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In the last few years, autonomous ships have attracted increasing attention in the maritime industry. Autonomous ships with an autonomous collision avoidance capability are the development trend for future ships. In this study, a ship manoeuvring process deduction-based dynamic adaptive autonomous collision avoidance decision support method for aut...
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... The CRI is a crucial physical quantity that quantifies the urgency of avoiding collisions between ships, which is determined by various factors such as the relative velocity, bearing, and distance between the two ships (Zhang et al. 2022). The CRI serves as a valuable tool to assess collision urgency in different scenarios and contribute to determining priorities during multi-ship collision avoidance situations. ...
... Zhang et al. (2021) proposed a novel collision avoidance trajectory search and optimisation algorithm, which can effectively generate free collision avoidance trajectories, realise multi-ship real-time collision avoidance in uncertain environments. Additionally, based on the ship manoeuvring process, combined with the recovery navigation model, Zhang et al. (2022) proposed an adaptive autonomous collision avoidance scheme for MASS, which can make MASS return to its original course after completing the collision avoidance task. Liu et al. (2022b) proposed a fuzzy logic-based multi-model spatial data fusion and accident data mining approach to trajectory risk perception and developed a risk perception system. ...
To address human errors in collision avoidance tasks of remotely controlled ships, this study aims to develop a comprehensive framework for human error analysis within the context of autonomous ships. Firstly, the Hierarchical Task Analysis method is utilized to identify crew collision avoidance tasks associated with the traditional ship, and these tasks are then dissected into different operational stages using the Information Decision Action in a Crew cognitive model. Secondly, a combination of the fault hypothesis method and expert opinions are used to identify potential human error that may occur during collision avoidance operations of remotely controlled ships. Thirdly, an integrated approach is proposed to build a quantitative risk assessment model, which combines Failure Mode and Effects Analysis, Evidential Reasoning, and Belief rules-based Bayesian Network. Then, axiomatic analysis is used to verify the robustness and applicability of the risk assessment model. Finally, based on the results of quantitative risk assessment, specific measures are proposed for enhancing the safety of collision avoidance process of remotely controlled ships. The findings show that uncoordinated interactions of human-computer systems during the decision-making stage are a pivotal factor in the collision avoidance process. Therefore, future design efforts for remote-control centre should prioritize improving the clarity of human-computer interaction interfaces.
... Zhang et al. [62][63][64] proposed an autonomous decision-making model for complex encounter situations of multi-ship based on the deduction of ship maneuvering process, model predictive control (MPC), modified velocity obstacle (VO) algorithm, and grey cloud model. Wang et al. [65] employed the Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning algorithm to address the coordinated control problem of unmanned surface ships (USVs) regarding speed and heading. ...
Sorting out the requirements for intelligent functions is the prerequisite and foundation of the top-level design for the development of intelligent ships. In light of the development of inland intelligent ships for 2030, 2035, and 2050, based on the analysis of the division of intelligent ship functional modules by international representative classification societies and relevant research institutions, eight necessary functional modules have been proposed: intelligent navigation, intelligent hull, intelligent engine room, intelligent energy efficiency management, intelligent cargo management, intelligent integration platform, remote control, and autonomous operation. Taking the technical realization of each functional module as the goal, this paper analyzes the status quo and development trend of related intelligent technologies and their feasibility and applicability when applied to each functional module. At the same time, it clarifies the composition of specific functional elements of each functional module, puts forward the stage goals of China’s inland intelligent ship development and the specific functional requirements of different modules under each stage, and provides reference for the Chinese government to subsequently formulate the top-level design development planning and implementation path of inland waterway intelligent ships.
... The geometric analysis method determines the responsibility and behavior of vessel avoidance through quantitative analysis of the "Collision Avoidance Rules". Through quantitative analysis and evaluation of information such as vessel position, speed, and heading feasible avoidance intervals are determined, and feasible avoidance decisions are obtained through random or iterative methods [34]. Liu et al. [35] also defined ship avoidance actions based on the "Collision Avoidance Rules", and finally solved feasible avoidance decisions with the goal of not infringing on the ship domain; Wang et al. [36] divided the multi-vessel encounter situation into multiple groups and quantitatively analyzed the encounter situation in the "Collision Avoidance Rules" based on the relative speed and navigation of the two vessels, to study the avoidance decision-making under the multi vessel encounter situation, and to obtain the possible avoidance behavior of each vessel, laying the foundation for the multi vessel encounter. ...
