1. Introduction

2. Materials and Methods

2.3. Ship Collision Analytical Model

To investigate the potentiality of collisions involving historical vessels and towed transport fleets using a deductive approach, it is imperative to initially comprehend the various scenarios in which collisions occur. Subsequent to this understanding, an analysis of these collision scenarios is conducted to discern the fundamental causes underlying these accident scenarios. This analysis further facilitates the delineation of the constituents of accident scenarios, culminating in the establishment of a mathematical model. As depicted in Figure 5, collisions between vessels and towed transport formations primarily manifest in two distinct categories: vessel-to-vessel collisions and vessel-to-FOWT collisions. Notably, these two collision categories correspond to two distinct collision modes: bow impact and impact during evasive manoeuvres. Therefore, this segment will be subdivided into two sections for investigation. The first involves the deductive analysis and model development of vessel-to-vessel collision scenarios. In this section, consideration will also be given to whether the motion of the FOWT connected by a flexible coupling can lead to secondary incidents. The second part entails the deductive analysis and model development of vessel-to-FOWT collision scenarios.

Nevertheless, it is imperative to preface with some general settings. As mentioned in the assumptions section, collision occurrence is considered once the circles of the target objects are tangent. Equation (1) to (2) provide the methodology for calculating the collision area diameters for both vessels and Floating Offshore Wind Turbines (FOWTs). It is noteworthy that, while the Pedersen algorithm is currently well-established for calculating the probability of vessel-to-vessel collisions based on AIS data in commercial waterways, it is specifically developed for ship collisions occurring in navigational channels. Given the absence of commercial shipping lanes in the vicinity of the study area and the prevalence of fishing vessels, the navigation patterns applicable to the Pedersen algorithm may not be suitable. Consequently, the use of a normal distribution to assess the position and trajectory of vessel navigation is not applicable in this context.

$$W_S=\raisebox{1ex}{$2$}\!\left/ \!\raisebox{-1ex}{$\pi $}\right.\left(L_S+B_S\right)$$

(1)

$$W_T=\raisebox{1ex}{$4\sqrt{3}$}\!\left/ \!\raisebox{-1ex}{$3$}\right.\left(\raisebox{1ex}{$D_f$}\!\left/ \!\raisebox{-1ex}{$2$}\right.+R_f\right)$$

(2)

Where ${\mathit{W}}_{\mathit{S}}$ is the equivalent width of the ship; ${\mathit{L}}_{\mathit{S}}$ is the length of the ship; ${\mathit{B}}_{\mathit{S}}$ is the breadth of the ship; ${\mathit{W}}_{\mathit{T}}$ is the equivalent width of the FOWT; ${\mathit{D}}_{\mathit{f}}$ is the distance between the center of floaters; ${\mathit{R}}_{\mathit{f}}$ is the radius of floaters;

Lastly, consideration is given to the methodology employed for probability calculations. To analyze the reasons behind collisions between two vessels, it is essential to investigate the fundamental causes of collision incidents. Table 4 presents a series of fundamental reasons for vessel collisions, along with the corresponding symbols used in this study, the respective values employed, and the origins of these numerical values.

$$P_r\left(t_e\right)=\raisebox{1ex}{$0.5$}\!\left/ \!\raisebox{-1ex}{$0.605$}\right.{\left(\raisebox{1ex}{$t_e$}\!\left/ \!\raisebox{-1ex}{$0.605$}\right.\right)}^{0.4}{e}^{-{\left(\raisebox{1ex}{$t_e$}\!\left/ \!\raisebox{-1ex}{$0.605$}\right.\right)}^{0.5}}$$

(3)

$$t_e=\raisebox{1ex}{$D_E$}\!\left/ \!\raisebox{-1ex}{$V_{ij}$}\right.$$

(4)

Where ${\mathit{V}}_{\mathit{i}\mathit{j}}$ is the relative speed of ship i and j; ${\mathit{t}}_{\mathit{e}}$ is the evasive duration; ${\mathit{D}}_{\mathit{E}}$ is the evasive distance, set as 2.5km. These two equations are used to calculate the time may take for ships to make evasive reactions when they have vision with each other. If there is no evasive reaction on both sides, a collision accident may happen highly likely.

Having acquired the necessary foundations and general research methods, the discussion now turns to the consideration of whether the transportation route intersects with navigational channels. If the transportation route traverses or partially intersects with a navigational channel, the vessel behavior in the channel needs to be taken into account during transportation, and collision probabilities are computed based on this information. Conversely, if the transportation route does not intersect with or closely approach navigational channels, the behavioral patterns of fishing vessels and other ships in the target area need to be considered. Given the distinct calculation methods required for these two scenarios, they warrant separate discussions.

