In the last few years, autonomous ships have attracted increasing attention in the maritime industry. Autonomous ships with an autonomous collision avoidance capability are the development trend for future ships. In this study, a ship manoeuvring process deduction-based dynamic adaptive autonomous collision avoidance decision support method for autonomous ships is presented. Firstly, the dynamic motion parameters of the own ship relative to the target ship are calculated by using the dynamic mathematical model. Then the fuzzy set theory is adopted to construct collision risk models, which combine the spatial collision risk index (SCRI) and time collision risk index (TCRI) in different encountered situations. After that, the ship movement model and fuzzy adaptive PID method are used to derive the ships’ manoeuvre motion process. On this basis, the feasible avoidance range and the optimal steering angle for ship collision avoidance are calculated by deducting the manoeuvring process and the modified velocity obstacle (VO) method. Moreover, to address the issue of resuming sailing after the ship collision avoidance is completed, the Line of Sight (LOS) guidance system is adopted to resume normal navigation for the own ship in this study. Finally, the dynamic adaptive autonomous collision avoidance model is developed by combining the ship movement model, the fuzzy adaptive PID control model, the modified VO method and the resume-sailing model. The results of the simulation show that the proposed methodology can effectively avoid collisions between the own ship and the moving TSs for situations involving two or multiple ships, and the own ship can resume its original route after collision avoidance is completed. Additionally, it is also proved that this method can be applied to complex situations with various encountered ships, and it exhibits excellent adaptability and effectiveness when encountering multiple objects and complex situations.

Collision prevention is critical for navigational safety at sea, which has developed rapidly in the past decade and attracted a lot of attention. In this article, an improved velocity obstacle (IVO) algorithm for intelligent collision avoidance of ocean-going ships is proposed in various operating conditions, taking into count both a ship’s manoeuvrability and Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). An integrated model combines a three-degree-of-freedom manoeuvring model with ship propeller characteristics to provide a precise prediction of ships in various manoeuvring circumstances. In the given case, what is different to present studies, this improved algorithm allows for decision-making in two ways: altering course and changing speed. The proposed technique is demonstrated in a variety of scenarios through simulation. The findings reveal that collision-avoidance decision-making can intelligently avoid collisions with the target ships (TSs) in multi-ship situations.

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.

A great number of collision accidents can be attributed to incongruous collision-avoidance actions between the give-way vessel and the stand-on vessel in a crossing or overtaking situation. If the give-way vessel does not take appropriate collision-avoidance action according to international regulations for preventing collisions at sea, the last barrier to pass safely is the appropriate and effective collision-avoidance action taken by the stand-on vessel. To find the proper autonomous collision-avoidance action of the stand-on vessel, a method is proposed that combines quantitative analysis rules of collision-avoidance with the deduction of nonlinear maneuvering motion process based on the mathematical model group, which conformity can reach 90%. This research presents a method to calculate the timing and most effective collision-avoidance actions for the stand-on vessel based on the four-stage theory of encountering vessels and the characteristics of vessel motion. The accuracy of the latest-action timing and the action amplitude for the stand-on vessel can be increased to the level of second and degree, respectively. A novel model of collision risk index is constructed by the latest time of the feasible collision-avoidance action on the precise of different course-altering amplitude. Methods to find the stand-on vessel’s proper collision-avoidance actions in the open sea are presented. The simulation indicates the proposed method for the stand-on vessel can make correct collision-avoidance decisions autonomously.

This study utilizes the deep-water channel from the mouth of the Liuhe River to the Jiangyin Bridge in China as a case study to address ship navigation decision-making in wide inland waterways equipped with traffic separation systems. We propose a novel navigation decision-making method based on time-sequence rolling calculations, integrating a digital traffic environment model, collision risk model, and course and speed control techniques. Initially, we innovatively incorporated navigation rules into the quantitative analysis of collision risk based on the behavioral characteristics of ships in the study area. This approach led to the development of a decision-making method capable of adapting to system residual errors and random movements of target ships. Subsequently, a multi-ship navigation decision-making experiment was conducted using available Automatic Identification System (AIS) data for the study area. The results indicate that our method effectively controls ship traffic and ensures timely route tracking in a multi-ship environment within wide inland waters equipped with traffic separation systems, significantly enhancing safety and efficiency.