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Situation Awareness under Collision Risk and Navigation Safety in the...
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Situation Awareness under Collision Risk and Navigation Safety in the Intelligent Ship Era

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (31 May 2019) | Viewed by 17720

Special Issue Editor

Dr. Lokukaluge Prasad Perera

E-Mail Website
Guest Editor
UiT The Arctic University of Norway, Tromsø, Norway
Interests: maritime and offshore systems & controls; instrumentation; data analytics; machine learning and artificial intelligence; autonomous navigation; intelligent guidance and decision support; condition monitoring and condition-based maintenance; energy efficiency and emission control, safety, risk and reliability

Special Issue Information

Dear Colleagues,

The accuracy of the collision risk assessment is an important factor when evaluating the navigation safety under situation awareness of ship encounter situations. Since the collision avoidance actions of ship navigators completely depend on the risk of possible collisions or near-miss situations (i.e. within a considerable confidence interval), the same risk will influence their decision-making process. However, the decision-making process of ocean-going vessels can be further complicated by close encounter situations with remote-controlled, autonomous and manned vessels in the intelligent ship era. It is believed that adequate measures to evaluate situation awareness including the collision risk assessment in such encounters should be implemented in future vessels to improve their navigation safety.

Ship encounter situations, related to possible near-miss and collision situations, are regulated by the International Regulations for Preventing Collisions at Sea 1972 (COLREGs) in open sea areas. Furthermore, additional local navigation rules and regulations can be enforced on ships, especially in confined waters and maritime traffic lanes. On the other hand, if the collision risk can be detected relatively far away from a ship encounter situation, then vessels can take appropriate actions to avoid even a close encounter situation. That step can eliminate the possibility of any close ship encounter situation.

A navigator should always be on the bridge to evaluate/re-evaluate the collision risk with respect to expected or unexpected ship behaviour resulting from his course and speed control actions. Unexpected ship behaviour can complicate the navigator`s decision-making process in some situations, where an adequate understanding of the situation may not be possible. When on-board systems are making the same decisions for future autonomous vessels, this can further complicate not only those system decisions but also their interactions (i.e. the outcomes) with the decisions made by manned vessels (i.e. human decisions).

Therefore, we are calling for research reflecting on overarching and cross-sectorial topics that relate to these challenging issues in future vessels. Research manuscripts addressing the empirical sectors, theoretical methods and applications should be submitted with an emphasize on how their findings can be relevant to a broad audience concerned with situation awareness under collision risk and navigation safety in the intelligent ship era.

Dr. Lokukaluge Prasad Perera
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Ship Collision Avoidance
  • Situation Awareness
  • Risk Assessment
  • COLREGs
  • Autonomous Ship
  • Remote Controlled Ships
  • e-COLREGs
  • Decision Supporting
  • Advanced Predictor
  • Decision-Making

Published Papers (5 papers)