2.3.1. Channel Area Collision Analytical Model

As delineated earlier, if there is an overlap between the transportation route and the primary navigational channels, it necessitates the consideration of potential collisions occurring separately for vessels in the navigational channels and the transportation fleet. In such instances, adhering to the Pedersen method, it is posited that the navigational behavior of vessels in the channel follows a normal distribution. Conversely, the towed transport fleet is conceptualized as an obstacle possessing a certain level of active avoidance capability—a circumstance not addressed in the Pedersen method, which assumes static obstacles without evasion functionalities along the route. According to the description in Figure 6, this situation gives rise to four major collision categories: encounter, overtaking, crossing, and bend collision. The bend collision category can be further subdivided into the opposite direction and same direction scenarios. Consequently, the ensuing deductive analysis will commence by examining and modeling these scenarios individually.

Figure 6. Three collision scenarios: (a) encounter collision; (b) overtaking collision; (c) crossing collision.

Figure 6. Three collision scenarios: (a) encounter collision; (b) overtaking collision; (c) crossing collision.

Figure 7. Two bend collision types: (a) opposite direction; (b) same direction.

Figure 7. Two bend collision types: (a) opposite direction; (b) same direction.

Firstly, analyze the three scenarios depicted in Figure 6. For vessels navigating in the channel, their navigational behavior typically conforms to a normal distribution, as illustrated in Formula (5), with Figure 8 providing supplementary clarification of this normal distribution. In the event of contact between two vessels or a vessel and FOWT, it can be assumed that the geometric collision circles of vessel-to-vessel or vessel-to-FOWT are tangent. The length of this segment is defined as the geometric collision diameter. Formula (6) represents the geometric diameter for vessel-to-vessel collisions, and Formula (7) represents the geometric diameter for vessel-to-FOWT collisions. Thus, the time elapsed before an incident occurs, after a vessel in channel i detects the towed transport fleet, is determined by the reaction distance between the two vessels, relative velocity, and geometric collision diameter. The expression (8) provides the function for the number of collisions between vessels on channel i and the fleet within a unit of time. By substituting Equation (5), (6), and (7) into (8), the total number of vessels colliding with the fleet on channel i within time t can be obtained, as expressed in Formula (9). It is noteworthy that, when investigating encounters and overtaking collisions, the sequence of vessel collisions needs to be considered. Therefore, appropriate modifications to the term $\left({\mathit{D}}_{\mathit{S}-\mathit{S}}+{\mathit{D}}_{\mathit{S}-\mathit{T}}\right)$ in the equation are required, reflecting that vessels in the channel cease to collide with the fleet after encountering the first object in the towed transport fleet.

$$f\left(z\right)=\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$\sqrt{2\pi }\sigma $}\right.exp\frac{-{\left(z-\mu \right)}^2}{2{\sigma }^2}$$

(5)

$$D_{S-S}=\raisebox{1ex}{$2$}\!\left/ \!\raisebox{-1ex}{$\pi $}\right.\left(L_{S1+S2}+B_{S1+S2}\right)$$

(6)

$$D_{S-T}=\raisebox{1ex}{$2$}\!\left/ \!\raisebox{-1ex}{$\pi $}\right.\left(L_S+B_S\right)+\raisebox{1ex}{$4\sqrt{3}$}\!\left/ \!\raisebox{-1ex}{$3$}\right.\left(\raisebox{1ex}{$D_f$}\!\left/ \!\raisebox{-1ex}{$2$}\right.+R_f\right)$$

(7)

$$N_i=\raisebox{1ex}{$Q_i$}\!\left/ \!\raisebox{-1ex}{$V_i$}\right.f_i\left(z_i\right)\left(D_{S-S}+D_{S-T}\right)V_{ij}d{z}_{i}dt$$

(8)

$$N_t=\sum _i\underset{0}{\overset{t}{\int }}\underset{z_i}{\int }\raisebox{1ex}{$Q_i$}\!\left/ \!\raisebox{-1ex}{$V_i$}\right.\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$\sqrt{2\pi }\sigma $}\right.exp\frac{-{\left(z_i-\mu \right)}^2}{2{\sigma }^2}\left(D_{S-S}+D_{S-T}\right)V_{ij}d{z}_{i}dt$$

(9)

