Trajectory planning is one of the important technologies to ensure the safe navigation of the unmanned ship. This paper presents a dynamic path planning method based on the multi-layer Morphin adaptive search tree algorithm, which considers ship maneuverability, COLREGS, and good seamanship to harmonize the actions in the mixed traffic environment. First, the environment model is built according to the environment information of the rolling window; second, the feasible avoidance range of collision avoidance is calculated according to the velocity obstacle (VO) method. Finally, path optimization is carried out using the Morphin adaptive search tree algorithm. Through a case study and comparison with traditional artificial potential field (APF) models, the applicability and potential of the method are verified. This model can be applied to the autonomous navigation for unmanned ships as well as conventional manned ships and demonstrate good potential in smart shipping.

Conflict detection is a vital step of collision prevention at sea, determining if there is a risk of collision and when to take preventing actions. This article proposes a practical Rule-aware Time-varying Conflict Risk (R-TCR) for ship collision avoidance. Considering maritime practice, the conflict risk measure takes the ship maneuverability, the COLREGs, and good seamanship into account in the conflict risk measure. Specifically, the conflict risk is formulated as a ratio of achievable maneuvers leading to a collision to all achievable maneuvers. Simulations are carried out to show the characteristics of R-TCR. The results show that the R-TCR evaluates the entire conflict risk incorporating COLREG rules, multiple targets, different maneuverability, and varying ship domains. Finally, the proposed measure is applied to analyze the collision accident between two ships. Compared with the conventional risk indicators, the proposed R-TCR can deliver extra information to users, such as providing early warning, showing the room-for-maneuver, and suggesting evasive actions. Besides, the extra information also supports collision avoidance for autonomous ships. 

Following the growth in global trade activities, vessel traffic has increased dramatically in some busy waterways and ports. However, such increments have made it more complex to manage the regional vessel traffic, which can increase the risk of an accident in the area. To model and analyze the relationship between vessel traffic and maritime traffic, this paper proposes a gridded geography information system (GIS)-based relation analysis model using the historical automatic identification system (AIS) data and accident records over a 10-year-span. Firstly, the extent of the hazards posed by a maritime accident in terms of hull loss, fatality, and direct economic loss is quantified using set pair analysis. Consequently, the hazardous degree posed by an accident is obtained. The relative consequence of the regional hazard (RCORH) is then estimated by summing up all the relative hazardous degrees of accidents that have occurred in a certain gridded area. Secondly, the vessel traffic in the gridded areas is analyzed using characteristics such as speed, heading variance, and traffic volume as indicators. Based on the analysis of both the maritime traffic accidents and the vessel traffic, the spatial relationships are analyzed with an overlay between the RCORH and vessel traffic data of each grid, as well as a regression analysis. In a case study of the Western port of Shenzhen City, China, the methodology proves to be effective for vessel traffic management and traffic engineering design.