Due to the complex internal layout of passenger ships, the large number of passengers, and the presence of designated assembly points, route selection during evacuation onboard ships has increasingly become a crucial factor affecting the overall evacuation process. However, variations in passengers’ risk perception and the heterogeneity of passenger groups often lead to marked differences in exit choice behaviour. To clarify the relationship between passengers’ exit choice behaviour and influencing factors, the Double Machine Learning (DML) method is employed in this study with optimisation of the nuisance function applied to identify key factors affecting exit choice from a causal inference perspective. First, 1380 valid questionnaires are collected from passengers on ferry routes in the Bohai Bay area, covering essential dimensions such as individual attributes, behavioural preferences, and evacuation decision-making. Second, feature selection and model optimisation are conducted based on this dataset to construct a nuisance function with optimal average out-of-sample prediction performance. Finally, the DML approach is employed to conduct a causal effect analysis of exit choice behaviour, allowing for the systematic identification of key influencing factors. The findings indicate that alarm response and decision-making under congested conditions are identified by the DML as having significant causal impacts on exit choice. It is shown that relying solely on correlational analysis may lead to strategic misjudgements, whereas the application of causal inference enables more accurate identification of priority intervention targets.

This study develops a data-driven analytical framework that integrates causal inference with hierarchical analysis to reveal the underlying mechanisms influencing ship fuel consumption (SFC). The framework combines multi-source data fusion, direct linear non-gaussian acyclic model-based causal discovery, and double machine learning with causal forests model to estimate Average Treatment Effects (ATEs), followed by interpretive structural modelling for hierarchical decomposition. Experimental results under the expanded DAG-derived adjustment specification indicate that Daily sailing hours has the strongest positive conditional effect on SFC (ATE = 2.058), followed by Main engine RPM with a positive but more uncertain effect estimate (ATE = 0.268). The hierarchical analysis further organises the directional-dependence network into interpretable structural levels, thereby illustrating possible multi-level transmission patterns among operational and environmental factors. This framework provides an exploratory and graph-informed analytical basis for interpreting directional dependencies and observed-covariate conditional effect patterns in SFC, offering cautious decision support for data-driven energy management. The source code is publicly available at: https://github.com/AdvMarTech/ship_ fuel_consum_causalinfer.

During the entire process of collision avoidance, conducting appropriate collision risk analysis is crucial for making effective decisions and ensuring maritime navigational safety. However, present studies on collision avoidance decision-making frequently fail to adequately address the significance of risk relevance and the coordination of actions, especially in complex multi-ship encounter situations. To overcome such limitations, a hierarchical conflict resolution strategy for collision avoidance in multi-ship encounter scenarios is proposed, which not only significantly reduces the complexity of multi-ship collision avoidance, but also has a better compliance with navigation practice. To this end, by combining Gaussian fitting, average link hierarchical clustering as well as silhouette coefficient, a conflict connectivity analytical method is proposed to help distinguish different clusters. In order to accurately acquire the action sequence in each cluster, the entropy weight method is adopted to standardize the collision risk index by reasonably assigning weights. Ultimately, a hierarchical conflict resolution mechanism is introduced to facilitate efficient and coordinated collision avoidance decision-making. The simulation results highlight that the proposed mechanism exhibits significant advantages in various maritime environments.

With the increasing use of passenger ships in passenger transport and tourism sighting, the risk of evacuation accidents is higher. To prevent such accidents and reduce casualties, a quantitative analysis method for identifying and evaluating risk influential factors (RIFs) of evacuation accidents is developed by integrating complex network (CN), decision-making trial and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) methods. Firstly, 27 RIFs are identified by extracting accident casual chain from global emergency evacuation reports of large passenger ships, and a network model for evacuation accidents is constructed. Secondly, CN is used to conduct a topological analysis of these identified RIFs from a global perspective, and robustness analysis under different attack modes is used to validate the ranking of these RIFs. Finally, DEMATEL and ISM are used to establish a multilayer structure model, 12 key RIFs are identified from causal relationship and structural perspectives, and countermeasures are proposed to mitigate these RIFs. By identifying these key RIFs, this study aims to deepen the understanding of evacuation risk management, provide a theoretical basis for emergency decision makers, optimize the evacuation process, and reduce casualties.

