Highway traffic incident detection method based on deep learning

Abstract

The invention discloses a road traffic incident detection method based on deep learning. The method comprises the following steps: obtaining a road traffic vehicle sample data set; processing the sample data set, and dividing the sample data set to obtain a training set and a verification set; an attention module CBAM is added to the original YOLOv5 model, alpha-CIOULoss is used for replacing the original CIOULoss, and an improved YOLOv5-Improved model detection algorithm is obtained; the processed sample data set is input into a YOLOv5-Improved model, and a. Pt weight file after training is obtained; detecting the video test set by using the weight file to obtain target vehicle result information, and inputting the target vehicle result information into a Deepsort target tracking detection algorithm for tracking to obtain specific coordinate information of the vehicle and a vehicle ID; and inputting the event into a pre-written logic algorithm to judge whether the event is a parking or congestion event or not. By adopting the road traffic event detection method based on deep learning, the problem that an existing target detection method is poor in real-time performance and detection precision can be solved.

Description

technical field [0001] The present invention relates to the technical field of traffic event detection, in particular to a deep learning-based highway traffic event detection method. Background technique [0002] With the rapid development of highways, its daily operation also encounters various problems, such as parking on the highway and congestion problems are the top priority. In the early days, it was mainly achieved by strictly controlling the entrances and exits of the expressway, and the traffic police patrolling the expressway. But this consumes manpower and material resources, and the efficiency is also very low. At present, traffic video surveillance systems are common in the market, but these systems are only responsible for collecting video information and transmitting it to the background control room, and do not have the ability to actively identify abnormal behaviors (such as parking, congestion) on the road, and can only be used as an accident. The later v...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a road traffic event detection method based on deep learning, to solve the problem that the existing target detection method has poor real-time performance and detection accuracy, and cannot satisfy the detection of traffic and congestion events on the road

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