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Discrimination method of traffic conflicts at intersections based on real-time vehicle trajectories

A technology of traffic conflict and discrimination method, which is applied in the field of traffic engineering, can solve the problems of inaccurate target detection and poor tracking effect, and achieve the effect of high accuracy

Active Publication Date: 2021-10-26
HEILONGJIANG INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are still many problems in the existing research on the use of video technology to detect traffic conflicts, such as inaccurate target detection, poor tracking effect, etc.

Method used

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  • Discrimination method of traffic conflicts at intersections based on real-time vehicle trajectories
  • Discrimination method of traffic conflicts at intersections based on real-time vehicle trajectories
  • Discrimination method of traffic conflicts at intersections based on real-time vehicle trajectories

Examples

Experimental program
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Effect test

Embodiment 1

[0077] This embodiment relates to the specific process of a method for judging traffic conflicts at intersections based on real-time vehicle trajectories, such as figure 1 Shown:

[0078] Step 1, collecting real-time video image data, and performing image grayscale, median filtering and binarization preprocessing on it;

[0079] Step 2. Establish a video background model according to the mixed Gaussian background model, and extract vehicle targets through morphological filtering;

[0080] Step 3, according to the centroid coordinates of the minimum circumscribed rectangular frame of the extended Kalman filter method, the running track of the vehicle is obtained, and the moving target is tracked;

[0081] Step 4, collecting traffic flow trajectory velocity parameter data at the intersection;

[0082] Step 5. Based on the real-time traffic flow data, create a vehicle traffic conflict discrimination model and a conflict counting method.

Embodiment 2

[0084] combine figure 2 To illustrate this embodiment, take the intersection of Songshan Road and Huaihe Road in Harbin City as an example. Right-turning vehicles at this intersection are not subject to signal restrictions, so there may be traffic conflicts between straight-going and right-turning vehicles.

[0085] In this embodiment, the specific process of preprocessing the image grayscale, median filter and binarization in the above steps is as follows:

[0086] (1) Using the moving average method to grayscale the video image, the formula for converting color pixels to grayscale pixels is:

[0087] GRAY=0.299R+0.587G+0.114B

[0088] In the formula, R, G, B——the red, green, and blue components of the original image;

[0089] For images before and after processing, see Figure 3a and 3b .

[0090] (2) Perform median filtering and denoising processing on the grayscaled image, see Figure 3c , the formula of the two-dimensional median filter is as follows:

[0091] g(x...

Embodiment 3

[0103] combine figure 2 and Figure 4 To illustrate this embodiment, in this embodiment, the above step 2 establishes a video background model according to the mixed Gaussian background model, and the specific process of extracting the vehicle target through morphological filtering is as follows:

[0104] (1) Use the mixed Gaussian distribution model to establish the background model of the video, and perform background difference to extract the vehicle image. The steps are as follows:

[0105] Step A, initializing K groups of Gaussian models;

[0106] The pixel X in the current frame is differentiated from K models respectively. If the difference result of the i-th group is less than the threshold value (generally 2.5σ), it is called pixel X t , matches with the i-th group of Gaussian models, otherwise it is called mismatch;

[0107] Step B, update the weight, the update formula is:

[0108] ω i,t =(1-a)ω i,t-1 +M i,t a

[0109] where a is the update rate, when the p...

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Abstract

The invention relates to a method for discriminating traffic conflicts at intersections based on real-time vehicle trajectories, comprising the following steps: step 1, collecting real-time video image data, and performing preprocessing of image grayscale, median filtering and binarization; step 2. Establish a video background model according to the mixed Gaussian background model, and extract the vehicle target through morphological filtering; Step 3, obtain the running track of the vehicle and track the moving target according to the centroid coordinates of the smallest circumscribed rectangular frame of the extended Kalman filter method; Step 4. Collect traffic flow trajectory velocity parameter data at the intersection; Step 5. Create a traffic conflict discrimination model and a conflict counting method for vehicles based on real-time traffic flow data. The invention provides a traffic conflict discrimination and counting method based on a video-based vehicle running track, which can detect and count traffic conflicts at intersections in real time, and is more efficient and accurate. Compared with the number of traffic conflicts obtained by the manual counting method, the accuracy is higher high.

Description

technical field [0001] The invention belongs to the field of traffic engineering, in particular to a method for judging traffic conflicts at intersections based on real-time vehicle trajectories. Background technique [0002] As an important part of the road system, level intersections have many traffic safety risks due to large traffic volume, many conflict points, large blind spots, and the gathering point of traffic flow in all directions. At present, the collection method of traffic conflicts is mainly through manual observation, which is poor in real-time and time-consuming and laborious, and the collected information is not accurate enough. With the development of intelligent transportation technology, it is possible to use video detection technology to discriminate and count traffic conflicts. However, there are still many problems in the existing research on traffic conflict detection system using video technology, such as inaccurate target detection and poor tracki...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G06T7/20G06T7/136
CPCG06T7/20G06T2207/10016G06T2207/20032G06T2207/30236G06T2207/30241G06T2207/30248G08G1/0104G08G1/0125G06T7/136
Inventor 吴丽娜慈玉生尹必清韩应轩吴海龙
Owner HEILONGJIANG INST OF TECH
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