Ship Motion Research Articles

Intelligent shipping: integrating autonomous maneuvering and maritime knowledge in the Singapore-Rotterdam Corridor

Designing safe and reliable routes is the core of intelligent shipping. However, existing methods for industrial use are inadequate, primarily due to the lack of considering company preferences and ship maneuvering characteristics. To address these challenges, here we introduce a methodological framework that integrates maritime knowledge and autonomous maneuvering model. Based on historical maritime big data, the framework offers customized routes for companies with specific routing preferences. The autonomous maneuvering model then evaluates the safety and reliability of the routes by considering ship motion characteristics and ocean hydrodynamics. We validate its effectiveness on the world’s longest Green and Digital Shipping Corridor between Singapore and Rotterdam. Results demonstrate that our model can provide customized route design for companies and enhance safety for shipping. The framework could serve as a fundamental structure to build a fully digitalized platform for route customization and evaluation for global shipping, optimizing operational decision-making and safety assurance.

Eradication of Yellow Crazy Ants, Anoplolepis gracileps Smith, from Lismore and Statistical Proof of Freedom Using Scenario Tree Analysis

Yellow crazy ants (YCAs) are an invasive ant with a pantropical distribution, largely due to the international movements of ships and produce. This invasive ant has the capacity to impact a broad range of environmental, domestic and agricultural situations and has the ability to develop into supercolonies and dominate landscapes if uncontrolled. YCAs have been detected in several locations in Australia. During 2018 in New South Wales, YCAs were detected in two locations in the Lismore region. Several awareness techniques were used to gain community support and engagement in the response program. The eradication program relied on the insecticide fipronil (several formulations), and the program subsequently used surveillance data to demonstrate that eradication had been achieved. We used the scenario tree analysis with stochastic models to estimate the likelihood of eradication. We combined the results of the passive and active surveillance systems to predict a 70.4% (62.7–80.7) probability of freedom of detecting one nest, 84.4% (73.9–94.4) probability of freedom for two nests and 98% (93.1–99.9) probability of freedom for five nests. The results from the scenario tree analysis were used to inform program managers regarding the termination of the eradication and surveillance activities.

Changes in physical impairments in femoroacetabular impingement syndrome following arthroscopic surgery: a systematic review and meta-analysis

Abstract Femoroacetabular impingement syndrome (FAIS) is a motion-related condition causing hip pain in young active adults. Physical impairment measures of body function include objective and reproducible measures of hip mobility, muscle power, and movement coordination. Limited data on physical impairments and the effects of arthroscopic surgery exist. The aim of this systematic review was to investigate changes in physical impairments in those with FAIS, pre- and post-arthroscopic surgery. Six databases were searched for English-language studies reporting on pre- and postoperative physical impairments using physical outcome measures. Reporting quality was assessed using the Grading of Recommendations Assessment, Development and Evaluations (GRADE) framework, the Cochrane Risk of Bias tools and Methodological Index for Non-Randomized Studies (MINORS); for pooled data [standardized mean difference (SMD), and 95% confidence intervals (CI)]. Seventeen studies were included (two randomized controlled trials; fifteen pre/postintervention studies), varying from low-critical risk of bias, low-moderate on the MINORS, and very low reporting quality using the GRADE tool. Postoperatively, participants with FAIS walked with a higher peak hip flexion moment [SMD 0.5, 95% CI (0.12–0.88); heterogeneity I2 = 0%, P = .82] and reduced external rotation range [SMD −0.68, 95% CI (−1.34 to −0.01); heterogeneity I2 = 61%, P = .05]. Surgery increased participant hip flexion moment and impulse, hip strength and faster gluteus maximus contraction time. Patients demonstrated reduced hip extension, abduction and adduction angles during walking gait, and peak hip extension moments during gait and squatting. While this review found some physical impairments changed postoperatively, further research into specific subgroups of FAIS would enhance understanding and inform rehabilitation programs and optimize patient outcomes. Level of Evidence: IV (systematic review of III and IV evidence).