Ship collision avoidance has always been a concern and it is crucial for achieving safe navigation of ships at sea. There are many studies on ship collision avoidance in open water, but less attention on coastal waters considering the uncertainty of target ships due to the complexity of the environment and traffic flow. In this paper, collision avoidance decision-making research in coastal waters considering the uncertainty of target ships was proposed. Firstly, accurate ship trajectories are obtained by preprocessing the raw Automatic Identification System (AIS) data. Subsequently, the processed trajectories are clustered using the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm and Hausdorff distance, acquiring a dataset for trajectory prediction of target ships. Then, a mixed Gaussian model is utilized to calculate the prior probability distribution of the prediction model, thus establishing a trajectory prediction model that considers the uncertainty of the target ship. Finally, ship maneuverability is simulated using the Mathematical Model Group (MMG) and Proportion Integration Differentiation (PID) models, and a collision avoidance decision-making model for ships is constructed. The proposed algorithm has been tested and verified in a case study. The results show that the approach effectively predicts the trajectory of the target ship and facilitates informed collision avoidance decision-making.
... As these vessels navigate waterways, sophisticated AI algorithms handle risk assessments, ensuring a comprehensive understanding of environmental variables and potential hazards. Decision support systems, fuelled by AI, contribute to the ship's adaptive decision-making capabilities, optimising routes and responses in real-timeZhang et al. 2022). ...
The maritime industry is following the trend of increased autonomy and digitalisation applied in aviation, automotive, military, and chemical industries. Maritime autonomous and unmanned vehicles have received significant attention recently, both from academia and industry. This paper investigates research into the progress of the development of autonomous and unmanned shipping by employing bibliometric analysis tools VOSviewer and CiteSpace, to present a comprehensive picture of this emerging field of research. Bibliometrics is applied to investigate the collected data sample from Scopus related to predefined keywords. Bibliometric tools assist review by network visualisation, clustering, and metrics. Therefore, this paper presents an analysis aiming at (1) increasing the understanding of the structure and contents of the academic field of autonomous and unmanned shipping; (2) determining and mapping scientific networks in this field; (3) analysing and visualising major divisions within the field; (4) identifying research needs and future research directions in the field. Through clusters generated by bibliometric tools, research divisions are identified and discussed. Furthermore, potential research directions are outlined.
... In [18,19], model predictive controllers were proposed for the collision avoidance problem. In [20], a fuzzy adaptive proportional-integral-derivative control method was proposed. Nevertheless, the controller design approach has not been developed or mentioned in detail. ...
... Via the application of Ξ, which is called the upper bound covariance matrix, in the design method of Theorem 1, all the covariance matrices Ξ i of state error e(t) in each fuzzy subsystem can satisfy the variance constraint δ 2 by (24). In addition, the equality of condition (18) is efficiently substituted by the inequality condition (20) such that the LMI tool in various programs can be conveniently applied to solve the control problem of Theorem 1. ...
A fuzzy controller design approach is developed in this research for the control problem of a ship’s dynamic path based on automatic identification system (AIS) data. Over the past few decades, the equipment of AISs has been widely applied and mandated on ships. Based on the advantages of AIS data, various valuable applications have been proposed to improve safety problems. However, most of the applications depend on the precise control of the ship’s dynamic behavior. Because of this reason, a fuzzy controller design approach is proposed based on the Takagi–Sugeno fuzzy observer model in this research. Firstly, the ship’s dynamic behavior based on the discrete-time AIS data is estimated and represented by the mathematical model of the fuzzy observer. Based on the fuzzy observer model, a fuzzy controller design approach subject to variance constraint is developed to solve the problem of stochastic disturbance in estimation and control. In accordance with the different application aspects, this approach can not only be applied to improve the estimation performance of the fuzzy observer, but it can also be provided as a controller design scheme for the ship’s dynamic path using AISs data. Finally, simulation results of a group of real AIS data from Kaohsiung Port and the assumed Keelung Port AIS data are applied to verify the effectiveness of the designed fuzzy controller.
... This Special Issue, "Data-/Knowledge-Driven Behavior Analysis of Maritime Autonomous Surface Ships", includes twelve contributions [1][2][3][4][5][6][7][8][9][10][11][12] published during 2021-2022. Maritime traffic data (e.g., radar data, AIS data, and CCTV data) provide designers, officers on watch, and traffic operators with extensive information about the states of ships at present and in history, representing a treasure trove for behavior analysis. ...
... The simulation verified and validated the proposed method's effectiveness in complex scenarios. Zhang et al. [11] developed a novel decision support method for ship collision avoidance based on the deduction of the maneuvering process. A fuzzy-based collision risk indicator, modified velocity obstacle algorithm, and fuzzy adaptive PID method were proposed to determine the time required for collision avoidance, identify evasive decisions, execute the selected evasive decision, and resume sailing operations. ...
This Special Issue, “Data-/Knowledge-Driven Behavior Analysis of Maritime Autonomous Surface Ships”, includes twelve contributions [...]