It is vital to effectively quantify the human movement parameters in rolling ships to save lives in maritime emergency and/or accidents. This study aims to develop a new two-layer social force model (2LR-SFM) to improve human evacuation efficiency in rolling ships. Firstly, the forces acting on humans are analysed in terms of physical forces, psychological adjustment, and inertial analysis, and the three-dimensional human moving process is described by a modified model. Secondly, the individual’s velocity and acceleration are calculated at each time step according to the walking direction, rolling amplitude, and rolling period. Thirdly, the accuracy of the human walking speed attenuation in 2LR-SFM simulation is verified by using the velocity data collected from real ship experiments. Finally, simulations are carried out in the dining room of a ship to reveal the human movement patterns in different rolling scenarios. The results reveal that the simulation process of 2LR-SFM satisfies the basic rules of human evacuation. With the increase of rolling amplitude, humans are more affected by the rolling motion, resulting in exponentially increased evacuation time. This study enables to simulate the evacuation process under different rolling scenarios and hence realizes a dynamic analysis for the first time in the area.

It is crucial to understand the movement characteristics and behaviour of individuals during ship emergencies for successful human evacuation on board ships. This study aimed to analyse the effect of heeling angles on human movement characteristics and comprehensive evacuation efficiency on passenger ships through the development of a new experimental dataset of human evacuation. To achieve this, a series of tests were conducted using an experimental simulator closely resembling the evacuation scenarios recommended by the International Maritime Organization (IMO). It is revealed that a heeling angle significantly reduces both walking and running speeds of participants. Notably, when the heeling angle is 16°, males demonstrated better adaptability as their speed was less affected compared to females. Additionally, height is found to be positively correlated with movement speed across different scenarios. In counter flow tests, a comprehensive evacuation experiment was systematically quantified. The results showed that evacuation time increased with higher heeling angles. Furthermore, participants tended to maintain a larger personal space in a heeling ship, resulting in lower density when the heeling angle reached 16° compared to other scenarios. The outcomes of this study offer valuable insights for validating evacuation models and developing guidelines for human evacuation from passenger ships.

When a ship accident occurs, emergency evacuation of passengers in a shorter time is one of the most effective means of reducing casualties. However, in addition to the ship inclination, the efficiency of the emergency evacuation can be affected by human behavior (e.g., competitive behavior), which affects human moving speed. Therefore, to analyze the impact of competitive behavior during ship evacuations, a dynamic evaluation system is developed to measure nested competitive behavior. Firstly, the perceived area is obtained by dividing the pedestrian visual perspective, which is used to calculate crowd density at every time step. Secondly, fuzzy logic is used to calculate the real-time competitive degree based on the inclined angle and crowd density, integrated into the human evacuation model as an input parameter to update competitive behavior. Finally, this study analyzes and evaluates evacuation time and efficiency with different proportions of competitive people at different inclined angles, using a dining room on a ship as a case study. The results show that without ship inclination, the total evacuation time decreases with an increase of the proportion of competitive people as more competitive people can accelerate the evacuation process. However, the inclination of a ship leads to a decrease in human walking speed, congestion at the exit, and a slower overall evacuation process. According to the findings of this study, an appropriate increase in the proportion of competitive humans is beneficial to the efficiency of emergency evacuation, while strengthening the guidance at the exit will also reduce the evacuation time.

