Abnormal S-type driving warning method based on binocular vision lane marking detection

Abstract

The invention discloses an abnormal S-type driving warning method based on binocular vision lane marking detection. Through the method, a driven S-type route of a vehicle can be determined by analyzing the video images collected from the front and side looking directions and then the driver is warned in the manner of voice or lighting lamp. The method of the invention indirectly judges the driving state of the driver and has no influence on the driving state of the driver, therefore being capable to efficiently prevent car accidents.

Description

technical field [0001] The present invention relates to an auxiliary driving technology on roads with good marking lines, in particular to an abnormal S-shaped driving warning based on binocular vision lane line detection that improves the safety of car driving and even the safety of the entire road system method. Background technique [0002] Ergonomics studies have shown that traffic accidents occur when instability or imbalance occurs in the human-vehicle-environment system. The direct or indirect causes of road traffic accidents include people, vehicles, roads and various environmental factors. One of the main causes of major traffic accidents is the vehicle deviating from the lane due to fatigue driving, drunk driving, and other driving errors caused by inattentive driving. According to the estimate of the (U.S.) Federal Highway Administration, 44% of all fatal traffic accidents in the U.S. in 2002 were related to lane departure driving. At the same time, driving acr...

AI Technical Summary

Problems solved by technology

[0003] At present, some scholars conduct lane line recognition research on structured expressways, respectively using curve fitting method, Hough transform method, inverse projection projection transformation lane line detection method, etc., but because the above methods are all processing grayscale images, image The preprocessing is complicated, other factors interfere too much with the extraction of lane lines, and the accuracy of lane line extraction is low

In the decision-making of lane departure and lane line warning, most of them adopt the strategy of warning once lane departure, which may cause false alarms and cannot reflect the current driving state of the driver well; S” type driving detection and early warning can ideally reflect whether the driver is currently in an abnormal driving state, so as to detect potential safety hazards in time and effectively avoid traffic accidents

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