Hip microinstability in subclinical FAI professional ballet dancer: clinical case

Background. Ballet dancers have peculiarities in the morphology of the hip joints, which is determined by their professional activities. Because of this, they are more susceptible to the development of pathological conditions of joints, which often present a specific clinical picture. The aim is to describe the features of the development of structural damage to the hip joint of a ballet dancer and present the results of treatment. Methods. The patient is a professional ballet dancer, 32 years old. She noted pain and limited range of motion in the right hip joint during dance classes. There were minimal anatomical features characteristic of femoroacetabular impingement, also damage to the articular labrum of the acetabulum and structures of the anterior joint capsule on computed tomography and magnetic resonance imaging. Pain and functional status were assessed using the VAS, HOOS, iHOT-12 before surgery and after 6, 12, 18, 24, 36, 48 months. Results. Correction of bone deformity of the hip joint and all identified soft tissue damage was successfully carried out. After 5 months the patient returned to ballet dancing. According to VAS pain decreased from 6 points to 0 at control points. But slight aching pain after physical activity remained. During the follow-up, functional status was assessed as «excellent» according to HOOS and iHOT-12. However, the patient noted slight limitations in the range of motion when performing some professional exercises. Conclusion. Patients with extreme hip range of motion and hip pain require a thorough clinical evaluation to ensure correct diagnosis and appropriate treatment. Arthroscopy of the hip joint allows achieving high results, including in patients with increased functional requirements, provided that arthroscopy is planned and performed taking into account the concept of microinstability.

A hybrid harmonic polynomial cell and STF strip theory method for marine hydrodynamics and ship motion analysis

ABSTRACT This paper presents a hybrid method that combines the Harmonic Polynomial Cell (HPC) method and STF strip theory to solve marine hydrodynamics and ship motion problems. The efficient and precise HPC method is extended to three-dimensional ship hydrodynamics using STF strip theory. A new single-node hybridisation condition is introduced to enhance the stability of hydrodynamic predictions. To improve computational accuracy for complex hull shapes, automatic structured grid generation and mesh refinement techniques are applied. The hybrid HPC-STF method is then used to solve 3D ship radiation and diffraction problems in regular waves with forward speed. The method’s performance is validated through comparisons of hydrodynamic coefficients, wave forces, and motion response amplitude operators (RAOs) against experimental data and results from other numerical methods. The findings demonstrate that this hybrid approach provides accurate and effective solutions for ship hydrodynamics, making it a valuable tool for analysing marine structures and motions.

Health-related quality of life after Dega pelvic osteotomy and varus derotation osteotomy due to spastic hip disease in children with cerebral palsy.

Our study aimed to present health-related quality of life (HRQL) after combined bone reconstruction in nonambulatory patients with cerebral palsy (CP) after at least a 2-year follow-up and to assess its impact on HRQL using the Caregiver Priorities and Child Health Index of Life with Disabilities questionnaire (CPCHILD) as the primary outcome measure. In this prospective study, we analyzed 31 nonambulatory patients with spastic or mixed CP (GMFCS levels IV-V) who underwent hip reconstructive surgery between 2015 and 2021. The surgical procedures included one-sided varus derotation osteotomy of the femur with Dega transiliac osteotomy and, on the opposite side, varus derotation osteotomy (VDRO) of the femur with shortening and, as needed, Dega pelvic osteotomy. The study demonstrated significant improvement in the hip joint motion range, as assessed by the Thomas test, in hip abduction and rotational movements of the hip, as well as reduction of spasticity. The procedures also resulted in significant radiographic improvement of the femoral head coverage. The assessment of symptoms and problems associated with the hip revealed a positive influence of the surgery on pain, contractures, toileting/perineal hygiene, dressing, seating, transferring, and position changes. The mean improvement at a follow-up visit was significant in all domains of the CPCHILD, except for communication and social interaction. Hip reconstruction with VDRO and Dega pelvic osteotomy can enhance the HRQL of children with CP. These surgical interventions can help to achieve the correct hip position and to reduce pain, which positively affects the patient QL, although proactive treatment results in less invasive procedures. IV case series.