As the receiving terminal of liquefied natural gas (LNG), the efficient emergency response of the floating storage and regasification unit (FSRU) is crucial to ensure the safety of LNG transportation at sea. However, few existing literature study the risk issues of FSRUs during emergency operations. In order to improve the emergency response capability of FSRU, this study proposes an innovative assessment method to identify hazards, quantify and rank the risks associated with emergency response and disposal operations of FSRU accidents. Firstly, a comprehensive index hierarchy system applicable to human, equipment, environment, and management aspects of emergency response and disposal operations of FSRU accident is established through an extensive literature review, analysis of accident reports, and expert judgments. Secondly, based on the concept of Intuitionistic Fuzzy Numbers, the Intuitionistic Fuzzy Hybrid Weighted Euclidean Distance (IFHWED) operator is used to enhance the conventional FMEA approach. This method considers the varying levels of expert confidence and integrates subjective and objective weights of risk influential factors (RIFs), and the efficacy is validated through sensitivity analysis. Finally, a comprehensive evaluation model employing the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation algorithms is used to aggregate the risk values of RIFs. The findings of this study offer decision-makers insights into risks during emergency operation, provide valuable guiding strategies for FSRU accident management, and improve the capability for emergencies at sea.

With the widespread application of ship Automatic Identification System (AIS) in maritime operations, a large number of ship trajectories become available. This study aims to improve the safety of ships navigating through densely trafficked areas and address the challenge of sufficient data exploration while fully describing the traffic conditions in these waters. To achieve this objective, traffic flow information is extracted from AIS data collected in Zhoushan waters. A combination of multi-algorithms is employed to extract the traffic flow frame, specifically, the Douglas-Peucker compression algorithm and trajectory intersection algorithm are utilised to identify the characteristic points of ship trajectories. Subsequently, a density clustering algorithm is applied to extract the three types of characteristic points: compressed trajectory points, intersection points, and ship position points, facilitating data mining efforts. The resulting initial traffic flow characteristic points are then subject to weighted fusion, followed by image superposition processing to create an overlapping map of the ship trajectories. This process culminates in the generation of a traffic flow frame for the region. The framework integrates various track characteristic points, offering insights into the distribution of essential routes in the vicinity waters, thereby providing a comprehensive depiction of ship traffic flow patterns. The proposed framework can be applied to the route planning and serve as a reference to the maritime authorities when selecting recommended shipping lanes.

Due to the constraints of various factors influencing human evacuation on board, it remains a challenging problem to accurately quantify the impact of these factors on the evacuation process. To analyse the multiple influential factors of human evacuation from ships, a specific framework based on orthogonal experiments is proposed in this paper to comprehensively investigate the impact of multiple factors on the evacuation time and the efficiency of the evacuation process. Heeling angles, unavailable stairs, and priorities of evacuees are identified as influential factors according to the characteristics of human evacuation from ships. The analysis results show that the heeling angle has a very significant effect on both evacuation time and efficiencies, and the efficiencies decrease as the heeling angle increases. Unavailable stairs also have a significant effect on evacuation results, the magnitude of which depends on the number of stairs nearby. While the effect of priorities of evacuees on evacuation results is relatively less important, it can be found that priority evacuation of pedestrians with impaired mobility will aid to achieve optimal evacuation results. In conclusion, the findings of this study can help managers quickly develop effective evacuation strategies in emergencies to further improve the safe operation of passenger ships.

The emergency scenarios of passenger ships are reproduced unrealistically by evacuation drills due to cost and safety limitations, and model simulation is an effective alternative method. To study the evacuation efficiency of an inclined ship, a deck of a Ro-Ro ship with 1065 passengers was modeled on a simulation platform developed based on a social force model (SFM). A series of inclined scenarios were produced by adding the walking speed attenuation factor to the individual parameters. Furthermore, the influence of crew’s guidance was considered in this model, and the effects on evacuation were also analyzed for the entire deck. The simulation results show that the larger the inclination angle is, the more evacuation time that is needed. When the largest inclination angle was 20°, the evacuation time increased by 32.6%. In addition, the participation of crew’s guidance in all of these scenarios significantly accelerated the evacuation efficiency, and this benefit was achieved by the evaluation of the exit flow and congestion level by crew. However, organizing orderly evacuations as soon as possible when the inclination angle is less than 15° and making maximum efforts to ensure evacuation success are still recommended. The findings provide useful insights into a large group of Ro-Ro passenger vessels under inclined emergency evacuation.