Where $\mathit{z}$ is the distance from the centerline of navigation route; $\mathit{\mu }$ is the mean value of the spatial distribution; and $\mathit{\sigma }$ is the standard deviation; ${\mathit{D}}_{\mathit{S}-\mathit{S}}$ is the geometrical collision diameter between ships; ${\mathit{D}}_{\mathit{S}-\mathit{T}}$ is the geometrical collision diameter between ship and FOWT; ${\mathit{L}}_{\mathit{S}\mathbf{1}+\mathit{S}\mathbf{2}}$ is the total overall length of ships; ${\mathit{B}}_{\mathit{S}\mathbf{1}+\mathit{S}\mathbf{2}}$ is the total breadth of ships; ${\mathit{N}}_{\mathit{i}}$ is the collision candidate in shipping route $\mathit{i}$ during unit period; ${\mathit{Q}}_{\mathit{i}}$ is the quantity of ships in shipping lane; ${\mathit{V}}_{\mathit{i}}$ is the velocities of ships in shipping lane; ${\mathit{N}}_{\mathit{t}}$ is the total number of collision candidate in shipping lane during the transportation fleet pass the shipping lane; $t$ is the duration of transportation fleet pass the shipping lane.

Once the total number of vessels potentially involved in collisions within the route is determined, the collision frequency can be calculated by combining the probabilities corresponding to various collision forms. Equation (10) represents the calculation method for the frequencies of three common collision forms, where the value of ${\mathit{P}}_{\mathit{c}}$ can be referenced from Table 5.

$$F_{collison}=N_t·P_c$$

(10)

The intricacies of bends collision scenarios, as illustrated in Figure 7, introduce a level of complexity. Traditionally, the establishment of a reliable analytical model necessitates considerations such as the operational status and inspection frequency of the Vessel Traffic System (VTS), as well as factors including the reaction distance between vessels. The integration of these diverse factors makes it challenging to formulate a robust analytical model. Consequently, when scrutinizing this particular issue, it is plausible to posit that the occurrence of such accidents is rooted in anomalies with vessels navigating the channel itself. Within the temporal window subsequent to detecting the towed transport fleet, these vessels fail to execute appropriate course adjustments, and the fleet is unable to evade successfully. This leads to the formulation of equations (11) and (12). Additionally, given the inherent absence of evasion capabilities in Floating Offshore Wind Turbines (FOWTs), the analysis of collisions between navigating vessels and FOWTs obviates the need to consider fleet evasion scenarios.

$$F_{collision}=N_t·P_{Human}·\left(1-P_{ca}\right) \text{for} \text{opposite} \text{direction} \text{bend} \text{collision}$$

(11)

$$F_{collision}=N_t·P_{Human}·{\left(1-P_{ca}\right)}^2 \text{for} \text{same} \text{direction} \text{bend} \text{collision}$$

(12)

The aforementioned model employs a deductive approach to analyze and construct a frequency estimation model for collisions between FOWTs transport fleets and vessels in navigational channels. The analytical process reveals the multitude of factors that must be considered when assessing vessel collisions. In practical engineering applications with similar requirements, it is advisable to deploy safety vessels on the periphery of the fleet to alert passing vessels to alter their course, thereby mitigating the risk of accidents.

2.3.2. Non-Channel Area Collision Analytical Model

For towed projects not situated near navigational channels, the methods mentioned earlier cannot be applied to estimate collision frequencies. The navigational behavior of fishing vessels often involves repetitive movements within a specific region, while engineering vessels navigate linearly between operation sites and docks, avoiding impassable areas. Both behaviors are challenging to statistically analyze and predict due to their unique characteristics. Consequently, a reanalysis of collision scenarios between these two types of vessels is necessary, and the specific analytical approach is illustrated in Figure 9.

Firstly, an estimation of the total number of vessels that could potentially collide in a given maritime area needs to be conducted. This estimation should be based on monthly statistics, taking into account the differences in fish species present in the sea during different months, as well as restrictions imposed by fishing bans in the vessels' respective countries. These factors can lead to significant variations in the number of fishing vessels, vessel types, and concentrated distribution areas in a particular maritime region. In this study, an assumption of uniform vessel density in a given maritime area is employed.

