Ships transport large volumes of cargo, and are therefore major contributors to the global economy. Ship collisions can cause significant economic losses. Path-planning algorithms can prevent such collisions by suggesting the optimal path for navigation. Conventional path-planning algorithms are disadvantageous, because they do not consider the navigation practices followed by experienced navigators. Therefore, in this study, we developed the requirements for optimal local path planning of autonomous ships by considering the open sea, restricted waters, and two-ship and multi-ship interactions, in addition to the navigation practices adopted by navigators and rules in COLREGs part B. First, the navigation practices under various scenarios were collected. Subsequently, these practices were linked to COLREGs part B to extract the key rules and keywords related to collision avoidance. Finally, the requirements for generating the optimal local path were drafted based on the rules and keywords. The utility of the requirements was demonstrated by applying them to representative path-planning algorithms for the timely and accurate evaluation of their effectiveness. The proposed requirements can be utilized to improve the existing path-planning algorithms and develop superior algorithms in the future.

According to International Regulations for Preventing Collision at Sea, collision avoidance started from assessing the collision risk. In particular, the radar was mentioned as suitable equipment for observation and analysis of the collision risk. Thus, many researches have been conducted by utilizing the radar. Fuzzy Inference System based on Type-1 Fuzzy Logic (T1FIS) using Distance to Closest Point of Approach ( $D_{CPA}$ ) and Time to Closest Point of Approach ( $T_{CPA}$ ) computed via the radar has been largely used for assessing the collision risk. However, the T1FIS had significant limitations on the membership function not including linguistic and numerical uncertainties. In order to solve the issue, we developed the Fuzzy Inference System based on Interval Type-2 Fuzzy Logic (IT2FIS) as follows: (i) the T1FIS was selected among proposed methods based on the type-1 fuzzy logic; (ii) we extended the T1FIS into the IT2FIS by gradually increasing the Footprint of Uncertainty (FOU) size taking into consideration symmetry, and (iii) numerical simulations were conducted for performance validation. As a result, the IT2FIS using the FOU size “±5%” (i.e., interval 10% between upper membership function and lower membership function) not only computed the appropriate and linear collision risk index smoothly until near-collision situation but also help to overcome uncertainties that exist in real navigation environments.

Although the International Regulations for Preventing Collision at Sea (COLREGs) provide guidelines for determining the encounter relations between vessels and assessing collision risk, most collision accidents occur in crossing situations. Accordingly, prior studies have investigated methods to identify the relation between the give-way and stand-on vessels in crossing situations to allow the stand-on vessel to make the optimal collision-avoidance decision. However, these studies were hindered by several limitations. For example, the collision risk at the current time (t) was evaluated as an input variable obtained at the current time (t), and collision-avoidance decisions were made based on the evaluated collision risk. To address these limitations, a collision risk prediction system was developed for stand-on vessels using a fuzzy inference system based on near-collision (FIS-NC) and a sequence model to facilitate quicker collision avoidance decision making. This was achieved by predicting the future time point (t + i) collision risk index (CRI) of the stand-on vessel at the current time point (t) when the own-ship is determined to be the stand-on vessel in different encounter relations. According to the performance verification results, navigators who use the developed system to predict the CRI are expected to avoid collisions with greater clearance distance and time.

In the future, electricity generation through eco-friendly renewable energy will accelerate. Surrounded by sea on three sides, the Republic of Korea is gaining attention for offshore wind power as a future industry, leveraging advantages of its maritime environment. However, maritime navigation remains active in waters, with maritime transportation being crucial, as it accounts for over 95% of the country’s cargo volume. Therefore, ensuring the safety of vessel operations is vital when constructing offshore wind farms. This study proposed alternative routes to ensure the safety of vessels and secure existing routes in the waters of the southwestern sea, where intensive development of OWFs is expected. The routes were determined based on the Permanent International Association of Navigation Congresses (PIANC) Guidelines and Maritime Traffic Safety Act’s implementation guidelines. Clearance between a maritime route and OWF was set to the rule of 6 L + 0.3 NM + 500 m for safety. The route width was calculated while considering vessel maneuverability, environmental factors, seabed conditions, the depth-to-draft ratio, and two-way traffic. The alternative routes were categorized into four types—maritime highways, maritime provincial routes, approach routes for departure/arrival, and recommended routes based on vessel positions, engine status, and route function. By considering traffic flow and applying international and domestic standards, these routes will ensure safe, efficient, and orderly vessel operations.