Fast-ICA Based Lane Detection Method for Autonomous Vehicles

Fast-ICA Based Lane Detection Method for Autonomous Vehicles

Lane detection is an important process in autonomous vehicle systems. Noise in the image, such as object shadows and terminating lane lines, make lane detection difficult. This study proposes a Convolutional Neural Network architecture with a dimension reduction method that has not been used before...

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Bibliographic Details
Published in:2022 26th International Conference Electronics pp. 1 - 6
Main Authors: Dogru, Hasibe Busra, Zengin, Aydin Tarik
Format: Conference Proceeding
Language:English
Published: IEEE 13-06-2022
Subjects:
Autonomous vehicles
Deep learning
Independent component analysis
Lane detection
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Summary:Lane detection is an important process in autonomous vehicle systems. Noise in the image, such as object shadows and terminating lane lines, make lane detection difficult. This study proposes a Convolutional Neural Network architecture with a dimension reduction method that has not been used before in lane detection. The proposed method has been tested with the open-source TuSimple dataset. The results showed that the proposed Fast-Independent Component Analysis based model training improved performance in lane detection and reduced the mean percent error by 42.2%.
DOI:10.1109/IEEECONF55059.2022.9810405