Ship Domain Model for Multi-ship Collision Avoidance Decision-making with COLREGs Based on Artificial Potential Field

Abstract

A multi-ship collision avoidance decision-making and path planning formulation is studied in a distributed way. This paper proposes a complete set of solutions for multi-ship collision avoidance in intelligent navigation, by using a top-to-bottom organization to structure the system. The system is designed with two layers: the collision avoidance decision-making and the path planning. Under the general requirements of the International Regulations for Preventing Collisions at Sea (COLREGs), the performance of distributed path planning decision-making for anti-collision is analyzed for both give-way and stand-on ships situations, including the emergency actions taken by the stand-on ship in case of the give-way ship's fault of collision avoidance measures. The Artificial Potential Field method(APF) is used for the path planning in details. The developed APF method combined with the model of ship domain takes the target ships' speed and course in-to account, so that it can judge the moving characteristics of obstacles more accurately. Simulation results indicate that the system proposed can work effectiveness.

A Real-Time Collision Avoidance Framework of MASS Based on B-Spline and Optimal Decoupling Control

“…Until the 1990s, many scholars and experts began to consider and use computer means, soft computing, and other technologies to study collision avoidance algorithms to address the issue of multi-ship collision [10]. The collision avoidance methods include velocity obstacle method (VO) [11], artificial potential field (APF) [12], A-Star [13], rapidly exploring random tree (RRT) [14][15][16], genetic algorithm [17], fuzzy theory [18], deep reinforcement learning (DRL) [19], and spline curves [20]. But overall, it can be classified into four categories, such as traditional algorithms, soft computing algorithms, intelligent learning algorithms, and spline curves.…”

Evaluation of PNT Error Limits Using Real World Close Encounters from AIS Data

“…Since the 1970s, various ship domains have been specified, which differ in the fineness of the modelling and the intended application scenarios. The research focused on improving the representation of existing collision risks to better support manoeuvring decisions, e.g., by considering the available manoeuvring space as well as nautical experiences or by translating the risk parameters into a representation more related to potential evasive manoeuvres [2,[14][15][16][17][18][19][20][21][22][23]. Especially in the last decade, an integrated consideration of ship dynamic aspects and environmental factors has been pursued within the framework of the further development of onboard and shore-based decision support systems [24][25][26][27][28][29][30][31].…”

Розробка Моделі І Методу Ідентифікації Навігаційних Ситуацій Для Підвищення Ефективності Управління В Ергатичних Системах

“…На основі цих даних формується інформаційна модель ситуації. В роботі [3] запропоновано створювати навколо судна потенційне поле, відповідно до якого та навігаційних параметрів руху судна, визначати небезпечні ситуації та визначати судовий домен судна. У роботі [4] розглядаються фактори та закономірності розвитку ситуації, що можуть створювати ризик зіткнення суден.…”