Safe, Efficient and Sustainable Autonomous Maritime Transportation System

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 651

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Department of Validation Intelligence for Autonomous Software Systems, Simula Research Laboratory, 0164 Oslo, Norway
Interests: artificial intelligence; machine learning; autonomous systems; autonomous shipping; software engineering/V&V
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There is a rapid increase in digitalization and automation in maritime transport, including the use of artificial intelligence (AI) to increase the safety and efficiency of maritime operations. Consequently, developing autonomous maritime transportation systems (vessels and other systems used in vessel traffic monitoring, control, and management) brings challenges and opportunities in terms of security, performance, safety, sustainability, and compliance with regulatory frameworks. For example, there is increasing pressure on vessel operators and owners to comply with CO2 emission regulations, such as CII, EU ITS, etc.

This Special Issue calls for innovative contributions in using data science and artificial intelligence to improve the safety and efficiency of autonomous maritime transportation systems, including compliance with emerging frameworks for reducing the maritime carbon footprint.

Dr. Dusica Marijan
Guest Editor

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Keywords

  • autonomous vessels
  • safe navigation
  • efficient navigation
  • sustainable navigation
  • compliance with maritime regulation

Published Papers (1 paper)

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Research

23 pages, 542 KiB  
Article
Real-Time Batch Optimization for the Stochastic Container Relocation Problem
by Sifang Zhou and Qingnian Zhang
Appl. Sci. 2024, 14(6), 2624; https://doi.org/10.3390/app14062624 - 21 Mar 2024
Viewed by 489
Abstract
The container relocation problem (CRP) is an important factor affecting the operation efficiency of container terminal yards, and it has attracted much attention for decades. The CRP during the pickup operations of import containers is still an intractable problem for two reasons: the [...] Read more.
The container relocation problem (CRP) is an important factor affecting the operation efficiency of container terminal yards, and it has attracted much attention for decades. The CRP during the pickup operations of import containers is still an intractable problem for two reasons: the first is that the solution efficiency of the algorithms developed in the existing literature cannot meet the real-time operation requirements; the second is that the pre-optimized operation plan cannot cope with the changes in the real-time operation scenarios caused by the uncertainty of the arrival time of external trucks. This paper proposes an optimization method for the real-time operation scenario which aims to solve the most reasonable operation plan quickly according to the arrivals of external trucks, in which a dynamic upper bound of the optimal solution is derived based on the dynamic programming model of the import containers’ CRP, and an approximate optimal solution can be obtained by minimizing this dynamic upper bound. A heuristic algorithm based on three relocation rules is developed to implement this method, considering the adjustment of the pickup sequence of the target containers. Numerical experiments show that (1) when the number of a batch of target containers is less than 10 (excluding target containers that can be directly picked up), the method proposed in this paper can solve the problem quickly to meet the demand of optimizing real-time pickup operations; (2) compared with other outstanding algorithms, the quality of the solutions obtained by this method is also improved; and (3) this method can be applied to the most container terminals for optimizing real-time pickup operations. Full article
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