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Abstract Recently, maritime accidents caused by human factors have increased according to the increase in the number of ships for sea transportation. Therefore, the autonomous navigation systems that find appropriate avoidance routes in a complex marine environment with various obstacles is attracting attention. In this study, we proposed a collision avoidance method using deep reinforcement learning (DRL) that generates an appropriate control action. DRL-based collision avoidance method derives the required rudder angle of own ship with given state of the own ship and target ship such as position, speed, and heading. To achieve the appropriate collision avoidance, it is necessary to assess the collision risk of the target ship accurately. Therefore, the probabilistic collision risk assessment method was proposed to predict the collision risk of the target ship with the probability distribution of the data. The probability distribution was calculated through the multivariate normal distribution of the four-dimensional variables of the position, speed, and heading angle of the target ship. The collision risk of the target ship was calculated through the probability distribution for each variable and the CPA (Closest Point of Approach)-based collision risk assessment method. To verify the proposed method, we applied the DRL-based collision avoidance method and the collision risk assessment method to various scenarios. The proposed method reliably avoided collisions through flexible paths for complex situations.
Publication Date 2021-12-07

Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, "Deep Reinforcement Learning-Based Ship Collision Avoidance Considering Collision Risk", Proceedings of TEAM(Asian-Pacific Technical Exchange and Advisory Meeting on Marine Structures) 2022, Istanbul, Turkey, pp. 268, 2021.12.06-08


List of Articles
번호 분류 제목 Publication Date
428 Domestic Conference 여인창, 노명일, 전도현, "선박 배관망 지지대의 최적 배치 설계", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12 file 2022-02-10
427 International Conference Jeong-Ho Park, Myung-Il Roh, Hye-Won Lee, Jisang Ha, Yeong-Min Jo, Nam-Sun Son, "Detection and Tracking Methods of Maritime Obstacles Using Multiple Cameras", Proceedings of ICDM 2022, Siheung, Korea, 2022.04.28-29 2022-04-28
426 Domestic Conference 박정호, 노명일, 이혜원, 하지상, 조영민, 손남선, "다중 선박으로부터의 카메라 영상 기반 단일 해상 장애물의 탐지 및 추적 방법", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12 file 2022-02-10
» International Conference Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, "Deep Reinforcement Learning-Based Ship Collision Avoidance Considering Collision Risk", Proceedings of TEAM 2022, Istanbul, Turkey, pp. 268, 2021.12.06-07 file 2021-12-07
424 International Conference Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Method for Automatic Control of Cranes for Block Lifting in Shipyard", Proceedings of PRADS 2022, Dubrovnik, Croatia, pp. 64, 2022.10.09-13 file 2022-10-09
423 Domestic Conference 김기수, 노명일, 송하민, 정동근, "차세대 스마트 함정을 위한 승조원 운영 최적화 방법", 2021년도 함정기술무기체계 세미나, 부산, 2021.06.10-11 2021-06-11
422 Domestic Conference 조영민, 노명일, 이혜원, 진은석, 유동훈, "가상의 센서 데이터 융합을 이용한 해상 장애물의 추적 방법", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12 file 2022-02-11
421 International Conference Min-Chul Kong, Myung-Il Roh, Jisang Ha, Eun Seok Jin, Donghun Yu, "Design of the Integrated System for the Safe Operation Based on Augmented Reality", Proceedings of PRADS 2022, Dubrovnik, Croatia, 2022.10.09-13 file 2022-10-12
420 International Conference Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, Min-Jae Oh, Sejin Oh, "Estimation Model of Hydrodynamic Performance Using Hull Form Variation and Deep Learning", Proceedings of PRADS 2022, Dubrovnik, Croatia, pp. 82, 2022.10.09-13 file 2022-10-09
419 Domestic Conference 공민철, 노명일, 박정호, "가상 현실 기반의 선박 충돌 시나리오 구현", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12 file 2022-02-10
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