Next, the calculation involves determining all vessels that could potentially navigate into the path of the transport fleet during transportation. Essentially, this entails two-dimensional quantification of the overtaking problem: calculating the range within which all nearby vessels, traveling at speeds ranging from $-{\mathit{v}}_{\mathbf{2}}$ to ${\mathit{v}}_{\mathbf{2}}$ (where ${\mathit{v}}_{\mathbf{2}}>{\mathit{v}}_{\mathbf{1}}$, the speed of the transport fleet), would converge towards the transport fleet from various directions during the transportation process at the speed of ${\mathit{v}}_{\mathbf{1}}$.

Finally, when a navigating vessel visually detects or radar scans the towed transport fleet on its predetermined course, an avoidance response should be initiated. In the event of a collision, it indicates a malfunction in the propulsion and/or steering systems of the navigating vessel. Therefore, the probability of such occurrences should be factored into the analysis.

In summary, equations (13) to (16) provide the mathematical analytical model for collisions of this nature.

$${\rho }_{pmi}={\displaystyle \sum }_m{\displaystyle \sum }_i\raisebox{1ex}{$N_{mi}$}\!\left/ \!\raisebox{-1ex}{$A_p$}\right.$$

(13)

$$A_{candidates}=\underset{\left(v_2-v_1\right)t}{\overset{\left(v_2+v_1\right)t}{{\displaystyle \int }}}\underset{-v_{2}t}{\overset{v_{2}t}{{\displaystyle \int }}}\sqrt{x^2+y^2-2xycos\left[\theta \left(t\right)\right]}dxdy$$

(14)

$$\theta \left(t\right)=\underset{0^{°}}{\overset{{360}^{°}}{{\displaystyle \int }}}co{s}^{-1}\raisebox{1ex}{$v_1\left(1-t^2\right)$}\!\left/ \!\raisebox{-1ex}{$v_2$}\right. dt$$

(15)

$$F_{collision}={\rho }_p·A_{candidates}·\left\{P_c+P_{pf}\left[1-P_r\left(t_e\right)\right]+P_{sf}\left[1-P_r\left(t_e\right)\right]\right\}$$

(16)

Where ${\mathit{\rho }}_{\mathit{p}\mathit{m}\mathit{i}}$ is the i type ship density in m month in the project area; ${\mathit{N}}_{\mathit{m}\mathit{i}}$ is the number of i type of ship in m month; ${\mathit{A}}_{\mathit{p}}$ is the project area; ${\mathit{A}}_{\mathit{c}\mathit{a}\mathit{n}\mathit{d}\mathit{i}\mathit{d}\mathit{a}\mathit{t}\mathit{e}\mathit{s}}$ is the ship location area which may collision with transport fleet when ships in velocity ${\mathit{v}}_{\mathbf{2}}$; ${\mathit{v}}_{\mathbf{1}}$ is the fleet velocity; $\mathit{x}$ is the horizontal displacement of ships; $\mathit{y}$ is the vertical displacement of ships; $\mathit{t}$ is the duration of the fleet from port to the wind farm; ${\mathit{F}}_{\mathit{c}\mathit{o}\mathit{l}\mathit{l}\mathit{i}\mathit{s}\mathit{i}\mathit{o}\mathit{n}}$ is the frequency of collision. Figure 10 helps to understand the process of building the analytic model. Assuming that during the process of a fleet moving from point A to point B at a velocity ${\mathit{v}}_{\mathbf{1}}$, there is a ship approaching the fleet at a velocity ranging from 0 to ${\mathit{v}}_{\mathbf{2}}$ at each $\Delta \mathit{t}$ moment. Then, within the total duration t from point A to point B, the cumulative area of all the positions where ships could potentially collide with the fleet is as depicted in the figure. In this process, the direction angle of the domain vessel ${\mathit{v}}_{\mathbf{2}}$ varies with time, and the relative position between the two ships also diminishes as time elapses. The analysis process did not take into account the collision geometry between the ship hull and the FOWT, as the collision geometry of ships and FOWTs is negligible at the scale of the sea area, rendering it insignificant for computational purposes.

According to the above analytic formula, the collision frequency between the transport fleet and the ships in a non-channel area can be roughly calculated.

In summary, the analytical scale and methods applied by the fleet in navigating through and avoiding channel routes exhibit significant differences. The fundamental cause of these differences lies in the distinct characteristics of the navigation channels and the traffic volume: the navigational behavior and traffic volume of vessels in primary channels are more predictable compared to those in fishing zones, with a considerable amount of research having utilized various methods to analyze them; hence, collision probability calculations can be conducted on a smaller scale using relatively mature distribution methods. In contrast, the behavior of vessels in non-channel areas, particularly fishing boats, is more challenging to statistically analyze and predict, necessitating the estimation of collision probabilities on a larger scale through geometric analysis techniques.

