A lane line tracking method based on a Kalman filter

Abstract

The invention relates to a lane line tracking method based on a Kalman filter. The method comprises the steps of initializing a counter; inputting lane lines obtained through Hough conversion detection at the moment k; brining Lane lines at k moments one by one with k- Matching the lane lines at the moment 1, and respectively calculating the deviation of the parameters at the two moments; updatingby matching with a counter; when the linear matching number is not smaller than the counter, starting a Kalman filter to track the lane line; otherwise, not tracking; and after 10 frames of lane lines are tracked, detecting and updating a straight line library again. According to the method, the problem that lane lines of one or more frames of images in a complex environment are missed or cannotbe detected is solved; a method for replacing a detection value with the estimation value is provided, the lane line detection stability is improved, when lane line detection of a plurality of framesof images fails, the estimation value can still be used for replacing the detection value for output, the lane line detection method is high in robustness and accurate in detection result, and the driving safety is improved.

Description

technical field [0001] The invention belongs to the technical field of vehicle engineering, and in particular relates to a lane line tracking method based on a Kalman filter. Background technique [0002] During the lane line detection process, the lane line video or image sequence captured by the on-board camera changes continuously over time. The existing lane tracking algorithm based on a single frame image will face many challenges, such as complex and changeable road environment, excessive curvature of lane lines and noise. In addition, the lack of lane line features, lane line defects or occlusions, and lane changes may lead to detection failures. In the process of lane line detection, the complex and changeable road environment, the lack of lane line features, the defect or cover of lane lines, etc. may easily cause one or several frames of image detection to fail, resulting in detection failure, and the robustness of the lane line detection algorithm is not good. p...

AI Technical Summary

Problems solved by technology

The existing lane tracking algorithm based on a single frame image will face many challenges, such as complex and changeable road environment, excessive curvature of lane lines and noise, etc.

In addition, the lack of lane line features, lane line defects or occlusions, and lane changes may lead to detection failures

In the process of lane line detection, the complex and changeable road environment, the lack of lane line features, the defect or cover of lane lines, etc. may easily cause one or several frames of image detection to fail, resulting in detection failure, and the robustness of the lane line detection algorithm is not good. powerful

The lane line tracking method in the prior art is prone to detection failures, and the detection results are inaccurate, which cannot well meet the needs of practical applications. Now it is urgent to develop a new lane line tracking method that can overcome the above technical defects

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