Traffic monitoring method and traffic monitoring apparatus

Abstract

The invention discloses a traffic monitoring method for vehicle locus tracking and collision early warning. The method is realized by use of an intelligent monitoring information hierarchical structure model, and the model comprises an environment perceiving layer, an object layer, a feature layer, a semantic layer and a decision layer. The method comprises the following steps: obtaining a traffic image in real time, and storing the traffic image in the environment perceiving layer; extracting a vehicle image in the traffic image and storing the vehicle image in the object layer; processing the vehicle image in real time by use of a model obtained from a convolutional neural network and an onsite acquisition device with an online learning capability so as to obtain identity information and motion parameters of a vehicle for storing in the feature layer; processing feature parameters to obtain a motion trend of the vehicle and storing the motion trend in the semantic layer; determining whether a vehicle is about to have a collision through a conclusion of the semantic layer; and if it is determined that the vehicle is about to have a collision, an early warning is generated. According to the invention, through preprocessing, learning and identifying the traffic image, whether an accident takes place can be analyzed; and the early warning is generated and correlation personnel is notified. Further disclosed is a traffic monitoring apparatus.

Description

Technical field [0001] The invention relates to traffic monitoring technology, in particular to a traffic monitoring method and a traffic monitoring device for vehicle trajectory tracking and collision warning. The invention belongs to the field of traffic monitoring, machine vision, machine learning, and artificial intelligence. Background technique [0002] With the continuous development of economy and society, the number of vehicles in my country has been increasing year by year, and traffic accidents have also increased year by year. In order to effectively monitor and manage road traffic and reduce the incidence of traffic accidents, traffic monitoring systems based on video technology are widely used in roads at all levels in urban and rural areas. Limited by hardware and software technology, traditional traffic monitoring methods can generally only obtain monitoring videos, but cannot identify and judge possible accidents. This requires monitoring personnel to spend a lo...

AI Technical Summary

Problems solved by technology

Limited by hardware and software technology, traditional traffic monitoring methods can only obtain monitoring videos, but cannot identify and judge possible accidents. Corresponding follow-up work, and real-time, efficient and accurate monitoring cannot be realized, which is not conducive to understanding traffic conditions as soon as possible and handling possible accidents as soon as possible

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