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Abstract Most marine accidents are caused by human error, such as navigators' immaturity or carelessness. In this study, we propose a guide system that presents an optimal route to avoid collision and information of collision risk to navigators for the safe and efficient operation. Firstly, the information of the own ship and other ships are obtained through Auto Identification System (AIS) data. The AIS data is provided in real-time through the National Marine Electronics Association (NMEA) protocol interface. Then, the collision risk of other ships are assessed using a method based on the closest point of approach (CPA) and a ship safety domain. As a result of using a combination of the CPA-based method and the ship safety domain, we represent a normalized collision risk that the navigator can recognize the risk intuitively. Finally, the optimal route to avoid the collision is generated based on the collision risk, by using various route optimization algorithms such as Dijkstra, A *, and isochrone algorithm. In particular, international regulations such as the International Regulations for Preventing Collisions at Sea (COLREGs) and ship's maneuverability were taken into account when generating a route for collision avoidance. The generated route and the collision risk information are visualized through the developed program. In order to verify the effectiveness of this study, we applied the suggested algorithms to various scenarios and compared them with the actual navigation data. As a result, we confirmed that the suggested route could effectively avoid collisions in a complex marine environment.

Keywords: Collision avoidance, Collision risk, AIS, COLREGs
Publication Date 2020-11-23

Jisang Ha, Myung-Il Roh, Hye-Won Lee, Jong-Ho Eun, Jong-Jin Park, Hyun-Joe Kim, "A Method of the Collision Avoidance of a Ship Using Real-time AIS Data", Proceedings of ACSMO(Asian Congress of Structural and Multidisciplinary Optimization) 2020, Seoul, Korea, pp.106, 2020.11.23-25


  1. Myung-Il Roh, "Simulation Based Engineering for Ship and Offshore Plant", International Ocean Technology Conference & Expo (IOTCE 2015), Qingdao, China, 2015.09.01-03

  2. Myung-Il Roh, "Physics-based Simulation for Design, Production, and Installation of Ships and Offshore Structures", International Symposium on Computational Design and Engineering, Ho Chi Minh, Vietnam, 2017.12.13-16

  3. No Image 07Dec
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    in Invited Seminar

    Myung-Il Roh, "Core AI Technologies for Autonomous Ships", 2023 Annual Autumn Meeting, JASNAOE (Japan Society of Naval Architects and Ocean Engineers), Nagasaki, Japan, 2023.11.27-28

  4. Myung-Il Roh, "Applications of Deep Learning in Ship Design, Production, and Operation Stages", Proceedings of ICDM(International Conference on Decarbonization and Digitalization in Marine Engineering) 2022, Siheung, Korea, 2022.04.28-29

  5. No Image 13Oct
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    in Invited Seminar

    Myung-Il Roh, "SNU Education Programs for Offshore Engineering", The 30th Asian-Pacific TEAM(Technical Exchange and Advisory Meeting on Marine Structures) 2016, Mokpo, Korea, 2016.10.10.10

  6. No Image 13Oct
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    in Invited Seminar

    Myung-Il Roh, "Introduction to Program of University Specialized for Offshore Plant Engineering in Korea", Offshore Korea 2016, Busan, Korea, 2016.10.19-20

  7. No Image 17Aug
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    in Conference Chairman

    Modeling & Simulation II, 2016년도 한국CAD/CAM학회 동계학술발표회, 평창, 2016.01.27-29

  8. Min-Jae Oh, Myung-Il Roh, Young-Soo Seok, and Sung-Jun Lee, "Optimization of a Ship Hull Form using Deep Learning", Proceedings of ACDDE 2019, Penang, Malaysia, 2019.07.07-10

  9. Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, Jeong-Youl Lee, Myeong-Jo Son, "Operational Analysis of Container Ships Using AIS Data", Proceedings of ACDDE 2018, Okinawa, Japan, 2018.11.1-3

  10. Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, In-Il Kim, Chang-Yong Kim, Won-Joon Lee, "Estimation of Ship Energy Efficiency from Big Data Analysis", Proceedings of the 32nd Asian-Pacific TEAM 2018, Wuhan, China, pp. 262-264, 2018.10.15-18

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