Abstract
In complex maritime environments, numerous ships operate simultaneously with overlapping routes, and the presence of confined waters, such as ports and coastal areas, increases the risk of collisions. In such environments, inappropriate maneuvers caused by human factors can lead to severe maritime accidents, including collisions and groundings. Therefore, autonomous navigation technology is essential for safe collision avoidance even in complex situations. Previous studies on traditional collision avoidance methods have explored rule-based methods such as RVO (Reciprocal Velocity Obstacles). However, in crowded environments with multiple ships, available maneuver options are limited, leading to excessively conservative decision-making. Furthermore, uncertainty due to sensor errors may degrade performance.
최성원, “어텐션 모듈 및 전문가 혼합 모델을 활용한 심층 강화 학습 기반 선박의 개선된 충돌 회피 방법”, 석사학위논문, 서울대학교, 2026.02.25