Research On Macroscopic Ship Collision Risk Mathematical Model

With the rapid development of the global shipping industry since 21 st century,ship traffic becomes busier,especially in the water off coast or near port,traffic density grows intensely,and the possibility of ship collision accidents also increases.The growth of ship traffic increases the demand of proposing new tools and methods to model the macroscopic ship collision risk in water.The identification of macroscopic ship collision risk and its geographical distribution by the new models can help maritime surveillance recognize the collision risk in water easier and improve the safety of navigation.This dissertation aims to propose a new model for identifying macroscopic collision risk by using the abundant AIS data,in order to improve the deficiencies in the previous research on macroscopic collision risk to some extent.First,this dissertation proposes a multi-vessel encountering collision risk model based on a cooperative game approach,in order to calculate the global collision risk in multi-vessel encountering.At first,a new collision risk indicator based on the range of collision avoidance manoeuvring and ship domain called danger sector is proposed.Considering the collision avoidance responsibility,danger sector is improved to multivessel danger sector at geometric perspective.The multi-vessel danger sector is converted to collision risk index by Stevens’ s Power Law to represent the collision risk encountered by the vessel in multi-vessel encountering.Then,the Shapley value method in cooperative game is applied to calculate the contribution of each ship to the global collision risk with the consideration of responsibility.Finally,multi-vessel encountering collision risk can be calculated.Meanwhile,the time emergency is considered in the calculation.The model can identify the global collision risk of multivessel encountering efficiently and accurately,and overcome the limitations of previous research in complex situation.The proposed model can provide maritime surveillance with assistance,facilitate their work in analyzing and monitoring collision risk,and provide the basis for the subsequent macroscopic collision risk calculation.Second,this dissertation proposes a macroscopic collision risk model,in order to calculate the global collision risk in water.At first,a spatial clustering algorithm is used to cluster the ships into different clusters with some ships are identified as noises.The global collision risk of each cluster can be calculated by multi-vessel encountering collision risk model.In order to lower the computational complexity and improve the efficiency of calculation,an analytical method is used to calculate the global collision risk of cluster.Apart from DCPA and TCPA,this method considers distance and relative bearing by a new proposed collision risk indicator called Ship Domain Overlapping Index.At last,the global collision risk of water can be represented by different ways according to different objects.Compared with traditional method,the proposed model can consider more factors,is more flexible in use,is easier to establish the relationship between collision risk and time or space,is less limited by the time period and vessel number.It also has good computational efficiency.The model can provide help to maritime surveillance in their analysis and monitor of collision risk,and provide the basis for the subsequent research on the geographical distribution model.Thirdly,this dissertation proposes a collision risk geographical distribution identification model based on a statistical mechanics method.The model is established based on radial distribution function.The dissertation assumes vessel as a molecule that moves freely without manipulation,and introduce the radial distribution function in a particle system into ship traffic research.At first,radial distribution function is applied to model ship density by identifying the distribution probability of ship in water and the ship density map can be depicted by a spatial interpolation technique.Besides,the proposed ship density model can also identify the traffic density and the order of ship position.Then,the proposed ship density model is improved to consider the influence of speed and course.Based on the proposed ship density model and an established threedimension collision risk space,the collision risk is modeled with radial distribution function by identifying the distribution probability of collision risk in the established space.At last,the collision risk map can be depicted by a spatial interpolation technique.Compared with traditional method,the proposed model can identify the geographical distribution of collision risk with higher accuracy and represent the risk of collision more sufficiently.The proposed model can help maritime surveillance recognize the collision risk situation in water more rapidly,clearly and visually under the trend that ship traffic becomes more and more complex.It can help them make related decisions,and improve the navigational safety.This dissertation hopes to improve the deficiencies in the previous research on macroscopic collision risk,and provide maritime surveillance with assistance when analyze and monitor collision risk.The dissertation also desires to provide some references to the subsequent research,and make some contributions to the development of the research on macroscopic collision risk and maritime traffic safety.