3. Results

4. Discussion

5. Conclusions

References

1. Polcyn, J.; Us, Y.; Lyulyov, O.; Pimonenko, T.; Kwilinski, A. Factors Influencing the Renewable Energy Consumption in Selected European Countries. Energies 2021, 15, 108. [Google Scholar] [CrossRef]
2. Taulo, J.L.; Sebitosi, A.B. Material and Energy Flow Analysis of the Malawian Tea Industry. Renew. Sustain. Energy Rev. 2016, 56, 1337–1350. [Google Scholar] [CrossRef]
3. Hosseini, S.E. Fossil Fuel Crisis and Global Warming. In Fundamentals of Low Emission Flameless Combustion and Its Applications; Elsevier, 2022; pp. 1–11.
4. Olabi, A.G.; Abdelkareem, M.A. Renewable Energy and Climate Change. Renew. Sustain. Energy Rev. 2022, 158, 112111. [Google Scholar] [CrossRef]
5. Liu, Y.; Zhang, J.M.; Min, Y.T.; Yu, Y.; Lin, C.; Hu, Z.Z. A Digital Twin-Based Framework for Simulation and Monitoring Analysis of Floating Wind Turbine Structures. Ocean Eng. 2023, 283. [Google Scholar] [CrossRef]
6. Nielsen, F.G. Perspectives and Challenges Related Offshore Wind Turbines in Deep Water. Energies 2022, 15, 2844. [Google Scholar] [CrossRef]
7. Jiang, Z. Installation of Offshore Wind Turbines: A Technical Review. Renew. Sustain. Energy Rev. 2021, 139, 110576. [Google Scholar] [CrossRef]
8. Anning, X. Research on Numerical Simulation of Transportation and Installation of Offshore Wind TurbineTurbine in Floating Condition, 2022.
9. Jian, Z. Research on Towing Motion Response and Risk Analysis of Fully Submerged Floating Offshore Wind Turbine, 2019.
10. Xudong, C.; Guozhao, K. Optimized Design of Mooring System for Deep-Water Floating Wind Turbine Platform. Sh. Ocean Eng. 2023, 52, 43–51. [Google Scholar]
11. Chuanyang, Z.; Hongbing, L.I.U.; Zhe, J.; Hehe, S.U.; Xianqiang, Q.U.; Hui, L.I. Failure Risk Analysis of Floating Offshore Wind Trubine Mooring Systems Based on the Fault Tree Method. 2023, 44, 3–9.
12. Liqin, L.; Weichen, J.; Zunfeng, D.; Changshui, X. Quantitative Risk Analysis of Floating Offshore Wind Turbine Foundation-Tower System Based on FTA Method. China Offshore Platf. 2019, 34, 79–87. [Google Scholar]
13. Hou, G.; Xu, K.; Lian, J. A Review on Recent Risk Assessment Methodologies of Offshore Wind Turbine Foundations. Ocean Eng. 2022, 264. [Google Scholar] [CrossRef]
14. Wei, G.; Yang, Y.; Jichun, M.; Xunkui, Z. Effects of Second-Rorder Hydrodynamics on the Dynamic Responses of a Semisubmersible-Type 15MW Wind Turbine. Renew. Energy Resour. 2023, 41, 333–338. [Google Scholar] [CrossRef]
15. Guanqing, H. Prediction of Motion Responses for the Floating Offshroe Wind Turbine Under Extreme Conditions, 2021.
16. Changshui, X.; Liqin, L.; Weichen, J. Risk Assessment of Floating Wind Turbine Blade System Based on FTA Method. China Offshore Platf. 2019, 34, 39–46. [Google Scholar]
17. 高龙 Study on Aeroelastic Response of Large Floating Offshroe Wind Turbine Based on FAST, 2022.
18. He, L. New FMECA and Bayesian Network Methodologies of Floating Offshore Wind Trubines’ Reliability Analysis, 2021.
19. Weichen, J. Reliability Analysis in Foundation-Tower-Blade and the Whole Risk Evaluation of Offshroe Floating Wind Turbine.
20. Salvação, N.; Soares, C.G. Floating Offshroe Wind Farms; 2016; ISBN 9783319279701.
21. Myhr, A.; Bjerkseter, C.; Ågotnes, A.; Nygaard, T.A. Levelised Cost of Energy for Offshore Floating Wind Turbines in a Life Cycle Perspective. Renew. Energy 2014, 66, 714–728. [Google Scholar] [CrossRef]
