Efficient and real-time lane detection using CUDA-based implementation

Lane detection is an essential component of autonomous driving systems, enabling vehicles to accurately identify and follow road markings. In this paper, we look at an lane detection approach that integrates median filtering and the Hough transform. Median filtering is an essential pre-processing st...

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Main Authors: El Boussaki Hoda, Latif Rachid, Saddik Amine
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:ITM Web of Conferences
Online Access:https://www.itm-conferences.org/articles/itmconf/pdf/2024/12/itmconf_maih2024_01007.pdf
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author El Boussaki Hoda
Latif Rachid
Saddik Amine
author_facet El Boussaki Hoda
Latif Rachid
Saddik Amine
author_sort El Boussaki Hoda
collection DOAJ
description Lane detection is an essential component of autonomous driving systems, enabling vehicles to accurately identify and follow road markings. In this paper, we look at an lane detection approach that integrates median filtering and the Hough transform. Median filtering is an essential pre-processing step for reducing noise and improving lane detection accuracy. However, given its high computational demands, optimization of this process is essential for real-time applications. To this end, we used CUDA for acceleration, taking advantage of its parallel computing capabilities to improve performance. We implemented and tested this optimised lane detection algorithm on the NVIDIA Jetson Nano and on a desktop, providing a comparative analysis of improvements in efficiency and speed. This approach highlights the potential of real-time path detection in embedded and high-performance computing environments.
format Article
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institution Kabale University
issn 2271-2097
language English
publishDate 2024-01-01
publisher EDP Sciences
record_format Article
series ITM Web of Conferences
spelling doaj-art-83fc298ac73541c2bbf54b1c2a3c79ee2025-01-08T10:58:54ZengEDP SciencesITM Web of Conferences2271-20972024-01-01690100710.1051/itmconf/20246901007itmconf_maih2024_01007Efficient and real-time lane detection using CUDA-based implementationEl Boussaki Hoda0Latif Rachid1Saddik Amine2Laboratory of Systems Engineering and Information Technology LISTI, ENSALaboratory of Systems Engineering and Information Technology LISTI, ENSALaboratory of Systems Engineering and Information Technology LISTI, ENSALane detection is an essential component of autonomous driving systems, enabling vehicles to accurately identify and follow road markings. In this paper, we look at an lane detection approach that integrates median filtering and the Hough transform. Median filtering is an essential pre-processing step for reducing noise and improving lane detection accuracy. However, given its high computational demands, optimization of this process is essential for real-time applications. To this end, we used CUDA for acceleration, taking advantage of its parallel computing capabilities to improve performance. We implemented and tested this optimised lane detection algorithm on the NVIDIA Jetson Nano and on a desktop, providing a comparative analysis of improvements in efficiency and speed. This approach highlights the potential of real-time path detection in embedded and high-performance computing environments.https://www.itm-conferences.org/articles/itmconf/pdf/2024/12/itmconf_maih2024_01007.pdf
spellingShingle El Boussaki Hoda
Latif Rachid
Saddik Amine
Efficient and real-time lane detection using CUDA-based implementation
ITM Web of Conferences
title Efficient and real-time lane detection using CUDA-based implementation
title_full Efficient and real-time lane detection using CUDA-based implementation
title_fullStr Efficient and real-time lane detection using CUDA-based implementation
title_full_unstemmed Efficient and real-time lane detection using CUDA-based implementation
title_short Efficient and real-time lane detection using CUDA-based implementation
title_sort efficient and real time lane detection using cuda based implementation
url https://www.itm-conferences.org/articles/itmconf/pdf/2024/12/itmconf_maih2024_01007.pdf
work_keys_str_mv AT elboussakihoda efficientandrealtimelanedetectionusingcudabasedimplementation
AT latifrachid efficientandrealtimelanedetectionusingcudabasedimplementation
AT saddikamine efficientandrealtimelanedetectionusingcudabasedimplementation