Most maritime accidents are caused by human errors or failures. Providing early warning and decision support to the officer on watch (OOW) is one of the primary issues to reduce such errors and ...failures. In this paper, a quantitative real-time multi-ship collision risk analysis and collision avoidance decision-making model is proposed. Firstly, a multi-ship real-time collision risk analysis system was established under the overall requirements of the International Code for Collision Avoidance at Sea (COLREGs) and good seamanship, based on five collision risk influencing factors. Then, the fuzzy logic method is used to calculate the collision risk and analyze these elements in real time. Finally, decisions on changing course or changing speed are made to avoid collision. The results of collision avoidance decisions made at different collision risk thresholds are compared in a series of simulations. The results reflect that the multi-ship collision avoidance decision problem can be well-resolved using the proposed multi-ship collision risk evaluation method. In particular, the model can also make correct decisions when the collision risk thresholds of ships in the same scenario are different. The model can provide a good collision risk warning and decision support for the OOW in real-time mode.
The safe and efficient navigation of ships traversing the Northern Sea Route demands accurate information regarding sea ice concentration. However, the sea ice concentration forecasts employed to ...support such navigation are often flawed. To address this challenge, this study advances a statistical interpolation method aimed at reducing errors arising from traditional interpolation approaches. Additionally, this study introduces an autoregressive integrated moving average model, derived from ERA5 reanalysis data, for short-term sea ice concentration forecasts along the Northern Sea Route. The validity of the model has been confirmed through comparison with ensemble experiments from the Coupling Model Intercomparison Project Phase 5, yielding reliable outcomes. The route availability is assessed on the basis of the sea ice concentration forecasts, indicating that the route will be available in the upcoming years. The proposed statistical models are also shown the capacity to facilitate effective management of Arctic shipping along the Northern Sea Route.
Tianjin Port is one of the largest ports in northern China. Liquefied natural gas (LNG) ships are one of the most special ship types, and their navigation safety and efficiency has become the top ...concern of the port authority. There are two LNG berths at the port, and the annual arrivals, which reach more than 100, increasingly influence other ships. The objective of this study is to evaluate the influence of LNG ships on other ships in a quantitative way. To realize this, a simulation system is established by analyzing the factors affecting waterway transit efficiency. The software Arena is adopted to simulate the arrival and departure of the ships at Tianjin Port and to simulate how the average waiting time and the average queue length in the port area are affected by the LNG ships. A traffic system for the two ship types is formulated, and the mutual influences between them are expressed by the inbound and outbound waterway states. The simulations are performed under both existing and new ship traffic regulations. Cases in which the number of LNG ships gradually increases are simulated comprehensively. The simulation model as well as the results can serve as a good reference for the local port authority in the formulation of traffic regulations.
Traffic conflicts between ships are one of the most important reasons causing delays in restricted waterways. Aiming to improve the traffic efficiency, a hybrid self-organizing scheduling (HSOS) ...method for restricted two-way waterways is proposed. Ship transportation system is treated as a distributive and self-organized system under uncertainties. Each ship makes the decision on when to enter the waterway and how to keep the safe distance between them, while the VTS center could manage the direction of traffic flow according to the navigation situations. In order to reduce the traffic conflict between the opposite directions, small ships are given higher priority than the large ships in the same direction. When the large ships are accumulating, they are given higher priority than small ships in the same direction. The large ships are delayed while small ships decrease the waiting time. The trade-off between small and large ships can enhance efficiency by accumulating the large ships. Comparing the results from HSOS with First Come First Served (FCFS), it can effectively reduce the average delays brought by large ships, especially at high arrival rates.
Ocean-crossing ship structures continuously suffer from wave-induced loads when sailing at sea. The encountered wave loads cause significant variations in ship structural stresses, leading to ...accumulated fatigue damage. Where large inherent uncertainties still exist, it is now common to use spectral methods for direct fatigue calculation when evaluating ship fatigue. This paper investigates the use of a machine learning technique to establish a model for 2800TEU container vessel fatigue assessment. Measurement data from 3 years of cross-Atlantic sailing demonstrated and validated the machine learning model. In this investigation, the ship’s motions were used as inputs to build a machine learning model. The fatigue damage amounts predicted using a machine learning model were compared with those obtained from full-scale measurements and direct fatigue calculation. The pros and cons of the methods are compared in terms of their capability, robustness, and prediction accuracy.
Qinzhou Port is one of the most important ports in the “Beibu Gulf” of China. It is also the main hub port of the "21st century maritime silk road" strategy. Based on a basic collision risk ...assessment approach, an Event Sequence Diagram (ESD) model that explains the four-stage collision avoidance decision-making procedure is proposed from the perspectives of perception, cognition, decision, and execution. Using the historical data derived from collision accident reports from the Qinzhou Port waters from 2013 to 2017, as well as the data elicited from expert knowledge, a quantitative evaluation of probability distributions of different collision failure modes is performed. The results are also compared with relevant results from other types of navigation waters to analyse collision risk level of Qinzhou waters. At the same time, the main failures paths of collision avoidance decision making are identified. The proposed model can provide with an overall collision risk picture from a macro perspective.