22. Hassan, M.; Guedes Soares, C. Dynamic Analysis of a Novel Installation Method of Floating Spar Wind Turbines. J. Mar. Sci. Eng. 2023, 11, 1373. [Google Scholar] [CrossRef]
23. Yiyao, Z. Optimization of Connection and Support Structure for Twin-Barge Float-over Installation of Offshore Wind Turbines, 2022.
24. Sclavounos, P.D.; Lee, S.; DiPietro, J.; Potenza, G.; Caramuscio, P.; De Michele, G. Floating Offshore Wind Turbines: Tension Leg Platform and Taught Leg Buoy Concepts Supporting 3-5 MW Wind Turbines. Eur. Wind Energy Conf. Exhib. 2010, EWEC 2010 2010, 3, 2361–2367. [Google Scholar]
25. Myland, T.; Adam, F.; Dahlhaus, F.; Großmann, J. Towing Tests for the GICON®-TLP for Offshore Wind Turbines. Renew. Energies Offshore - 1st Int. Conf. Renew. Energies Offshore, RENEW 2014 2015, 705–708. [CrossRef]
26. Presencia, C.E.; Shafiee, M. Risk Analysis of Maintenance Ship Collisions with Offshore Wind Turbines. Int. J. Sustain. Energy 2018, 37, 576–596. [Google Scholar] [CrossRef]
27. Dai, L.; Ehlers, S.; Rausand, M.; Utne, I.B. Risk of Collision between Service Vessels and Offshore Wind Turbines. Reliab. Eng. Syst. Saf. 2013, 109, 18–31. [Google Scholar] [CrossRef]
28. Zhang, S.; Pedersen, P.T.; Villavicencio, R. Probability of Ship Collision and Grounding; 2019; ISBN 9780128150221.
29. 中华人民共和国海事局 导航综合服务系统 Available online: https://ais.msa.gov.cn/.
30. Wang, J.S.; Liu, Y.X.; Yang, K.; Li, M.C.; Sun, C. Extraction Method of Main Routes in South China Sea Based on Spatial Cluster Analysis. Jiaotong Yunshu Gongcheng Xuebao/Journal Traffic Transp. Eng. 2016, 16, 91–98. [Google Scholar]
31. Wang, J.; Li, M.; Liu, Y.; Zhang, H.; Zou, W.; Cheng, L. Safety Assessment of Shipping Routes in the South China Sea Based on the Fuzzy Analytic Hierarchy Process. Saf. Sci. 2014, 62, 46–57. [Google Scholar] [CrossRef]
32. Wan, Z.; Shi, Z.; Nie, A.; Chen, J.; Wang, Z. Risk Assessment of Marine Invasive Species in Chinese Ports Introduced by the Global Shipping Network. Mar. Pollut. Bull. 2021, 173, 112950. [Google Scholar] [CrossRef]
33. Guan, Y.; Zhang, J.; Zhang, X.; Li, Z.; Meng, J.; Liu, G.; Bao, M.; Cao, C. Identification of Fishing Vessel Types and Analysis of Seasonal Activities in the Northern South China Sea Based on Ais Data: A Case Study of 2018. Remote Sens. 2021, 13. [Google Scholar] [CrossRef]
34. Fujii, Y. Integrated Study on Marine Traffic Accidents. Reports Work. Comm. (International Assoc. Bridg. Struct. Eng. 1983, 42, 91–98. [Google Scholar] [CrossRef]
35. Montewka, J.; Hinz, T.; Kujala, P.; Matusiak, J. Probability Modelling of Vessel Collisions. Reliab. Eng. Syst. Saf. 2010, 95, 573–589. [Google Scholar] [CrossRef]
36. Rasmussen, M.F.; Glibbery, K.K.A.; Melchild, K.; Hansen G., M.; Jensen, K.T.; Lehn-Schioler, T.; Randrup-Thomsen, S. Quantitative Assessment of Risk to Ship Traffic in the Fehmarnbelt Fixed Link Project. J. Polish Saf. Reliab. Assoc. 2012, 3, 123–134. [Google Scholar]
37. Čorić, M.; Mandžuka, S.; Gudelj, A.; Lušić, Z. Quantitative Ship Collision Frequency Estimation Models: A Review. J. Mar. Sci. Eng. 2021, 9. [Google Scholar] [CrossRef]
38. Fujii, Y.; Mizuki, M. Design of VTS Systems for Water with Bridges. In Ship Collision Analysis; 1998; p. 14.