Academic literature on the topic 'Ship Collision'

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Journal articles on the topic "Ship Collision"

1

Kim, Dong-Gyun, Katsutoshi Hirayama, and Gyei-Kark Park. "Collision Avoidance in Multiple-Ship Situations by Distributed Local Search." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 5 (2014): 839–48. http://dx.doi.org/10.20965/jaciii.2014.p0839.

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As vital transportation carriers in trade, ships have the advantage of stability, economy, and bulk capacity over airplanes, trucks, and trains. Even so, their loss and cost due to collisions and other accidents exceed those of any other mode of transportation. To prevent ship collisions many ways have been suggested, e.g., the 1972 COLREGs which is the regulation for preventing collision between ships. Technologically speaking, many related studies have been conducted. The term “Ship domain” involves that area surrounding a ship that the navigator wants to keep other ships clear of. Ship domain alone is not sufficient, however, for enabling one or more ships to simultaneously determine the collision risk for all of the ships concerned. Fuzzy theory is useful in helping ships avoid collision in that fuzzy theory may define whether collision risk is based on distance to closest point of approach, time to closest point of approach, or relative bearing – algorithms that are difficult to apply to more than one ships at one time. The main purpose of this study is thus to reduce collision risk among multiple ships using a distributed local search algorithm (DLSA). By exchanging information on, for example, next-intended courses within a certain area among ships, ships having the maximum reduction in collision risk change courses simultaneously until all ships approach a destination without collision. In this paper, we introduce distributed local search and explain how it works using examples. We conducted experiments to test distributed local search performance for certain instances of ship collision avoidance. Experiments results showed that in most cases, our proposal applies well in ship collision avoidance amongmultiple ships.
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2

Zhang, Ke, Liwen Huang, Xiao Liu, et al. "A Novel Decision Support Methodology for Autonomous Collision Avoidance Based on Deduction of Manoeuvring Process." Journal of Marine Science and Engineering 10, no. 6 (2022): 765. http://dx.doi.org/10.3390/jmse10060765.

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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 autonomous ships is presented. Firstly, the dynamic motion parameters of the own ship relative to the target ship are calculated by using the dynamic mathematical model. Then the fuzzy set theory is adopted to construct collision risk models, which combine the spatial collision risk index (SCRI) and time collision risk index (TCRI) in different encountered situations. After that, the ship movement model and fuzzy adaptive PID method are used to derive the ships’ manoeuvre motion process. On this basis, the feasible avoidance range and the optimal steering angle for ship collision avoidance are calculated by deducting the manoeuvring process and the modified velocity obstacle (VO) method. Moreover, to address the issue of resuming sailing after the ship collision avoidance is completed, the Line of Sight (LOS) guidance system is adopted to resume normal navigation for the own ship in this study. Finally, the dynamic adaptive autonomous collision avoidance model is developed by combining the ship movement model, the fuzzy adaptive PID control model, the modified VO method and the resume-sailing model. The results of the simulation show that the proposed methodology can effectively avoid collisions between the own ship and the moving TSs for situations involving two or multiple ships, and the own ship can resume its original route after collision avoidance is completed. Additionally, it is also proved that this method can be applied to complex situations with various encountered ships, and it exhibits excellent adaptability and effectiveness when encountering multiple objects and complex situations.
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3

Li, Weifeng, Lufeng Zhong, Yaochen Liu, and Guoyou Shi. "Ship Intrusion Collision Risk Model Based on a Dynamic Elliptical Domain." Journal of Marine Science and Engineering 11, no. 6 (2023): 1122. http://dx.doi.org/10.3390/jmse11061122.

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To improve navigation safety in maritime environments, a key step is to reduce the influence of human factors on the risk assessment of ship collisions by automating the decision-making process as much as possible. This paper optimizes a dynamic elliptical ship domain based on Automatic Identification System (AIS) data, combines the relative motion between ships in different encounter situations and the level of ship intrusion in the domain, and proposes a ship intrusion collision risk (SICR) model. The simulation results show that the optimized ship domain meets the visualization requirements, and the intrusion model has good collision risk perception ability, which can be used as the evaluation standard of ship collision risk: when the SICR is 0.5–0.6, the ship can establish a collaborative collision avoidance decision-making relationship with other ships, and the action ship can take effective collision avoidance action at the best time when the SICR is between 0.3 and 0.5. The SICR model can give navigators a more accurate and rapid perception of navigation risks, enabling timely maneuvering decisions, and improving navigation safety.
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4

Cheng, Zhiyou, Yaling Li, and Bing Wu. "Early Warning Method and Model of Inland Ship Collision Risk Based on Coordinated Collision-Avoidance Actions." Journal of Advanced Transportation 2020 (July 20, 2020): 1–14. http://dx.doi.org/10.1155/2020/5271794.