•The ship encounter identification model is formed based on AIS historical data.•A two-stage collision avoidance behavior extraction algorithm is constructed to obtain the collision avoidance ...scheme.•A novel path planning method is established by fusion the collision avoidance trajectory in similar scenarios.
AIS data include ship spatial-temporal and motion parameters which can be used to excavate the deep-seated information. In this article, an interpretable knowledge-based decision support method is established to guide the ship to make collision avoidance decisions with good seamanship and ordinary practice of seamen using AIS data. First, AIS data is preprocessed and trajectory reconstructed to restore the ship historical navigation state, and a ship encounter identification model is constructed according to the encounter characteristics; Second, a two-stage collision avoidance behavior extraction algorithm is formed to build a behavior knowledge base, and the scenario similarity model is constructed to measure and match similar scenarios based on ship position, motion tendency and collision risk. Then, the Delaunay Triangulation Network is used to fuse ship trajectories of similar scenario to form the collision avoidance path. Finally, a case study is performed using the real AIS data outside Ningbo-Zhoushan Port waters, China, and the effectiveness of the planned path is verified by setting the head-on and crossing situations and comparison between the planned and real paths. Results indicate that the proposed model can extract the ship collision avoidance behavior accurately, and the planned path can ensure navigation safety.
Nonlinear equation systems (NESs) are common in practical applications, and solving them is an important task in numerical computation. Evolutionary algorithms (EAs) for handling NESs have received ...considerable attention. EAs generate a large amount of data, which reflect the evolutionary behavior. However, there are still deficiencies in the mining and use of these data. Inspired by the ability of humans to acquire knowledge from past historical experience, this paper proposes a knowledge-learning-and-transfer-aided hybrid niching-based differential evolution (HNDE/KLT). HNDE/KLT aims to acquire knowledge from historical experiences and use them to guide the evolution. The HNDE/KLT include two main features: i) artificial neural networks are embedded in EAs, so the algorithm can learn from successful historical evolutionary information and obtain the relationship between the current individual’s position and the optimal evolutionary direction; ii) a knowledge-transfer-based technique is designed to perform information exchange between different subpopulations, enhancing exploitation efficiency. Experimental results show that the HNDE/KLT can better solve NESs, indicating that learning plus transfer can make problem solving more intelligent. Additionally, we employed our algorithm to solve two real-world problems, and obtained good results.
Trajectory planning for working ships within offshore wind farms is significant for navigation safety and efficiency. Regarding to this, a global multi-direction A* algorithm is introduced. The ...algorithm is modified from three perspectives: (1) Artificial potential field (APF) is expressed in scalar mode instead of vector mode; (2) The moving distance in each step is adjusted based on the complexity of the around environment; (3) The penalty mode is proposed for the subsea pipelines. The scalar APF model avoids ships crossing between the two obstacles very close to each other, which is very important in dense wind turbine waters. The adjusted stepping mode can extend possible moving directions compared with conventional A* algorithm while making a trade-off between computation complexity and efficiency. The penalty model plays an effective role, so that the planned trajectory is crossing the pipelines only once. Simulation results indicate that the trajectory from 20-direction A* algorithm has similar path length with real cases while enhancing navigation safety to a large degree. Compared with the real-case trajectory, the minimum distance to the wind turbines has increased more than 3 times and the path length outside the wind farm decreased from more than 16000m to less than 11000m.
Ship meteorological path planning has received increasing attention, especially in the dynamic wind, wave, and current environments. Determining a safe and efficient voyage path is one of the most ...important issues for ships. In order to reduce the navigation costs in terms of distance, energy, and time under multiple constraints, a novel ship path planning method is proposed in a spatially-temporally variant environment, which can find the optimum paths under different task requirements. An improved A* algorithm in a dynamic current environment (A*-DCE) is proposed, which introduces the weights of distance, energy, and time to generate paths with significantly different costs. The attractive/repulsive field replaces the distance cost estimation of the conventional A* algorithm. The grid map is segmented based on velocity data to determine energy and time cost estimations. Under the varied spatial-temporal current environment in the Nw-European Shelf region, the B-spline curve is used to improve the smoothness and to reduce the yaw cost. In addition, the paths in the candidate set that conform to the Pareto front are obtained using the NSGA-II algorithm. The smallest distance path has the same distance-optimal capability as the path from the conventional A* algorithm. The energy and time cost of the remaining optimal paths are also reduced.
•An improved A* method in dynamic current environment (A*-DCE) is proposed, which introduces the weights of distance, energy and time to generate three paths with significantly different costs.•The attractive/repulsive field is used to replace the distance cost estimation of conventional A*.•B-spline curve is used to improve the path smoothness and to reduce the yaw cost. In addition, the paths in the candidate set that conform to the Pareto front are obtained using the NSGA-II.
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