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Authors: Chun-Ke Chang 1 and Huei-Yung Lin 2

Affiliations: 1 Department of Electrical Engineering, National Chung Cheng University, Chiayi 621, Taiwan ; 2 Department of Electrical Engineering and Advanced Institute of Manufacturing with High-tech Innovations, National Chung Cheng University, Chiayi 621, Taiwan

Keyword(s): Advanced Driver Assistance System, Lane Detection, Convolutional Neural Network.

Abstract: With the advances of driver assistance technologies, more and more people begin to pay attentions on traffic safety. Among various vehicle subsystems, the lane detection module is one of the important parts of advanced driver assistance system (ADAS). Traditional lane detection techniques use machine vision algorithms to find straight lines in road scene images. However, it is difficult to identify straight or curve lane markings in complex environments. This paper presents a lane detection technique based on the deep neural network. It utilizes the 3D convolutional network with the incorporation of temporal information to the network structure. Two well-known lane detection network structures, PINet and PolyLaneNet, are improved by integrating 3D ResNet50. In the experiments, the accuracy is greatly improved for the applications to a variety of different complex scenes.

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Paper citation in several formats:
Chang, C. and Lin, H. (2022). A Vision-based Lane Detection Technique using Deep Neural Networks and Temporal Information. In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-573-9; ISSN 2184-495X, SciTePress, pages 172-179. DOI: 10.5220/0010973200003191

@conference{vehits22,
author={Chun{-}Ke Chang. and Huei{-}Yung Lin.},
title={A Vision-based Lane Detection Technique using Deep Neural Networks and Temporal Information},
booktitle={Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2022},
pages={172-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010973200003191},
isbn={978-989-758-573-9},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - A Vision-based Lane Detection Technique using Deep Neural Networks and Temporal Information
SN - 978-989-758-573-9
IS - 2184-495X
AU - Chang, C.
AU - Lin, H.
PY - 2022
SP - 172
EP - 179
DO - 10.5220/0010973200003191
PB - SciTePress

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