Design prognostics for 4400 TEU container vessel by multi‐variate Gaidai reliability approach

AbstractThis case study introduces an innovative multivariate methodology for assessing the lifetime of marine engineering systems, specifically in cargo vessel transportation. The analysis focused on stress data collected onboard a 4400 TEU container vessel during multiple trans‐Atlantic voyages. One of the major challenges in marine cargo transport lies in mitigating the risk of container loss due to excessive whipping loads. Accurate prediction of extreme stress levels on vessel deck panels remains difficult, primarily because of the nonlinear and non‐stationary nature of wave and ship motion interactions. Higher‐order dynamic effects, such as second‐ and third‐order responses, often become significant when ships operate under adverse environmental conditions, amplifying nonlinear influences. Laboratory simulations, constrained by wave characteristics and scale similarity issues, may not always provide reliable results. Consequently, data collected from vessels navigating extreme weather conditions serves as a critical resource for comprehensive container ship risk assessment. The primary goal of this study was to validate and demonstrate the effectiveness of a novel multivariate risk evaluation approach, leveraging onboard measurements of dynamic areal pressure on cargo ship deck panels as the core dataset. The Gaidai methodology for multivariate risk evaluation proved to be a robust tool for assessing failure, hazard, and damage risks in complex, nonlinear vessel deck panel and ship hull stress systems.

Investigation into the Prediction of Ship Heave Motion in Complex Sea Conditions Utilizing Hybrid Neural Networks

While navigating at sea, ships are influenced by various factors, including wind, waves, and currents, which can result in heave motion that significantly impacts operations and potentially leads to accidents. Accurate forecasting of ship heaving is essential to guarantee the safety of maritime navigation. Consequently, this paper proposes a hybrid neural network method that combines Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory Networks (BiLSTMs), and an Attention Mechanism to predict the heaving motion of ships in moderate to complex sea conditions. The data feature extraction ability of CNNs, the temporal analysis capabilities of BiLSTMs, and the dynamic adjustment function of Attention on feature weights were comprehensively utilized to predict a ship’s heave motion. Simulations of a standard container ship’s motion time series under complex sea state conditions were carried out. The model training and validation results indicate that, under sea conditions 4, 5, and 6, the CNN-BiLSTM-Attention method demonstrated significant improvements in MAPE, APE, and RMSE when compared to the traditional LSTM, Attention, and LSTM-Attention methods. The CNN-BiLSTM-Attention method could enhance the accuracy of the prediction. Heave displacement, pitch displacement, pitch velocity, pitch acceleration, and incoming wave height were chosen as key input features. Sensitivity analysis was conducted to optimize the prediction performance of the CNN-BiLSTM-Attention hybrid neural network method, resulting in a significant improvement in MAPE and enhancing the accuracy of ship motion prediction. The research presented in this paper establishes a foundation for future studies on ship motion prediction.

Towards Real-Time Detection of Wakes for Various Sea States with Lightweight Deep Learning Model in Synthetic Aperture Radar Images

Synthetic aperture radar (SAR) is an essential tool for monitoring and managing maritime traffic and ensuring safety. It is particularly valuable because it can provide surveillance in all weather conditions. Ship wake detection has attracted considerable attention in offshore management as it has potential for widespread use in ship positioning and motion parameter inversion, surpassing conventional ship detection methods. Traditional wake detection methods depend on linear feature extraction through image transformation processing techniques, which are often ineffective and time-consuming when applied to large-scale SAR data. Conversely, deep learning (DL) algorithms have been infrequently utilized in wake detection and encounter significant challenges due to the complex ocean background and the effect of the sea state. In this study, we propose a lightweight rotating target detection network designed for detecting ship wakes under various sea states. For this purpose, we initially analyzed the features of wake samples across various frequency domains. In the framework, a YOLO structure-based deep learning is implemented to achieve wake detection. Our network design enhances the YOLOv8’s structure by incorporating advanced techniques such as deep separation convolution and combined frequency domain–spatial feature extraction modules. These modules are used to replace the usual convolutional layer. Furthermore, it integrates an attention technique to extract diverse features. By conducting experiments on the OpenSARWake dataset, our network exhibited outstanding performance, achieving a wake detection accuracy of 66.3% while maintaining a compact model size of 51.5 MB and time of 14 ms. This model size is notably less than the existing techniques employed for rotating target detection and wake detection. Additionally, the algorithm exhibits excellent generalization ability across different sea states, addressing to a certain extent the challenge of wake detection being easily influenced by varying sea states.

