Traffic jam analysis method based on millimeter wave radar and video detection

A millimeter-wave radar, traffic congestion technology, applied in the traffic control system of road vehicles, traffic flow detection, traffic control system, etc., can solve the problems of complex models, difficult to understand for non-professionals, etc., to improve road conditions and improve robustness and accuracy, and the effect of improving the efficiency of citizens' travel

Active Publication Date: 2021-07-09
WUHAN UNIV
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Problems solved by technology

The above-mentioned models are relatively complex, and it is difficult for non-professionals to understand intuitively, so an intuitive, reasonable and efficient congestion analysis model is needed

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  • Traffic jam analysis method based on millimeter wave radar and video detection
  • Traffic jam analysis method based on millimeter wave radar and video detection
  • Traffic jam analysis method based on millimeter wave radar and video detection

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Embodiment Construction

[0063] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0064] Such as figure 1 As shown, the present invention provides a traffic congestion analysis method based on millimeter wave radar and video detection, comprising the following steps:

[0065] Step 1. Use video images to obtain road information and vehicle quantity information, including the number of lanes in the field of view, the length of each lane, the number of vehicles in the field of view, and the length of each vehicle. Calculate the lane space occupancy rate based on the length of each vehicle and the length of the lane , calculate the vehicle group density by the number of lanes, the length of each lane, and the number of vehicles;

[0066] The cameras installed around the monitoring road collect vehicle image information in the field of view l, extract vehicle feature contours, calibrate the position of the vehi...

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Abstract

The invention discloses a traffic jam analysis method based on millimeter wave radar and video detection. A video monitoring camera is used for obtaining road images in a view field, recognizing vehicle movement conditions, measuring data such as the number of vehicles and lanes in the view field, a millimeter-wave radar is used for detecting vehicle positions and vehicle running speeds, road congestion indexes are calculated through obtained traffic flow data, quantitative parameters of the congestion degree are obtained, and furthermore, the traffic jam condition is analyzed. The traffic jam degree is analyzed according to the traffic flow data, the road condition is evaluated intelligently and quickly in real time, the guidance and evacuation of traffic jam are facilitated, the road condition is improved, and the travel efficiency of citizens is improved.

Description

technical field [0001] The invention belongs to the field of traffic road condition supervision, in particular to a traffic congestion analysis technology based on radar signals and machine vision. Background technique [0002] At present, there are many road traffic congestion analysis technologies based on video images at home and abroad. This technology can be divided into two parts, one is the extraction of traffic flow parameters based on video images, and the other is traffic congestion analysis based on traffic flow parameters. A lot of research has been done on the two parts at home and abroad, but there are not many studies on the combination of the two parts, and the traffic flow parameters to evaluate the degree of traffic congestion are more extracted from the video shot by the fixed traffic camera or from the coil Extraction from sensor detection equipment or computer software simulation. [0003] Based on traffic video congestion analysis, foreign research mai...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G08G1/017G08G1/04G08G1/052
CPCG08G1/0104G08G1/017G08G1/04G08G1/052
Inventor 王力行颜思睿黄玉春孟小亮陈江伟谢烁红
Owner WUHAN UNIV
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