In maritime transport, evacuation, escape and rescue play a crucial role in protecting people's lives when a passenger ship is involved in a serious accident. The study aims to develop a new method to identify hazards, quantify and rank the associated risks in the process of Human Evacuation from Passenger Ships (HEPS). Firstly, based on extensive literature review and marine accident investigation reports, the risk factors affecting passenger ship evacuation were analysed and identified, and an analysis framework based on Human, Ship, Environment and Organization (HSEO) for HEPS was proposed. Secondly, a risk assessment model was proposed to quantify and rank risk factors in the process of HEPS. Finally, a large-scale evacuation drill of a cruise ship was taken as a case study to demonstrate the applicability of the proposed evaluation model, and accuracy of the results. The results reveal that (1) evacuation decision, operation of Life-Saving Appliances (LSAs) are the main risks affecting the safety of HEPS; (2) the behaviours of passengers have a relatively lower risk priority; and (3) future HEPS research should focus on the development of a multi-attribute decision system to address the issue on when to evacuate and when to abandon a ship.

为研究船舶横摇对行人疏散速度的影响,通过计算行人在横摇运动空间中不同维度的受力,依据实时更新的横摇角度和角速度,建立一种考虑船舶横摇运动的三维动态社会力模型.以横摇幅度和横摇周期为变量,设置多场景的仿真实验,计算行人平均运动速度和疏散时间,分析不同横摇状态下的行人运动规律.仿真结果表明:相较静态倾斜,船舶横摇进一步导致行人移动速度衰减及疏散进程延缓,随着横摇幅度增大,行人速度不断降低,横摇幅度超过15.后,疏散时间迅速增加;增大船舶横摇周期对疏散过程有一定的积极影响,可以有效提升人员行走速度,减少疏散时间,但其影响程度仍与横摇幅度有关;在相同横摇幅度情况下,当横摇周期达到10 s及以上时,疏散效率可以显著提高.研究结果可为设计人员提升船舶安全性和管理者制定人员疏散决策提供理论依据和技术支撑.

船舶人员疏散可有效保障紧急情况下的人员生命安全,而船舶在事故后的倾斜状态会使人员疏散面临新的挑战.通过梳理和总结人员运动特征、人员疏散行为、仿真建模三个方面的研究进展,得到船舶倾斜状态下人员紧急疏散关于运动特征的提取、人员心理的量化、仿真建模研究的验证等瓶颈问题.未来的研究应该以完善人员疏散特征实验、改进现有疏散模型、分析人员的可能性疏散行为为目标,以结合船舶人员疏散特点,提出优化的船舶布局和疏散方案,保证在船舶倾斜状态下人员能迅速安全地撤离.

In order to consider the impact of fires at different locations in ship on the human evacuation process in an emergency situation, the living deck of a training ship was used as the experimental framework, and Pathfinder was used to simulating the evacuation process. In the simulation scenarios, the unavailability of a single exit due to an accident was taken into account, and three indicators were adopted to analyze the impact of each exit on the efficiency of evacuation. The results showed that the occurrence of fire at the widest exit (exit 3) has the greatest impact on performance, and the congestion is the key restricting factor of evacuation onboard. However, the evacuation time decreased on the contrary when exit 3 undertaking heavy tasks was closed. Accordingly, when another exit near exit 3 was closed, exit 3 should take more tasks and the evacuation time increased sharply. Based on the simulation results, the types of stairs can be optimized from a scientific perspective to alleviate congestion, and the evacuation efficiency and process can be greatly improved.