Impact of Arctic Sea Ice Changes on LNG Shipping in the Context of Rising Global Energy Demand

The need for and demand for energy rises quickly as the world's population grows and economic growth quickens as well. Given the rising need for energy worldwide, liquefied natural gas, or LNG, is playing a significant role in energy transportation. Russia has a lot of gas. Russia plays a significant role in the LNG trade. The Northern Sea Route has opened due to the melting of the Arctic Sea's ice due to global warming. There is great potential for LNG transportation in the area. EViews was employed in this study to ascertain the connection between Arctic Sea ice and LNG ship movement in the NSR. The data was prepared using the Vector Autoregressive Model and the Granger Causality Test. The outcome of the analysis was the correlation between Arctic Sea ice and LNG ship traffic. LNG ship traffic in the NSR in 2023, 2024, and 2025 was estimated using the Census X-12 Method, and the 5-year (2018–2022) dataset of LNG ships departing the Russian port of Sabetta was analyzed. According to this data, by 2025, an estimated 27.03% more LNG tankers will be visiting the Russian Arctic port of Sabetta.

Impact of Contralateral Hemiplegia on Lower Limb Joint Kinematics and Dynamics: A Musculoskeletal Modeling Approach

This study investigates the biomechanical differences between typically developed (TD) individuals and those with contralateral hemiplegia (CH) using musculoskeletal modeling in OpenSim. Ten TD participants and ten CH patients were analyzed for joint angles and external joint moments around the three anatomical axes: frontal, sagittal, and transverse. The analysis focused on hip, pelvis, lumbar, knee, ankle, and subtalar joint movements, leveraging MRI-derived bone length data and gait analysis. Significant differences (p < 0.05) were observed in hip flexion, pelvis tilt, lumbar extension, and ankle joint angles, highlighting the impact of hemiplegia on these specific joints. However, parameters like hip adduction and rotation, knee moment, and subtalar joint dynamics did not show significant differences, with p > 0.05. The comparison of joint angle and joint moment correlations between TD and CH participants highlights diverse coordination patterns in CH. Joint angles show significant shifts, such as HF and LR (−0.35 to −0.97) and PR and LR (0.22 to −0.78), reflecting disrupted interactions, while others like HR and LR (0.42 to 0.75) exhibit stronger coupling in CH individuals. Joint moments remain mostly stable, with HF and HA (0.54 to 0.53) and PR and LR (−0.51 to −0.50) showing negligible changes. However, some moments, like KA and HF (0.11 to −0.13) and PT and KA (0.75 to 0.67), reveal weakened or altered relationships. These findings underscore biomechanical adaptations and compensatory strategies in CH patients, affecting joint coordination. Overall, CH individuals exhibit stronger negative correlations, reflecting impaired coordination. These findings provide insight into the musculoskeletal alterations in hemiplegic patients, potentially guiding the development of targeted rehabilitation strategies.

Design, Control, and Analysis of a 3-Degree-of-Freedom Kinematic–Biologically Matched Hip Joint Structure for Lower Limb Exoskeleton

The increasing demand for rehabilitation and walking assistive devices driven by aging populations has promoted the development of a novel hip joint structure. This design aims to enhance the functionality of lower limb exoskeletons by eliminating the kinematic mismatch with the human’s biological hip. The design utilizes three 1-DOF (Degree of Freedom) rotational joints to replicate natural hip movement. By integrating IMU data, motor compensation is dynamically made to facilitate a more natural gait. Experimental results indicate improved hip joint angles and enhanced user comfort, presenting a promising solution for better walking assistance for elderly individuals.

Shipborne comparison of infrared and passive microwave radiometers for sea surface temperature observations

Abstract. In the spring of 2021, a shipborne comparison of sea surface temperature (SST) measurements was undertaken using thermal infrared (IR) and passive microwave (PMW) radiometers. The Danish Meteorological Institute (DMI) and the Technical University of Denmark (DTU) jointly deployed two IR and two PMW instruments aboard the Norröna ferry, which traversed between Denmark and Iceland for a week. The primary objective was to assess the proximity-based comparison of IR and PMW measurements, minimizing atmospheric influences and providing valuable insights into reconciling IR- and PMW-derived SSTs. A linear regression algorithm was developed using IR SST data as a reference to derive PMW SST from brightness temperature. The data analysis primarily focused on evaluating data variability, identifying discrepancies between IR and PMW SST, and assessing the overall uncertainty in the retrieval process. The overall root-mean-square error (RMSE) of the retrieved PMW SST was 0.88 K during the ship's motion and 0.94 K when the ship was moored. The analysis of the retrieved SST uncertainty budget involved the consideration of observed quantities and a forward model, accounting for factors like instrument noise, wind speed, incidence angle, and the RMSE of skin and sub-skin temperature. The resulting uncertainty budget in the retrieved PMW SST indicated 0.53 K for the data acquired during motion and 0.3 K for data collected during a port stay. Based on the analyses of the collected data and uncertainty estimations, recommendations are offered to improve future inter-comparisons and help reconcile IR and PMW measurements.

