Vehicle incident detection method on mountainous expressway based on dual-view learning

Abstract

The invention provides a double-perspective learning-based mountainous area highway vehicle event detection method used for intelligent traffic monitoring. According to the double-perspective learning-based mountainous area highway vehicle event detection method, based on two mutually-independent perspectives, namely, moving object spatial-temporal trajectory mode learning and epipolar plane map-based vehicle moving state analysis, respective independent behaviors of vehicles and overall characteristics of traffic section vehicle flow are detected; the two kinds of characteristics are utilized to detect events such as traffic accidents, traffic congestion, vehicle retrograde travelling and illegal parking; decision level fusion judgment is carried out through correlation processing; a joint inference result can be obtained; and therefore, robustness detection of mountainous area highway vehicle events under a double-perspective fusion framework can be completed. As indicated by experiment results, the detection method has the advantages of low complexity, high real-time performance and excellent performance in terms of a variety of traffic events.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic monitoring and traffic event detection based on image processing, and in particular relates to a method for detecting vehicle events on mountainous highways based on dual-view learning. Background technique [0002] With the implementation of the great development strategy in the west of our country, the mountainous highways connecting remote areas have developed rapidly. The mountainous expressway has the characteristics of ensuring continuous driving and large traffic capacity. It meets the needs of rapid flow of people and goods, realizes the improvement of the overall level of traffic, and improves the social benefits of traffic. Due to the high design capacity of mountainous expressways and their greater traffic attraction, the traffic volume of certain bottleneck sections of some mountainous expressways has gradually reached saturation, and various traffic incidents have increase...

AI Technical Summary

Problems solved by technology

Like computer vision, pattern recognition, and information retrieval, all kinds of highway traffic events belong to high-level semantic content, and there is inevitably a semantic gap problem, which cannot be fully and accurately expressed by simple low-level features

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