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Development and Implementation of Autonomous Vehicles and Their Impact on...
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Development and Implementation of Autonomous Vehicles and Their Impact on Maritime Safety

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: 1 June 2024 | Viewed by 1145

Special Issue Editors

Dr. David Moreno-Salinas

E-Mail Website
Guest Editor
Department of Computer Science and Automatic Control, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain
Interests: localization; control; sensor networks; marine vehicles; identification and modelling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Shiyuan Zheng

E-Mail Website
Guest Editor
College of Transport and Communications, Shanghai Maritime University, Shanghai, China
Interests: transport network optimization; port operation management; port governance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Maritime safety is a critical aspect of the shipping industry, and advancements in technology have facilitated new opportunities to enhance safety measures. This Special Issue aims to explore the application of smart shipping navigation and vessel traffic services in improving maritime safety. We invite researchers and practitioners to submit their original research and review articles that contribute to the understanding and implementation of innovative technologies for maritime safety.

The Special Issue will focus on, but is not limited to, the following topics:

  • Smart shipping navigation systems and their role in ensuring safe vessel operations;
  • Vessel traffic services and their contribution to maritime safety management;
  • Integration of artificial intelligence, Internet of Things (IoT), and machine learning techniques in maritime safety;
  • Development and implementation of autonomous marine vehicles and their impact on maritime safety;
  • Risk assessment and management in smart shipping navigation and vessel traffic services;
  • Cybersecurity challenges and solutions in smart shipping and vessel traffic management;
  • Case studies and practical applications of smart shipping technologies for maritime safety.

Dr. David Moreno-Salinas
Prof. Dr. Shiyuan Zheng
Guest Editors

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

  • smart shipping navigation
  • vessel traffic services
  • autonomous marine vehicles
  • maritime safety
  • risk assessment and management

Published Papers (1 paper)

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Research

33 pages, 16036 KiB  
Article
Robust Decision-Making for the Reactive Collision Avoidance of Autonomous Ships against Various Perception Sensor Noise Levels
by Paul Lee, Gerasimos Theotokatos and Evangelos Boulougouris
J. Mar. Sci. Eng. 2024, 12(4), 557; https://doi.org/10.3390/jmse12040557 - 27 Mar 2024
Viewed by 763
Abstract
Autonomous ships are expected to extensively rely on perception sensors for situation awareness and safety during challenging operations, such as reactive collision avoidance. However, sensor noise is inevitable and its impact on end-to-end decision-making has not been addressed yet. This study aims to [...] Read more.
Autonomous ships are expected to extensively rely on perception sensors for situation awareness and safety during challenging operations, such as reactive collision avoidance. However, sensor noise is inevitable and its impact on end-to-end decision-making has not been addressed yet. This study aims to develop a methodology to enhance the robustness of decision-making for the reactive collision avoidance of autonomous ships against various perception sensor noise levels. A Gaussian-based noisy perception sensor is employed, where its noisy measurements and noise variance are incorporated into the decision-making as observations. A deep reinforcement learning agent is employed, which is trained in different noise variances. Robustness metrics that quantify the robustness of the agent’s decision-making are defined. A case study of a container ship using a LIDAR in a single static obstacle environment is investigated. Simulation results indicate sophisticated decision-making of the trained agent prioritising safety over efficiency when the noise variance is higher by conducting larger evasive manoeuvres. Sensitivity analysis indicates the criticality of the noise variance observation on the agent’s decision-making. Robustness is verified against noise variance up to 132% from its maximum trained value. Robustness is verified only up to 76% when the agent is trained without the noise variance observation with lack of its prior sophisticated decision-making. This study contributes towards the development of autonomous systems that can make safe and robust decisions under uncertainty. Full article
(This article belongs to the Special Issue Development and Implementation of Autonomous Vehicles and Their Impact on Maritime Safety)
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