Online Data-Driven Integrated Prediction Model for Ship Motion Based on Data Augmentation and Filtering Decomposition and Time-Varying Neural Network

Online Data-Driven Integrated Prediction Model for Ship Motion Based on Data Augmentation and Filtering Decomposition and Time-Varying Neural Network

Gender Differences in the Dynamics and Kinematics of Running and Their Dependence on Footwear.

Previous studies on gender differences in running biomechanics have predominantly been limited to joint angles and have not investigated a potential influence of footwear condition. This study shall contribute to closing this gap. Lower body biomechanics of 37 recreational runners (19 f, 18 m) were analysed for eight footwear and two running speed conditions. Presenting the effect size Cliff's Delta enabled the interpretation of gender differences across a variety of variables and conditions. Known gender differences such as a larger range of hip movement in female runners were confirmed. Further previously undiscovered gender differences in running biomechanics were identified. In women, the knee extensors are less involved in joint work. Instead, compared to men, the supinators contribute more to deceleration and the hip abductors to acceleration. In addition to differences in extent, women also show a temporal delay within certain variables. For the foot, ankle and shank, as well as for the distribution of joint work, gender differences were found to be dependent on footwear condition, while sagittal pelvis and non-sagittal hip and thigh kinematics are rather consistent. On average, smaller gender differences were found for an individual compared to a uniform running speed. Future studies on gender differences should consider the influence of footwear and running speed and should provide an accurate description of the footwear condition used. The findings of this study could be used for the development of gender-specific running shoes and sports and medical products and provide a foundation for the application of smart wearable devices in gender-specific training and rehabilitation.

Deep reinforcement learning for collision avoidance of autonomous ships in inland rivers

Due to the characteristics of large inertia, large time delay and non-linearity in ship motion, the manoeuvrability of ships is an important issue related to the safety of ship navigation. The manipulation of ships significantly affects the safety of ship navigation, and its importance will gradually increase with the development of autonomous ships (ASs). Due to the complexity of inland waterways and the density of ships, collisions are common. In this work, an autonomous learning framework with deep reinforcement learning (DRL) was constructed for ASs. The state space, action space, reward function and neural network structure of DRL were designed based on the AS's manoeuvring characteristics and control requirements. A deep deterministic policy gradient (DDPG) algorithm was then used to implement the controller. Finally, some representative route segments of an inland waterway were selected for simulation research based on a virtual simulation environment. The designed DRL controller was able to quickly converge from the training and learning process to meet the control requirements. The effectiveness of the DDPG algorithm was verified by comparisons with the experimental results. This study provides a reference for future research on collision-avoidance technology for ASs in inland rivers.

The Characteristics of Methylsiloxane Distribution in the Marine Surface Sediment, Masan Bay, Korea, in August 2018 and Suggesting Directions for Further Studies

The present study determined the distribution of fifteen methylsiloxane compounds (total methylsiloxanes, TMSs), including four cyclic (CMSs) and eleven linear (LMSs), in the marine surface sediment of Masan Bay, Korea, in 2018. The levels ranged from 76.6 to 2320 (median 264 ± 680), 5.00 to 3570 (median 359 ± 1310), and 81.6 to 5890 (median 607 ± 1940) ng/g-dw., in ΣCMSs, ΣLMSs, and ΣTMSs, respectively. The CMSs: LMSs ratio was 34:66, and the most dominant compound was D5 (27%), followed by L11 (22%) and L12 (20%). Principal component and cluster analyses categorized the ten sampling points into four groups based on the point sources: Group A (MS1) representing the industrial wastewater from the Changwon National Industrial complex; Group B (MS2) representing the ship movements; and Groups C (MS3, MS5, MS6, and MS7) and D (MS4, MS8, MS9, and MS10) representing the organic carbons. The present study hypothesized that the missing link between the methylsiloxane levels in 2013 and 2021 was due to the considerable industry recession in the bay. This was verified by positive correlations between the median ΣCMSs and the monthly production, the median ΣLMSs and ΣTMSs and the monthly employment in the complex. However, the hypothesis should be supplemented with the following perspectives: (1) selecting the sampling areas representing only the industrial wastewater, (2) considering the seasonal fluctuations, (3) estimating half-lives, and (4) investigating time series. This study is the first to link methylsiloxane levels and social issues in the bay, providing insights into illuminating the distribution characteristics of various pollutants.

