###### Abstract
Furthermore, VO algorithms are provided for collision avoidance based on the target ships whose motions are non-linear and probabilistically predictable [27]. Moreover, the article [28], presents a generalised VO algorithm for ship collision avoidance and designs a collision, which is more reliable and suitable for close-range ship collision avoidance. Considering the ship maneuverability, multi-ship, COLREGs, off-course, and seamanship, [PERSON] [29], designed the multistage optimisation decision model based on the modified VO method. Despite a lot of research work and achievements being completed on ship collision avoidance, there are still some unignorable shortcomings in the available studies. Most of the current research on decision-making for collision avoidance in the multi-ship situation considers the ship motion model insufficiently, especially in the process of the changing speed of ship motion. Little research has been focused on the model in which the ship's speed and rotation of the propeller are not matched. Moreover, the decision-making of ship-intelligent collision avoidance should be expected to follow COLREGs and good seamanship, which are guidelines for all vessels. Although humans are good at interpreting navigational regulation, negligence will lead to marine accidents. Therefore, a model combining the advantages of human intelligence and machine intelligence is necessary for ship collision avoidance. The advantages of machine intelligence in computing power are extremely complementary to human intelligence. In other words, this model will not only provide real-time decision-making for collision avoidance but will also take into account the COLREGs and good seamanship. Considering the characteristics of ship movement, an accurate manoeuvring model is required to deduce future ship motion trends and states for collision avoidance, especially when large ships are involved in adjustable speed operations. In conclusion, this paper aims to design an intelligent collision avoidance model for ships, which combines the COLREGs and good seamanship mentioned above, as well as ship manoeuvrability, based on the advantages of both machine intelligence and human intelligence. Furthermore, the primary research topic for this project is: how can the ship combine machine intelligence and human intelligence to make intelligent collision avoidance decisions? The main contributions of this article are as follows:  
1. This paper provides the improved mathematical model group (MMG) based on ship manoeuvrability to deduce the process of own ship (OS) motion, which is also appropriate for the situation when a ship's speed and rotation of propeller are not matched. 2. An integrated algorithm for collision avoidance decision-making based on improved VO algorithm and MMG is presented, which comprehensively considers COLREGS, sea practice, and good seamanship. 3. The decision-making of collision avoidance following the manoeuvrability habit of manned ships is provided by combining a dynamic feasible manoeuvring decision interval and an optimisation evaluation function, which will gap reduce the difference of awareness about manoeuvrability in the process of collision avoidance between the intelligent and manned ship. The contents of the research are arranged as follows: The quantitative analysis of COLREGs, improved MMG, and improved Velocity Obstacle (IVO) algorithm are covered in Section 2. The intelligent collision avoidance method based on the collision risk index (CRI) model is covered in Section 3, which introduces dynamically feasible manoeuvring intervals calculated by IVO algorithm and the collision decision determined by optimisation functions. The case study in Section 4 demonstrates the accuracy of MMG and the practicality of the proposed strategy. In Section 5, there is an analysis and discussion on future research. Finally, in Section 6, the conclusions are outlined.