Vehicle shift inspection method and apparatus

Abstract

The invention relates to a checking method and a device of automobile deviation, wherein the method is mainly an image identification and processing procedure, wherein the image identification and processing procedure comprises the following steps: an image acquisition step which comprises utilizing an image pick-up device to extract image picture data, and a lane line identification step which comprises analyzing image picture data, distinguishing a lane line position, utilizing a quadratic curve to fit an equation, connecting a segmental lane line, and making a lane line predicating model, wherein the lane line predicating module which is got through utilizing the above steps is used to check automobile deviation, and is supplied for warning. The checking method of automobile deviation mainly comprises an image pick-up device which is used to extract road image information, a calculating platform which is used to analyze the road image information extracted by the image pick-up unit, and judges the corresponding relationship of a current automobile and a road, and a signal outlet unit which utilizes light, visual variation or sound to reach the behavior of warning. The invention can give off warning to prompt a driver to pay attention and reach the behavior of warning when an automobile does not normally run.

Description

technical field [0001] The invention relates to a detection method and device for vehicle deviation. Background technique [0002] With the popularization and widespread use of vehicles in human society, the gap between different regions has been shortened, and it has gradually become a globalized social form. However, in recent years, traffic accidents have caused an endless stream of casualties. Therefore, advanced countries and major car manufacturers are actively seeking how to apply technology. on the vehicle to improve the safety of the vehicle and reduce the incidence of traffic accidents; [0003] In the occurrence of traffic accidents, human factors often account for the majority, and fatigue and distraction are often the main causes of accidents. Although relevant institutions at home and abroad are working on drowsiness detection, brain waves and other related research to remind drivers, the effect is not as good as Satisfactory, coupled with system response time...

AI Technical Summary

Problems solved by technology

[0006] However, this prior art is to compare the road markings with the driving path to confirm whether the vehicle has deviated from the normal track; however, this method of comparison is not foolproof, and there is still the possibility of misjudgment due to differences in the comparison. In addition, the actual road markings and driving routes have not been estimated and calculated by trajectory, which is prone to actual deviation, sending wrong warnings, or sending warnings too late, which is not conducive to actual use

Images