Time-Delay-Based Sliding Mode Tracking Control for Cooperative Dual Marine Lifting System Subject to Sea Wave Disturbances

Dual marine lifting systems are complicated, fully actuated mechatronics systems with multi-input and multi-output capabilities. The anti-swing cooperative lifting control of dual marine lifting systems with dual ships’ sway, heave, and roll motions is still open. The uncertainty regarding system parameters makes the task of achieving stable performance more challenging. To adjust both the attitude and position of large distributed-mass payloads to their target positions, this paper presents a time-delay-based sliding mode-tracking controller for cooperative dual marine lifting systems impacted by sea wave disturbances. Firstly, a dynamic model of a dual marine lifting system is established by using Lagrange’s method. Then, a kinematic coupling-based cooperative trajectory planning strategy is proposed by analyzing the coupling relationship between the dual marine lifting system and dual ship motion. After that, an improved sliding mode tracking controller is proposed by using time-delay estimation technology, which estimates unknown system parameters online. The finite-time convergence of full-state variables is rigorously proven. Finally, the simulation results verify the designed controller in terms of anti-swing control performance. The hardware experiments revealed that the proposed controller significantly reduces the actuator positioning errors by 83.33% compared with existing control methods.

Study of a Cable‐Driven Hip Swimming‐Assisted Exoskeleton Utilizing Adaptive Active Control Strategy

ABSTRACTThe power‐assisted exoskeletons have a far‐reaching research significance. The adaptive active control strategy (AACS) of the exoskeleton allows the wearers to achieve personalized assistance tailored to their specific movement patterns and physical needs. However, due to the high requirements for waterproof design and the high difficulty in underwater AACS design, the researches on underwater power‐assisting exoskeletons are hardly to be seen. Therefore, this research proposes a cable‐driven hip swimming‐assisted exoskeleton (SAE) utilizing an AACS. SAE can generate adaptive power‐assisting guiding trajectories of thighs by underwater motion intention perception (UMIP) of the wearer. To achieve UMIP, a deep learning network is presented by combining conventional neural network, bidirectional long short‐term memory network, and attention mechanism (AM‐Dconvbilstm). SAE guides the wearer's thighs to move along the generated guiding trajectory by UMIP through the cables to conduct hip power assisting. The feasibility of the proposed AM‐Dconvbilstm on UMIP and the power‐assisting effect of designed SAE are tested on three elite swimmers by recording corresponding data from IMUs and a sports watch. According to the results of generated trajectories from SAE and actual trajectories from the wearer, the proposed AM‐Dconvbilstm model is verified to predict the wearer's hip motion intention accurately. The power‐assisting effect of SAE is also verified according to the sports watch's heart rate and average energy consumption. All the experiment results greatly validated the feasibility of the proposed AACS and designed SAE.

Identification of Ship Domain Shape to Degree of Ship Collision Risk on Head-on Encounter Situation

Abstract Ship collisions are one of the marine accidents that can occur at any time, causing significant material and cargo losses. Lack of awareness of collision impacts and human factors are primary issues for ship collisions. Consequently, ship captains and technology have devised an imaginary area known as the ship domain. This ship domain is an imagined region used to define safe conditions around the ship. With the presence of a ship domain, collision risk can be reduced. This paper investigates the influence of ship domains on collision risk assessment during head-on encounters. To simulate realistic ship movement conditions, the manoeuvring mathematical group (MMG) model is used to predict ship movements. Additionally, fuzzy logic calculations and the closest point of approach (CPA) are employed to help identify the effectiveness of ship domains. Numerical simulations are conducted using three different ship domain shapes: egg, circle, and ellipse. The results indicate that the shape of the ship domain does not significantly influence collision risk assessment in head-on encounters. Instead, the division of the ship domain plays a more crucial role in evaluating ship collision risk.