Maritime Transportation System and Traffic Engineering Oriented for the New Generation of Waterborne Transportation Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 2530

Special Issue Editors


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Guest Editor
State Key Laboratory of Maritime Technology and Safety, School of Navigation, Wuhan University of Technology, 1178 Heping Road, Wuhan 430063, China
Interests: intelligent navigation for surface vehicles; path planning; path following; motion control; networked control algorithm
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Guest Editor
Division of Navigation Science, Mokpo National Maritime University, Mokpo City 58628, Jeonnam, Republic of Korea
Interests: LCA; artificial neural networks; navigation; fuzzy logic; control life-cycle assessment; MATLAB simulation; advanced control theory; environment automation tracking; environmental studies; ship maneuverability; ships control theory; ship stability
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Navigation and Shipping, Shandong Jiaotong University, Weihai 264209, China
Interests: nonlinear feedback control; ship automatic berthing control; ship robust control

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Guest Editor
School of Maritime, Zhejiang Ocean University, Zhoushan 316022, China
Interests: robust adaptive control; neural network control; nonlinear control

Special Issue Information

Dear Colleagues,

Maritime transportation system and traffic engineering play vital roles in the domain of the shipping industry. With the rapid development of AI, big data and IOT technologies and shipping infrastructures, the new generation of waterborne transportation systems is being constructed and shaped, and will further promote the high-quality and innovative development of China’s shipping industry. Following that, oriented to the new generation of waterborne transportation systems, it is significant to re-examine and conduct more in-depth studies on maritime transportation systems and traffic engineering.

Maritime transportation mainly focuses on the navigational safety and efficiency enhancement of the navigation of vessels all across the world. Probing into those details, areas including vessel traffic flow, vessel behavior, marine traffic investigation, simulation and safety assessment of maritime traffic engineering, ship routing, vessel traffic systems, vessel intelligent NGC (navigation, guidance and control) technologies, and their corresponding theories and technologies are being rapidly developed.

This Special Issue of Applied Sciences aims to target the above opportunities and challenges. Researchers from both academia and industry are invited to submit unpublished research work related to the novel theory and technologies of maritime transportation systems and traffic engineering, especially from the perspective of the new generation of waterborne transportation systems. Meanwhile, original research related, but not limited, to autonomous navigation, heterogeneous traffic flow, intelligent control, traffic accident prevention, vessel traffic simulation, etc., are welcomed for publication.

Prof. Dr. Yong Ma
Prof. Dr. Nam-kyun Im
Prof. Dr. Qiang Zhang
Dr. Guibing Zhu
Guest Editors

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Keywords

  • maritime transportation system
  • maritime traffic engineering
  • new generation of waterborne transportation system
  • vessel intelligent NGC technology

Published Papers (2 papers)

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Research

18 pages, 6429 KiB  
Article
An Approach of Consensus-Based Double-Layer Blockchain System for Multi-Ship Collision Risk Mitigation Considering COLREGs
by Yongjun Chen, Tengfei Wang, You’an Xiao, Yang Wang and Gang’ao Yan
Appl. Sci. 2023, 13(20), 11178; https://doi.org/10.3390/app132011178 - 11 Oct 2023
Cited by 1 | Viewed by 875
Abstract
Ship collision avoidance (CA) is the most fundamental and essential issue of maritime safety, regardless of whether the ship is a conventional ship or a future maritime autonomous surface ship (MASS). However, effective ship-to-ship communication has been recognized as a critical issue and [...] Read more.
Ship collision avoidance (CA) is the most fundamental and essential issue of maritime safety, regardless of whether the ship is a conventional ship or a future maritime autonomous surface ship (MASS). However, effective ship-to-ship communication has been recognized as a critical issue and one of the major challenges affecting the success of ship CA. This study intends to investigate the basic trust concerns in the cybersecurity components of the ship CA process and develop a blockchain-based solution for trustworthy communication. The novel idea behind applying blockchain to ship CA decision-making is that the various participating ships in a scenario of dynamically changing ship encounters form a decentralized network of opportunities, which makes blockchain an appealing tool to offer a solution for evaluating and maximizing trust in entity dynamics. The mechanism of entity participation in upholding a master chain for avoiding ship encounters is described in this work. The research begins by analyzing conventional ship CA decision scenarios under COLREGs in order to identify formal communication strategies that can make information more understandable. Based on this, it is demonstrated how beliefs of trust (BoT) between entities are encoded and combined on the chain to enable entities in the encounter scenario to form an initial opinion about another entity before becoming familiar with it. This first encounter occurs during ship CA. Second, this article examines how encounter ships have temporary rights in the process of making CA decisions. This generates blocks and attaches them to the chain at the consensus layer of blockchain technology. Finally, this study undertakes a case test of ship CA based on the aforementioned communication principles. In order to ensure safe and effective communication during brief, one-time ship encounters, the results offer a practical method for conveying CA reasoning in encounter scenarios. As a result, it can aid in the selection of better (more reliable) nodes to uphold the evidence-based understanding of the ship CA process and assess the reliability of unidentified members. Full article
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21 pages, 5497 KiB  
Article
CIPSO-Based Decision Support Method for Collision Avoidance of Super-Large Vessel in Port Waters
by Bo Xiang and Yongqiang Zhuo
Appl. Sci. 2023, 13(19), 11100; https://doi.org/10.3390/app131911100 - 9 Oct 2023
Viewed by 883
Abstract
Effective and timely collision avoidance decision support is essential for super-large vessels navigating in port waters. To guarantee the navigational safety of super-large vessels, this work proposes a collision avoidance decision support method based on the curve increment strategy with adaptive particle swarm [...] Read more.
Effective and timely collision avoidance decision support is essential for super-large vessels navigating in port waters. To guarantee the navigational safety of super-large vessels, this work proposes a collision avoidance decision support method based on the curve increment strategy with adaptive particle swarm optimization (CIPSO). Firstly, the objective function is constructed based on the multi-objective optimization method. Here, a fuzzy comprehensive evaluation (FCE)-based vessel collision hazard model and vessel speed-varying energy-loss model integrating the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) are involved. Furthermore, in response to the limitations of the PSO algorithm, which is prone to falling into local optima in the later stages of iteration, a curve increment strategy is incorporated. To improve the performance of the global optimization, it is optimized using a local followed by global search method. The iterative evolution of CIPSO is used to obtain the optimal decision value in the set domain of feasible solutions. Finally, the effectiveness and feasibility of the proposed method are verified by the numerical simulation and large vessel maneuvering simulator, which can provide collision avoidance decision support for ship pilots. Full article
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