... However, a large amount of data shows that more than 40% of the world's annual ship accidents are caused by ship collisions, and nearly 80% of collision accidents are caused by human decision-making errors (EMSA, 2020;Tsou and Hsueh, 2010). Ship collision accidents are a major threat to the safety of maritime navigation and may cause serious casualties, economic losses and marine environmental pollution (Zhang et al., 2022b). As the maritime environment is complex and changeable and the conventions or regulations do not stipulate the avoidance measures and responsibilities of each ship, especially in the case of multi-ship encounters, it creates greater difficulty for the ship operators to make proper collision avoidance decisions. ...
Ship autonomous collision avoidance has attracted increasing attention in recent years. However, more attention is paid to the scenario in which the target ship keeps its course and speed. Less attention is paid to the development of a collision avoidance decision-making system under the uncertainty of the target ship's movement in a complex multi-ship encounter situation. Based on the idea of model predictive control (MPC), this paper proposes an autonomous ship collision avoidance decision-making system (CADMS) suitable for the uncertainty of ship motion. The CADMS includes four modules: collision risk analysis module, control and execution module, ship trajectory prediction module and collision avoidance decision-making model. The proposed model can be implemented in the collision avoidance decision-making system for safe navigation or it can be included in the ship autonomous navigation process. The decision-making model is achieved from a risk identification-motion prediction-ship control-scheme implementation perspective, and the dynamic and uncertainty features of the ship action (i.e., alter course or change speed) are considered in the modelling process. The real-time rolling update of ship collision avoidance decisions is realised based on the time series rolling method. Four scenarios are designed to demonstrate the collision avoidance decision-making system's performance. The results show that the proposed collision avoidance decision-making system is a reasonable and effective system for collision avoidance, particularly in multi-ship encounter situations of target ships suddenly altering course or change speed.
... To ensure safety, maritime managers have endeavoured to prevent collision accidents by identifying the collision risks in the Yangtze River, while scholars have also proposed several risk models. In general, the quantification of collision risk models is used to aid mariners in assessing collision situations and to aid collision avoidance decision-making [11,28]; qualitative risk models are applied to evaluate the overall water risks by considering risk impact factors such as weather, traffic conditions and human impacts [23]. ...
The risks for ferries in the Yangtze River are relatively high, as they frequently cross the main traffic flows, leading to more intersections with other upwards and downwards ships. Although some studies have developed many models to assess collision risks in the Yangtze River, collision warning studies on ferries are scant. Meanwhile, most of the current collision studies evaluate risk based on AIS data, which are incapable of providing real-time ship information as they are discrete-time series data. In this work, fused data combining radar and AIS data are applied in a real-time ship collision warning model to assess the dynamic risk for ferries in the Yangtze River. Firstly, data fusion technology is proposed to acquire refined ship trajectories from AIS and radar data. Then, a widely used geometric collision model is enhanced to assess the real-time collision risk for ferries. And lastly, to illustrate the model, a real case of a ferry crossing through the Yangtze River is studied. The real-time risk values of the ferries are calculated based on fused data inputs, and the output results indicate that the use of fused data provides more accurate and continuous real-time ship risks. Thus, the proposed approach is evidenced to support the development of smart maritime surveillance.
... Due to the advantages of high efficiency, adaptability and intellectualization, ship path planning has become an important means to ensure the safety of ships and an important technology to stabilize the course and change direction infrequently. Ship path planning is also an inevitable trend of future development [3]. ...
Ship path planning is one of the key technologies for ship automation. Establishing a cooperative collision avoidance (CA) path for multi-ship encounters is of great value to maritime intelligent transportation. This study aims to solve the problem of multi-ship collaborative collision avoidance based on the algorithm of Conflict Search (CS) and Space-Time Hybrid A-star (STHA). First, a static CA path is searched for each ship by using the space-time Hybrid A-star algorithm, and the conflict risk area is determined according to the ship safety distance constraint and fuzzy Collision Risk Index (CRI). Secondly, the space-time conflict constraint is introduced into the multi-ship cooperative CA scheme, and the binary tree is used to search for an optimal navigation path with no conflict and low cost. In addition, the optimal path is smoothed by using cubic interpolation to make the path consistent with actual navigation practice and ship maneuvering characteristics. Finally, considering the constraints of the International Regulations for Preventing Collisions at Sea (COLREGs), the typical two-ship and multi-ship encounter scenarios are designed and simulated to verify the effectiveness of the proposed method. Furthermore, a comparative analysis of actual encounters and encounters based on CS-STHA is also carried out. The results indicate that the proposed algorithm in the study can obtain an optimal CA path effectively and provide a reference of CA decision-making for autonomous ships.
