban economy, people's quality of life, and the international reputation of the region and t...

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Application Information

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IPC IPC(8): G08G1/01
Inventor 史忠科
Owner XIAN FEISIDA AUTOMATION ENG
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