한국항해항만학회:학술대회논문집 (Proceedings of the Korean Institute of Navigation and Port Research Conference)

한국항해항만학회 (Korean Institute of Navigation and Port Research)
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Robust Lane Detection Algorithm for Autonomous Trucks in Container Terminal

  • Ngo Quang Vinh (Graduate school of Korea Maritime and Ocean University) ;
  • Sam-Sang You (Division of Mechanical Engineering, Korea Maritime and Ocean University) ;
  • Le Ngoc Bao Long (Graduate school of Korea Maritime and Ocean University) ;
  • Hwan-Seong Kim (Dept. of Logistics, Korea Maritime and Ocean University)
  • Published : 2023.05.02
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Abstract

Container terminal automation might offer many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A robust 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 lane positioning robustness. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions and tested the robustness of the lane detection method with stochastic noise.

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