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To reduce the occurrence of ship collisions, immediate danger, and close-quarters situations in narrow inland waterways, a step-by-step early warning system for ship collision-avoidance actions was developed, along with an early warning method and model of collision risk based on coordinated collision-avoidance actions. This study first analyzed the importance of coordinated collision-avoidance actions in inland waterways, and the process and key components of coordinated collision-avoidance actions were studied. Then, the early warning method of inland ship collision risk based on coordinated collision-avoidance actions was introduced; the effectiveness of the early warning method was comparatively analyzed via experimental observations. A framework of early warning model of inland ship collision risk was created based on the early warning method; a collision risk early warning model for inland ships based on coordinated collision-avoidance actions was proposed according to the relationship between the distance/time to the closest point of approach (DCPA, TCPA), coordination degree of collision-avoidance actions of the two considered ships and collision risk; moreover, the early warning model of inland ship collision risk was further considered for quantitative calculation. Finally, the application of the early warning method and model was demonstrated using a case study. The results indicate that the early warning method of inland ship collision risk based on coordinated collision-avoidance actions could effectively reduce the emergence of close-quarters situations and immediate danger, and the early warning model could quantitatively show the evolution of collision risk of two ships along with the process of coordinated collision-avoidance actions.
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5

Li, Yun, and Haiyu Zhang. "Collision Avoidance Decision Method for Unmanned Surface Vehicle Based on an Improved Velocity Obstacle Algorithm." Journal of Marine Science and Engineering 10, no. 8 (2022): 1047. http://dx.doi.org/10.3390/jmse10081047.

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To ensure navigation safety, unmanned surface vehicles (USVs) need to have autonomous collision avoidance capability. A large number of studies on ship collision avoidance are available, and most of these papers assume that the target ships keep straight or follows the International Regulations for Preventing Collisions at Sea (COLREGS). However, in the actual navigation process, the target ship may temporarily turn. Based on the above reasons, this paper proposes a multi-ship collision avoidance decision method for USVs based on the improved velocity obstacle algorithm. In the basic dynamic ship domain model, a collision risk model is constructed to improve the accuracy of the risk assessment between the USV and target ships. The velocity obstacle algorithm is combined with the dynamic ship domain, and the collision avoidance timing and method are judged according to the collision risk. The simulation results show that the decision method can handle the situation that the target ship temporarily turns and has an emergency collision avoidance capability. Compared with the traditional VO algorithm, the collision avoidance time of the method is shorter, and the number of course changes is less.
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6

Gong, Haonan. "Application of Viscoelastic Materials in Ship Collision." Journal of Contemporary Educational Research 5, no. 11 (2021): 118–24. http://dx.doi.org/10.26689/jcer.v5i11.2690.

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With the expansion of global trade routes, ship collision has become a major problem. This article proposes an approach by laying viscoelastic material on the inner side of the ship to increase the crashworthiness. By using the nonlinear finite element model software, this study simulates ship collisions as well as models and analyzes ships along with viscoelastic materials. The results from the simulation suggest that viscoelastic materials can effectively protect ships during collisions.
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7

Wei, Guan, and Wang Kuo. "COLREGs-Compliant Multi-Ship Collision Avoidance Based on Multi-Agent Reinforcement Learning Technique." Journal of Marine Science and Engineering 10, no. 10 (2022): 1431. http://dx.doi.org/10.3390/jmse10101431.

