Lane line trajectory prediction method, device and equipment and storage medium
By using a lane trajectory prediction method based on convolutional neural networks, and employing pseudo-image processing technology, feature extraction modules, and vector fusion weighting modules, the problem of low lane trajectory prediction accuracy in AR HUD is solved, achieving high-precision and engineering-simple lane trajectory prediction.
CN116863423BActive Publication Date: 2026-05-26WUHAN HANGSHENG AUTOMOTIVE ELECTRONICS CO LTD +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WUHAN HANGSHENG AUTOMOTIVE ELECTRONICS CO LTD
- Filing Date
- 2023-06-12
- Publication Date
- 2026-05-26
Smart Images
Figure CN116863423B_ABST
Abstract
The application discloses a lane line trajectory prediction method and device, equipment and a storage medium, and the method comprises the steps of acquiring lane line information to be predicted; based on the acquired lane line information to be predicted, sampling the lane line to be predicted, and splicing the sampling points into a pseudo image; inputting the pseudo image into a pre-trained convolutional neural network model for prediction to obtain a lane line trajectory prediction result, wherein the convolutional neural network model is obtained by training a model based on a convolutional neural network and in combination with a feature extraction module and a vector fusion weighting module. The lane line trajectory prediction algorithm based on the convolutional neural network (CNN) mainly converts lane line trajectory information into a pseudo image for processing, and improves the ordinary convolutional neural network, so that the algorithm is not only high in accuracy but also simple in engineering.
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