Efficient identification of multi-ship encounter situation concerning action priority analysis is of vital significance for making effective and practical collision avoidance manoeuvres. However, action priority analysis is strongly involved in conflict urgency quantification, collision candidates relevance analysis as well as the contribution analysis within the encountering ships. In this paper, considering Maritime Autonomous Surface Ship, a deterministic collision avoidance decision-making system is established to estimate multi-MASS encounter situation. To this end, the approach index and asymmetrical Gaussian fitting method are deployed to assess collision risk, while the encountering ships are analytically distinguished into different clusters based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. By virtue of the improved Sharpley value method, the collision avoidance action priority is elaboratively sorted for different clusters. Accordingly, each individual collision avoidance manoeuvres are collaboratively generated by the modified velocity obstacle algorithm with certain time delay. Eventually, the proposed decision-making system is synthesized by functional modules including data-processing, conflict assessment detection, relevance analysis, action priority analysis, path planning and performance monitor. Simulation results demonstrate that this proposed decision-making system can perform significant superiority in various maritime environment in line with the practice of coordination and navigation.

Passenger vessels often present different heeling and/or trim angles during and after accidents, while recognising it as the main factor affecting pedestrian movement during an emergency evacuation process, there is difficulty to reproduce the evacuation activities on ships due to cost constrains and safety concerns in relevant studies. To fill the research gap, an improved social force model (SFM) incorporating both inclining and self-adjusting forces of pedestrians into the basic SFM model was constructed to simulate the pedestrian dynamics under different ship trim and heeling circumstances. The improved SFM also includes a reduction law of pedestrian speed at different heeling and/or trim angles and adds a calculation of the reduction factor in each time step. It enables the simulation of the pedestrian movement process on inclined vessels accurately. The simulation results show that when the inclination angle is less than 20°, the impact of both heeling and/or trim on an individual’s walking speed and evacuation time are weaker than the one with an angle exceeding 20°. When passengers walk along the keel line on an inclined ship, the impact of heeling on speed attenuation is more significant than the one of trim. The overall evacuation time is extended with the increasing number of evacuees. The flow rate at the exit reaches the maximum when the number of evacuees is 100, and the average evacuation rate is 2.01 persons/s. The findings provide useful insights on crowd management in the process of passenger vessel evacuation under an inclined state.

为研究船舶倾斜对船上人员疏散过程的影响,在基础社会力模型中引入行人倾斜力和自调整力,构建一种考虑船舶倾斜状态的改进社会力模型,通过比对前人实验结果验证模型的有效性.增加行人视角范围,确定周围行人作用的有效范围;结合MATLAB仿真单向、对向、交叉和多向行人流场景,分析不同倾斜状态对行人疏散速度的影响,并拟合疏散时间随倾斜角度变化规律.仿真结果表明:船舶倾斜角小于15°的情况下,行人速度会有小幅下降,但对整体疏散过程影响不大;当倾斜角超过15°时,行人行走速度会迅速下降,整体疏散时间也会急剧增加,并与倾斜角度呈六次关系变化.基于此,船舶倾斜状态下的最佳疏散时机为倾斜角小于15°.

为了解楼梯布局对客船人员疏散效率的影响,基于烟台—大连的滚装客船的人员组成和船舶熟悉程度的调查结果,利用FDS+EVAC建立客船疏散仿真模型,通过设置不同的楼梯布局方案,计算疏散时间和疏散效率.结果显示:在客船的主楼梯上增加间隔扶手可以有效分散人流,提高主楼梯处的人员疏散效率,缓解拥堵现象;但是,在主楼梯处增加间隔扶手过多,反而导致总体疏散时间变长.考虑到建造成本和人员行走的便捷性,建议在主楼梯处增加1个间隔扶手.本文建立的客船疏散模型可供识别现有客船几何布置的拥堵点,优化船舶楼梯设计,提高客船人员疏散效率.

考虑船舶人员疏散的特点,对不同的人员折返比例对船舶疏散过程的影响运用Pathfinder软件进行仿真分析,疏散实验结果表明,随着人员折返比例的增大,疏散时间迅速增加,人员在出口附近的走廊处出现拥堵现象;在人员折返比例为40％时,折返行为对疏散效率的影响最大,对船舶布置进行优化后,疏散效果得到改善,疏散时间明显减少,拥堵程度得到缓解.