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The congestion of waterways can easily lead to traffic hazards. Moreover, according to the data, the majority of sea collisions are caused by human error and the failure to comply with the Convention on the International Regulation for the preventing Collision at Sea (COLREGs). To avoid this situation, ship automatic collision avoidance has become one of the most important research issues in the field of marine engineering. In this study, an efficient method is proposed to solve multi-ship collision avoidance problems based on the multi-agent reinforcement learning (MARL) algorithm. Firstly, the COLREGs and ship maneuverability are considered for achieving multi-ship collision avoidance. Subsequently, the Optimal Reciprocal Collision Avoidance (ORCA) algorithm is utilized to detect and reduce the risk of collision. Ships can operate at the safe velocity computed by the ORCA algorithm to avoid collisions. Finally, the Nomoto three-degrees-of-freedom (3-DOF) model is used to simulate the maneuvers of ships. According to the above information and algorithms, this study designs and improves the state space, action space and reward function. For validating the effectiveness of the method, this study designs various simulation scenarios with thorough performance evaluations. The simulation results indicate that the proposed method is flexible and scalable in solving multi-ship collision avoidance, complying with COLREGs in various scenarios.
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8

Li, Qiang. "A Research on Autonomous Collision Avoidance under the Constraint of COLREGs." Sustainability 15, no. 3 (2023): 2446. http://dx.doi.org/10.3390/su15032446.

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In this paper, a decision-making model suitable for the collision avoidance (CA) of numerous target ships (TSs) is proposed, based on the principle of ship collision avoidance geometry and the characteristics of numerous target ships’ collision avoidance at sea. To ensure that the collision avoidance behaviors of own-ship (OS) are subject to the International Regulations for Preventing Collisions at Sea (COLREGS), this paper gives full consideration to the requirements of COLREGS within the scope of CA action and the time of collision avoidance. A ship CA simulation is established based on the Mathematical Modeling Group (MMG) model. To optimize the CA decision-making model, the influence of hydrodynamic force on steering time required to reach the new course is integrated into the collision avoidance simulation system. The simulation results show that the method can quickly and effectively determine a collision avoidance decision under the complex situation of numerous target ships and static obstacles, and it can consider the unpredictable strategies used by other vessels.
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9

Weng, Jinxian, Guorong Li, Tian Chai, and Dong Yang. "Evaluation of Two-Ship Collision Severity using Ordered Probit Approaches." Journal of Navigation 71, no. 4 (2018): 822–36. http://dx.doi.org/10.1017/s0373463317000996.

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This study develops an ordered probit model to evaluate the factors influencing two-ship collision severity using ten years’ ship collision accident data from Fujian sea areas. The model results show that the involvement of big ships has the largest impact in increasing the probability of a serious or very serious accident, followed by the involvement of fishing vessels. There will be a bigger probability of a serious accident if both ships involved in the collision are cargo ships. We found that the season of spring, poor visibility and night time periods are more likely to be factors in high severity levels of ship collision. The results also reveal that lookout failure plays a decisive role in increasing serious accident risk compared with other types of human errors. The results of this study may be beneficial for policy-makers in proposing efficient strategies to reduce the likelihood of serious ship collisions.
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10

Wang, Zhiyuan, Yong Wu, Xiumin Chu, Chenguang Liu, and Mao Zheng. "Risk Identification Method for Ship Navigation in the Complex Waterways via Consideration of Ship Domain." Journal of Marine Science and Engineering 11, no. 12 (2023): 2265. http://dx.doi.org/10.3390/jmse11122265.

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Collision risk identification is an important basis for intelligent ship navigation decision-making, which evaluates results that play a crucial role in the safe navigation of ships. However, the curvature, narrowness, and restricted water conditions of complex waterways bring uncertainty and ambiguity to the judgment of the danger of intelligent ship navigation situation, making it difficult to calculate such risk accurately and efficiently with a unified standard. This study proposes a new method for identifying ship navigation risks by combining the ship domain with AIS data to increase the prediction accuracy of collision risk identification for ship navigation in complex waterways. In this method, a ship domain model is constructed based on the ship density map drawn using AIS data. Then, the collision time with the target ship is calculated based on the collision hazard detection line and safety distance boundary, forming a method for dividing the danger level of the ship navigation situation. In addition, the effectiveness of this method was verified through simulation of ships navigation in complex waterways, and correct collision avoidance decisions can be made with the Regulations for Preventing Collisions in Inland Rivers of the People’s Republic of China, indicating the advantages of the proposed risk identification method in practical applications.
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