An Improved Danger Sector Model for Identifying the Collision Risk of Encountering Ships

Liu, Zihao; Wu, Zedong; Zheng, Zhongyi

doi:10.3390/jmse8080609

Cited by 6 publications

(5 citation statements)

References 24 publications

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“…Therefore, in order to assess the ship traffic density, ship particles should be arranged in a real water plane. For a specified ship particle, we can obtain the distribution probabilities of its surrounding ship particles by RDF and assess the ship density by integrating the RDF curve as expressed by Equations ( 12) and (13).…”

Section: The Complexity On Ship Positionmentioning

confidence: 99%

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A Molecular Dynamics Approach to Identify the Marine Traffic Complexity in a Waterway

Liu

Zheng

et al. 2022

JMSE

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With the rapid development of the shipping industry in recent years, the increasing volume of ship traffic makes marine traffic much busier and more crowded, especially in the waterway off the coast. This leads to the increment of the complexity level of marine traffic and poses more threats to marine traffic safety. In order to study marine traffic safety under the conditions of increasing complexity, this article proposed a marine traffic complexity model based on the method in molecular dynamics. The model converted ship traffic to a particle system and identified the traffic complexity by analyzing the radial distribution of dynamic and spatial parameters of ships in a Euclid plane. The effectiveness of the proposed model had been validated by the case studies in the waters of Bohai Strait with real AIS (Automatic Identification System) data and simulated data. The results show that the proposed model can evaluate the marine traffic complexity more sufficiently and accurately. The proposed model is helpful for marine surveillance operators to monitor and organize marine traffic under complex situations so as to improve marine traffic safety.

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Section: The Complexity On Ship Positionmentioning

confidence: 99%

“…The model is useful for collision risk prediction for the water area under complex traffic situations. Liu et al [13] propose an improved danger sector model to identify the collision risk of encountering ships. The model considers the course alteration maneuver by taking ship maneuverability limitation into consideration.…”

Section: Introductionmentioning

confidence: 99%

A Molecular Dynamics Approach to Identify the Marine Traffic Complexity in a Waterway

Liu

Zheng

et al. 2022

JMSE

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“…Liu et al [25][26][27][28] used fuzzy mathematics theory to propose the CRI measurement model by using the distance at the closest point of approach (DCPA), the time to the closest point of approach (TCPA), and the distance between two ships as variables. Han-Jin Lee et al [29][30][31][32] also established the fuzzy function model using the same idea and method. As with many parameters in these ships, CRI measurement models are determined by the ship officer's experience in handling; in some special cases, due to the influence of human factors such as the officer's psychology and experience in the ship's handling, the mathematical model may not work.…”

Section: The Fuzzy Ship Domain Modelmentioning

confidence: 99%

Collision Risk Index Calculation Based on an Improved Ship Domain Model

Liu

Zhong

Yang

et al. 2022

JMSE

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The traditional ship collision risk index model based on the distance at the closest point of approach (DCPA) and the time to the closest point of approach (TCPA) is insufficient for estimating ship collision risk and planning collision avoidance operations. This paper constructs an elliptical, dynamic ship domain that changes with ship speed and maneuverability parameters to overcome subjective human factors. Based on the constructed domain model, the concept of the ship domain proximity factor is introduced to improve the ship collision risk model based on DCPA and TCPA, and a risk calculation function model that considers the safety of ship navigation is constructed. The numerical calculation of the improved collision risk index calculation model confirms that the enhanced model has a higher rate of identification of risk between ships. The model is more compatible with the requirements of ship navigation decision-making and can provide theoretical support and a technical basis for research on ship collision avoidance decision-making.

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“…The collision risk index (CRI) is used to evaluate the probability and severity of a ship collision with obstacle nearby [7]. Identification and accurate quantification of CRI can help the mariners or OOW to become familiar with encounter situations and assist them in making subsequent collision avoidance decisions [8]. Zhen et al [9] proposed the concept of ship domain, it can be used to assess the risk of ship collisions.…”

Section: Introductionmentioning

confidence: 99%

Collision Avoidance Method for Autonomous Ships Based on Modified Velocity Obstacle and Collision Risk Index

Zhang

Huang

et al. 2022

Journal of Advanced Transportation

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A novel real-time collision avoidance method for autonomous ships based on modified velocity obstacle (VO) algorithm and grey cloud model is proposed. A typical VO algorithm is used to judge whether there is a collision risk for ships in the potential collision area (PCA). Then, in order to quantify the collision risk of ships in different encounter situations within the PCA and trigger a prompt warning of danger of collision, this study sets up a novel collision risk assessment method based on asymmetric grey cloud model (AGC). It can effectively consider the randomness, ambiguity, and incompleteness of the information in the ship collision risk evaluation process. Moreover, reachable collision-free velocity sets under different encounter situations and optimal steering angle model are constructed. A real-time collision avoidance method based on modified VO algorithm and manoeuvring motion characteristics of vessels is put forward. In this model, various constraints are considered including the International Regulations for Preventing Collisions at Sea (COLREGs), ship manoeuvrability, and ordinary practice of seaman. Finally, several case studies are carried out to verify the performance and reliability of the collision avoidance model. The results show that the proposed method can not only effectively identify and quantify the collision risk in real-time but also offer proper collision-free solutions for autonomous ships.

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An Improved Danger Sector Model for Identifying the Collision Risk of Encountering Ships

Cited by 6 publications

References 24 publications

A Molecular Dynamics Approach to Identify the Marine Traffic Complexity in a Waterway

A Molecular Dynamics Approach to Identify the Marine Traffic Complexity in a Waterway

Collision Risk Index Calculation Based on an Improved Ship Domain Model

Collision Avoidance Method for Autonomous Ships Based on Modified Velocity Obstacle and Collision Risk Index

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