Road congestion monitoring system based on vehicle feature matrix sequence change analysis

Abstract

The invention discloses a road congestion monitoring system based on vehicle feature matrix sequence change analysis, which relates to the technical field of road traffic and solves a technical problem of traffic condition detection. The road congestion monitoring system based on vehicle feature matrix sequence change analysis comprises a clock driving subsystem GTS, a video information acquisition subsystem CAVS, an initial mark subsystem MS, an image feature extraction subsystem TS, a congestion monitoring analysis subsystem BAS and an alarming subsystem AS; the clock driving subsystem GTS is used for generating a time sequence, the video information acquisition subsystem CAVS is used for capturing the image of a camera area CA according to the received time sequence, and the initial mark subsystem MS is used for segmenting the camera area CA into a plurality of independent area lanes MR; the image feature extraction subsystem TS is used for extracting vehicle features from the image; the congestion monitoring analysis subsystem BAS is used for performing congestion analysis according to the image of the camera area and the segmented area lanes; and the alarming subsystem AS is used for performing early warning timely according to a result of congestion analysis. The system provided by the invention is used for monitoring the road traffic conditions.

Description

technical field [0001] The invention relates to road traffic technology, in particular to a technology of a road congestion monitoring system based on the sequence change analysis of vehicle characteristic matrix. Background technique [0002] At present, with the expansion of the number of vehicles, the problem of urban traffic congestion is becoming more and more serious, which has become an important problem in urban management. In order to solve the traffic congestion problem, the traffic control department needs to monitor the road congestion situation. [0003] The existing road congestion monitoring methods mainly include the following: [0004] 1) Vehicle perception analysis based on electronic induction coils. This method embeds electronic induction coils at key road intersections and main roads to record passing vehicles and then judge vehicle congestion. The main disadvantages of this method are high cost, large construction impact, and easy damage , high mainte...

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Problems solved by technology

[0004] 1) Vehicle perception analysis based on electronic induction coils. This method embeds electronic induction coils at key road intersections and main roads to record passing vehicles and then judge vehicle congestion. The main disadvantages of this method are high cost, large construction impact, and easy damage , high maintenance costs, and weak regional overall judgment ability

[0005] 2) Analysis based on the collection of vehicle GPS information. This method is adopted by Internet map providers, such as Baidu Maps; it judges the vehicle flow speed and vehicle density of the corresponding road section according to the motion information fed back by each user's mobile phone using GPS information navigation; The main disadvantage of this mode is that the positioning accuracy of GPS information cannot distinguish the height and position of the lane and viaduct, and then give a misjudgment

[0006] 3) Video vehicle monitoring based on artificial intelligence. At present, there are many studies in this area, but most of them are road moving vehicle detection, and then realize vehicle counting; the disadvantage of this method is that it cannot distinguish lane information, and cannot accurately perceive vehicle speed, so it cannot be effectively predicted. traffic jam

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