Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminals

Container terminal automation offers many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A novel lane detection method is proposed using score-based generative modeling through stochastic differ...

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Main Authors: Ngo Quang Vinh, Hwan-Seong Kim, Le Ngoc Bao Long, Sam-Sang You
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/11/4/731
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author Ngo Quang Vinh
Hwan-Seong Kim
Le Ngoc Bao Long
Sam-Sang You
author_facet Ngo Quang Vinh
Hwan-Seong Kim
Le Ngoc Bao Long
Sam-Sang You
author_sort Ngo Quang Vinh
collection DOAJ
description Container terminal automation offers many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A novel lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure fast and accurate lane positioning. A robust lane detection method can deal with complicated detection problems in realistic road scenarios. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions; in addition, the robustness of the lane detection method with stochastic noise is tested.
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spelling doaj.art-3ba11517f06440f7843dfdfa8dafa31f2023-11-17T19:55:14ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-03-0111473110.3390/jmse11040731Robust Lane Detection Algorithm for Autonomous Trucks in Container TerminalsNgo Quang Vinh0Hwan-Seong Kim1Le Ngoc Bao Long2Sam-Sang You3Division of Logistics, Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDivision of Logistics, Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDivision of Logistics, Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDivision of Mechanical Engineering, Korea Maritime and Ocean University, Busan 49112, Republic of KoreaContainer terminal automation offers many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A novel lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure fast and accurate lane positioning. A robust lane detection method can deal with complicated detection problems in realistic road scenarios. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions; in addition, the robustness of the lane detection method with stochastic noise is tested.https://www.mdpi.com/2077-1312/11/4/731container terminallane detectionimage processingstochastic differential equationdeep learning
spellingShingle Ngo Quang Vinh
Hwan-Seong Kim
Le Ngoc Bao Long
Sam-Sang You
Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminals
Journal of Marine Science and Engineering
container terminal
lane detection
image processing
stochastic differential equation
deep learning
title Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminals
title_full Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminals
title_fullStr Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminals
title_full_unstemmed Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminals
title_short Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminals
title_sort robust lane detection algorithm for autonomous trucks in container terminals
topic container terminal
lane detection
image processing
stochastic differential equation
deep learning
url https://www.mdpi.com/2077-1312/11/4/731
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AT hwanseongkim robustlanedetectionalgorithmforautonomoustrucksincontainerterminals
AT lengocbaolong robustlanedetectionalgorithmforautonomoustrucksincontainerterminals
AT samsangyou robustlanedetectionalgorithmforautonomoustrucksincontainerterminals