Currently, the research on ship behavior during encounters focuses on evasive behavior during specific situations with existing risks of collision. However, the preliminary selection of encounters to refine the presented ship behavior is biased. To obtain a full understanding of all ship behavior during different encounters in ports and waterways, the encounter is defined from the viewpoint of the spatial-temporal co-existence of ships in the same waterway segments during the same period. Based on this definition, this paper investigates ship behavior through the encounter process with other ships. The proposed approach starts from the moment when the distance in between is minimum as the critical moment to recognize ship behavior change (course alteration and speed change) based on the Sliding Window algorithm. Thus, the encounter process is identified by the key behavior feature point into phases, being before decision-making, before the critical moment, after the critical moment, and after being past and clear. The relative movement factors are calculated according to the behavior status of both ships to describe the conditions, timing, and objective of behavior change during the dynamic process of encounters. The empirical findings based on one-year Automatic Identification System data in the port of Rotterdam are presented. In the overtaking encounters, as the give-way ship, about 14% of the overtaking ships do not take any evasive actions. Among the ships with behavior changes, the preference for course alteration and speed change is equal. As the stand-on ship, about 87% of the overtaken ships take cooperative maneuvers to facilitate the encounter, in which deceleration seems the primary choice. The timing of overtaken ship's behavior change is later than overtaking ship. For overtaking ships, the objective of course alteration is a clear passing distance of about 5 times her beam, 100m for overtaken ships irrespective of her own size. Regarding speed, the overtaking ship aims to reach a relative speed of 0.3 times her own SOG, while the objective for the overtaken ship is fixed at around 2–3 m/s. In the encounters of ships sailing in the opposite direction, most of the ships take maneuvers to change their course or speed. However, within the influence distance of 2 km, over 76% of the ships do not take any evasive behavior, which implies a passing-by situation. Based on the recognized key feature points of behavior change, statistical tests show the objective of clear passing distance has been reached beforehand. The behavior change during head-on situations could be due to the precautionary behavior of officers onboard in case of interaction between ships. The findings enrich the knowledge of ship behavior during different types of encounters in real-life navigation, which can be further applied to simulation models for ship behavior in ports and waterways.

During the process of collision avoidance, especially in a multi-ship encounter situation, the dynamic interactions among individual ships impose a significant impact on collision avoidance decision-making. It is imperative, therefore, that collision avoidance decisions are formulated with a comprehensive consideration of not only the current direct collision conflict but also the potential conflicts due to planned collision avoidance actions. To address this requirement, this paper proposes a dynamic conflict cluster detection method for collision avoidance decision-making in multi-ship encounters. The involved ships are clustered into stable temporal-dependent ship conflict groups taking into account both conflict connectivity and the potential spatiotemporal interactions originating from planned collision avoidance actions. The conflict cluster detection model is implemented within a framework to achieve hierarchical coordinated collision avoidance decision-making. By a simulation experiment of an 11-ship encounter, the proposed method successfully discerns the ships with conflicts and provides feasible collision avoidance decisions. Compared to the non-cluster collision avoidance methods, the proposed method generates the results with acceptable deviating distance and number of collision avoidance actions at minimum computation load. It has been demonstrated that the proposed method is both effective and efficient for officers on board and operators at Vessel Traffic Services centers in real-life navigation.

In ports and waterways, the impacts of external navigational factors may lead to serious incidents due to limited space for ship maneuvering. Using nautical traffic models, these incidents can be predicted in advance. In current studies of nautical traffic models, the impacts of wind and current on ship behavior are seldom considered when modeling the ship behavior in a port area. The numerical maneuvering models simulate the individual ship behavior under such impacts by calculating the hydrodynamic forces working on the ship's hull. However, the input, maneuvering particulars of individual ships, are not available in ports. In order to fill the knowledge gap of estimating ship behavior under external impacts without detailed ship maneuvering information, the impacts of wind and current on the observed dynamic ship behavior (speed over ground and leeway and drift angle) in ports and waterways have been investigated by analyzing Automatic Identification System data (showing ship paths over time) and the meteorological and hydrological data collected from the port of Rotterdam. The relation between unhindered speed variation and ship size is revealed. The regression analysis results on ships with similar size indicate the differences between wind and current impacts. Especially for small ships, the current impact on speed over ground outweighs the wind, while the wind influences the leeway and drift angle more than the current. Based on the quantified impact variation over ship size, the proposed impact mechanism explains the variance of speed over ground and leeway and drift angle. Some conventional sailing habits based on good seamanship, such as a series of small-angle alterations rather than direct turning at waypoints, are also revealed by the statistical analyses. Considering the variation of wind and current conditions in the study area, the analysis result provides generic quantitative insights into the wind and current impacts on the individual behavior of ships of different sizes. These mathematical formulations can be adopted in a microscopic nautical traffic model to include the impacts of external conditions.