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Research

21 pages, 1664 KiB  
Article
Dynamics Simulation for Process Risk Evolution on the Bunker Operation of an LNG-fueled Vessel with Catastrophe Mathematical Models
by Shaoyong Xuan, Shenping Hu, Zhuang Li, Wei Li and Boyin Li
J. Mar. Sci. Eng. 2019, 7(9), 299; https://doi.org/10.3390/jmse7090299 - 31 Aug 2019
Cited by 13 | Viewed by 3181
Abstract
Liquefied nature gas (LNG) is a green energy. LNG-fueled vessels are extremely complex engineering systems. In view of the inherent hazardous properties of LNG fuel, LNG fueling is not only an important part, but it is also full of high risks in the [...] Read more.
Liquefied nature gas (LNG) is a green energy. LNG-fueled vessels are extremely complex engineering systems. In view of the inherent hazardous properties of LNG fuel, LNG fueling is not only an important part, but it is also full of high risks in the operation of LNG-fueled vessels (LNGFVs). Therefore, it is necessary to study the risk factors, and the intrinsic relationship among them between the LNG and the vessel, and to simulate the system dynamics in the process of LNGFV operation. During the process of fueling of LNGFV, at every moment the vessel interacts with the energy and information of the surrounding environment. First, the impact of the three interactions of the fueling operation process, ship factors, and environmental factors were analyzed on the risk of fueling operation, and a complete node system was proposed as to the complex system dynamics mode. Second, by analyzing the boundary conditions of the system, the relationship of factors was established via the tools of system dynamics (SD). Based on the catastrophe theory (CA), the dynamics model for the fueling of LNG is set up to study the system’s risk mutation phenomenon. Third, combined with the simulation results of the case analysis, the risk evolution mode of the LNGFV during the fueling process was obtained, and constructive opinions were put forward for improving the safe fueling of the LNGFV. Application examples show that formal description of risk emergence and transition is a prerequisite for the quantitative analysis of the risk evolution mode. In order to prevent accidents, the coupling synchronization of risk emergence should be weakened, and meanwhile risk control should be implemented. Full article
(This article belongs to the Special Issue Situation Awareness under Collision Risk and Navigation Safety in the Intelligent Ship Era)
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19 pages, 2376 KiB  
Article
Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics
by Yong-jun Chen, Qing Liu and Cheng-peng Wan
J. Mar. Sci. Eng. 2019, 7(8), 277; https://doi.org/10.3390/jmse7080277 - 16 Aug 2019
Cited by 19 | Viewed by 2674
Abstract
Accidents occur frequently in traffic-intensive waters, which restrict the safe and rapid development of the shipping industry. Due to the suddenness, randomness, and uncertainty of accidents in traffic-intensive waters, the probability of the risk factors causing traffic accidents is usually high. Thus, properly [...] Read more.
Accidents occur frequently in traffic-intensive waters, which restrict the safe and rapid development of the shipping industry. Due to the suddenness, randomness, and uncertainty of accidents in traffic-intensive waters, the probability of the risk factors causing traffic accidents is usually high. Thus, properly analyzing those key risk factors is of great significance to improve the safety of shipping. Based on the analysis of influencing factors of ship navigational risks in traffic-intensive waters, this paper proposes a cloud model to excavate the factors affecting navigational risk, which could accurately screen out the key risk factors. Furthermore, the risk causal model of ship navigation in traffic-intensive waters is constructed by using the infectious disease dynamics method in order to model the key risk causal transmission process. Moreover, an empirical study of the Yangtze River estuary is conducted to illustrate the feasibility of the proposed models. The research results show that the cloud model is useful in screening the key risk factors, and the constructed causal model of ship navigational risks in traffic-intensive waters is able to provide accurate analysis of the transmission process of key risk factors, which can be used to reduce the navigational risk of ships in traffic-intensive waters. This research provides both theoretical basis and practical reference for regulators in the risk management and control of ships in traffic-intensive waters. Full article
(This article belongs to the Special Issue Situation Awareness under Collision Risk and Navigation Safety in the Intelligent Ship Era)
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16 pages, 1926 KiB  
Article
Identification and Analysis of Vulnerability in Traffic-Intensive Areas of Water Transportation Systems
by Yong-jun Chen, Qing Liu, Cheng-peng Wan, Qin Li and Peng-wei Yuan
J. Mar. Sci. Eng. 2019, 7(6), 174; https://doi.org/10.3390/jmse7060174 - 02 Jun 2019
Cited by 6 | Viewed by 3245
Abstract
Water transportation accidents have occurred frequently in recent years. In order to improve the emergency response capability of water transportation systems under traffic-intensive conditions, this paper identifies and analyzes the vulnerability in traffic-intensive areas of water transportation systems. Firstly, the vulnerability identification model [...] Read more.
