Highway vehicle behavior semantic analysis and abnormal behavior monitoring system and method

Abstract

The invention belongs to the technical field of a transport control system of road vehicles, and discloses a highway vehicle behavior semantic analysis and abnormal behavior monitoring system and method. By detecting a video and and tracking a moving vehicle target, vehicle speed detection and vehicle behavior semantic analysis are achieved, whether a vehicle has traffic offence behaviors or not is judged, and then the function of alarming the traffic offence behaviors is achieved; a multi-hybrid Gaussian model is utilized to detect the moving target from the video, a Kalman filter is utilizedto track the moving vehicle target to obtain the track in the vehicle driving process and three major motion characteristics, namely, the position, the direction and the speed, detection is conducted, the vehicle behavior semantic analysis is conducted, through the further utilization of a road driving regulation, whether the vehicle has the traffic offence behaviors or not is judged, and if yes,the vehicle is snapshot and alarmed. Vehicle driving and semantic analysis can be accurately detected in real time in a highway, abnormal behaviors and the traffic offence behaviors of the vehicle are alarmed and snapshot, and the purposes of automatic detection, quick alarming and timely processing are achieved.

Description

technical field [0001] The invention belongs to the technical field of road vehicle traffic control systems, and in particular relates to a system and method for expressway vehicle behavior semantic analysis and abnormal behavior monitoring. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: With the continuous development of society, automobiles have gradually become an indispensable means of transportation in people's lives. While automobiles bring great convenience to people's daily travel, they also bring a series of problems such as traffic congestion and traffic accidents. Especially the rapid development of expressway construction, driving speed is getting faster and faster, the phenomenon of continuous collision of multiple vehicles often occurs, and most of the serious traffic accidents that cause many deaths occur on the expressway, which has caused serious damage to people's lives and property. seriou...

AI Technical Summary

Problems solved by technology

[0005] (1) At present, various expressway monitoring systems emerge in endlessly. Most of the systems have single functions and can detect vehicles and monitor traffic flow. The data is simply transmitted and displayed without data processing, so it takes a lot of money of labor costs are on monitoring

A system that can detect abnormal vehicle behavior, but cannot capture the vehicle and automatically detect and recognize the license plate number, requires labor costs and is not smart enough

[0006] (2) Intelligent vehicle behavior recognition and analysis, usually using deep learning and other methods for detection and recognition, the detection and recognition speed is not fast enough to achieve real-time results

[0007] (3) Vehicle positioning adopts a simple edge detection algorithm, or uses the color characteristics of the license plate (generally the background color of the license plate is blue or yellow), in complex environments, or when the background color of the license plate is other colors, it cannot be accurately positioned. It is also impossible to perform subsequent license plate segmentation and license plate recognition

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