Water transportation accidents have occurred frequently in recent years. In order to improve the emergency response capability of water transportation systems under traffic-intensive conditions, this paper identifies and analyzes the vulnerability in traffic-intensive areas of water transportation systems. Firstly, the vulnerability identification model was constructed based on the analysis of characteristics and the vulnerability-influencing factors of water transportation systems. The newly proposed model is composed of three parts including the DEMATEL (Decision Making Trial and Evaluation Laboratory) method, ISM (interpretative structural modeling) model, and AHP (Analytic Hierarchy Process)–entropy weight method. Finally, a case study of the Yangtze River was conducted to test the logicality and feasibility of the proposed model. The research results reveal that traffic flow density, ship traffic, tides, fog, and bad weather are the key factors affecting the vulnerability of water transportation in traffic-intensive areas of the Yangtze River estuary. However, the influence of navigation aid configuration, berth, anchorage, and obstruction on the system vulnerability is relatively lower. The findings of this study can provide helpful references for maritime administration authorities on the management of water transportation safety. Full article
(This article belongs to the Special Issue Situation Awareness under Collision Risk and Navigation Safety in the Intelligent Ship Era)
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16 pages, 6422 KiB  
Article
Relational Model of Accidents and Vessel Traffic Using AIS Data and GIS: A Case Study of the Western Port of Shenzhen City
by Mengxia Li, Junmin Mou, Rongfang (Rachel) Liu, Pengfei Chen, Zhuojian Dong and Yixiong He
J. Mar. Sci. Eng. 2019, 7(6), 163; https://doi.org/10.3390/jmse7060163 - 28 May 2019
Cited by 19 | Viewed by 3617
Abstract
Following the growth in global trade activities, vessel traffic has increased dramatically in some busy waterways and ports. However, such increments have made it more complex to manage the regional vessel traffic, which can increase the risk of an accident in the area. [...] Read more.
Following the growth in global trade activities, vessel traffic has increased dramatically in some busy waterways and ports. However, such increments have made it more complex to manage the regional vessel traffic, which can increase the risk of an accident in the area. To model and analyze the relationship between vessel traffic and maritime traffic, this paper proposes a gridded geography information system (GIS)-based relation analysis model using the historical automatic identification system (AIS) data and accident records over a 10-year-span. Firstly, the extent of the hazards posed by a maritime accident in terms of hull loss, fatality, and direct economic loss is quantified using set pair analysis. Consequently, the hazardous degree posed by an accident is obtained. The relative consequence of the regional hazard (RCORH) is then estimated by summing up all the relative hazardous degrees of accidents that have occurred in a certain gridded area. Secondly, the vessel traffic in the gridded areas is analyzed using characteristics such as speed, heading variance, and traffic volume as indicators. Based on the analysis of both the maritime traffic accidents and the vessel traffic, the spatial relationships are analyzed with an overlay between the RCORH and vessel traffic data of each grid, as well as a regression analysis. In a case study of the Western port of Shenzhen City, China, the methodology proves to be effective for vessel traffic management and traffic engineering design. Full article
(This article belongs to the Special Issue Situation Awareness under Collision Risk and Navigation Safety in the Intelligent Ship Era)
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21 pages, 6794 KiB  
Article
Ship Manoeuvrability-Based Simulation for Ship Navigation in Collision Situations
by Shengke Ni, Zhengjiang Liu and Yao Cai
J. Mar. Sci. Eng. 2019, 7(4), 90; https://doi.org/10.3390/jmse7040090 - 30 Mar 2019
Cited by 34 | Viewed by 4189
Abstract
In this article, a ship manoeuvrability-based simulation for ship navigation in collision situations is established. Under the general requirement from the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) and good seamanship, the determination of encounter situations is quantified to [...] Read more.
In this article, a ship manoeuvrability-based simulation for ship navigation in collision situations is established. Under the general requirement from the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) and good seamanship, the determination of encounter situations is quantified to reduce navigators’ intervention. Meanwhile, the action manner by course alteration or changing speed in some typical encounter situations is graphically analysed for both the give-way and stand-on vessels. Then, the multiple genetic algorithm and linear extension algorithm are adopted to perform trajectory planning for collision avoidance. To improve the reliability of the simulation system, the mathematical model of ship motion and ship manoeuvring control mechanism are adopted, which can eliminate the insufficiency of neglect of ship manoeuvrability in the process of collision avoidance. Meanwhile, the course encoding technique is adopted to fit the ship manoeuvring control mechanism. Finally, a set of traffic scenarios emulating different encounter situations are applied to demonstrate the effectiveness, consistency, and practicality of this system. Full article
(This article belongs to the Special Issue Situation Awareness under Collision Risk and Navigation Safety in the Intelligent Ship Era)
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