Andreas Berntsen Løvland, Helge Fredriksen, John Markus Bjørndalen
{"title":"Predicting the destination port of fishing vessels utilizing transformers","authors":"Andreas Berntsen Løvland, Helge Fredriksen, John Markus Bjørndalen","doi":"10.1016/j.martra.2025.100131","DOIUrl":"10.1016/j.martra.2025.100131","url":null,"abstract":"<div><div>Vast databases on historical ship traffic are currently freely available in the form of AIS (Automatic Identification System) messages dating back to as early as 2002. This provides a rich source for training deep learning models for predicting various behaviors of vessels, which in this context is motivated by resource management of fisheries. In this paper, we explore the possibility for combining a transformer model’s powerful capabilities for long-term path prediction with added logic to infer probable destination harbors for fishing vessels. An additional baseline model is also developed for comparison, based on historically preferred harbors for the vessels. With AIS data from the Troms and Finnmark region of Norway, the prediction accuracy of the trained model is found to be highly dependent on the number of past tracked positions of the vessel. We foresee that a new and more precise model will need to incorporate not only dynamic AIS data, but static information about harbors and vessel types during training and inference.</div></div>","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"8 ","pages":"Article 100131"},"PeriodicalIF":3.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measuring the impact of port congestion on containership freight rates","authors":"Nektarios A. Michail , Konstantinos D. Melas","doi":"10.1016/j.martra.2025.100130","DOIUrl":"10.1016/j.martra.2025.100130","url":null,"abstract":"<div><div>We examine the impact of port congestion on containership freight rates. Our overall results show that port congestion has a positive and significant effect on containership freight rates. The most important region is Asia, where a 1 % increase in port congestion has a >1 % effect on shipping freight rates. This suggests that the region, being the world's largest manufacturing area and an integral part of the supply chain, has much more importance than previously considered. As such, the results highlight the importance of the manufacturing region in supply chains and are also in line with the derived demand system in shipping. As per the results, a return to the pre-pandemic congestion levels in Asia would lead to at least a 25 % decline in containership freight costs.</div></div>","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"8 ","pages":"Article 100130"},"PeriodicalIF":3.9,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sang-A Park , Deuk-Jin Park , Jeong-Bin Yim , Hyung-ju Kim
{"title":"A Bayesian network model integrating data and expert insights for fishing ship risk assessment","authors":"Sang-A Park , Deuk-Jin Park , Jeong-Bin Yim , Hyung-ju Kim","doi":"10.1016/j.martra.2024.100128","DOIUrl":"10.1016/j.martra.2024.100128","url":null,"abstract":"<div><div>Marine accidents can result in severe economic losses and casualties, underscoring the critical need for effective risk assessment.. In this study, quantitative marine accident reports from Korea that objectively describe accident variables were collected and classified to analyze marine accidents of fishing ships To analyze the causes of accidents involving different types of fishing ships, a survey with subject matter experts (SMEs) was conducted. A fishing ship accident Bayesian network (FABN) scenario was then developed by integrating fishing ship accident data with SME insights. The FABN was comprehensively modeled based on the scenario, with marine accidents being modeled based on causal variables each marine accident. Changes in the output value of the FABN were verified via a sensitivity analysis, and the independence and statistical significance of the model were confirmed using a statistical analysis of the collected data. FABN allows for the immediate assessment of the probability of marine accidents related to fishing ships by utilizing network structures, and provides the advantage of structurally assessing ship accident risks</div></div>","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"8 ","pages":"Article 100128"},"PeriodicalIF":3.9,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adrian Nicoll , Jackie Dawson , Jérôme Marty , Michael Sawada , Luke Copland
{"title":"Comparative and critical analysis of data sources used for ship traffic spatial pattern analysis in Canada and across the global Arctic","authors":"Adrian Nicoll , Jackie Dawson , Jérôme Marty , Michael Sawada , Luke Copland","doi":"10.1016/j.martra.2025.100129","DOIUrl":"10.1016/j.martra.2025.100129","url":null,"abstract":"<div><div>This study presents a comprehensive comparative analysis of three primary datasets commonly employed to evaluate shipping patterns in Arctic waters: 1) Northern Canada Vessel Traffic Zone (NORDREG), 2) satellite-based Automatic Identification System (S-AIS) from a private provider, and 3) the Arctic Ship Traffic Database (ASTD). Covering the years 2011 to 2022, the analysis assesses spatial and temporal metrics for each dataset while employing robust data cleaning techniques to address signal manipulation and detection gaps. Findings reveal that S-AIS and NORDREG excel in detecting vessel traffic in Canadian waters, including the Northwest Passage (NWP), while ASTD demonstrates strong performance in regions with dense terrestrial AIS coverage, such as Norway and Iceland. However, ASTD is less effective along critical shipping routes, including the NWP and the Northern Sea Route (NSR), where S-AIS provides broader coverage. Both datasets indicate an upward trend in AIS-based traffic throughout the Arctic. The results underscore the value of fusing S-AIS and ASTD datasets to provide a more complete and accurate understanding of Arctic shipping patterns. This research offers critical insights for policymakers and researchers selecting ship traffic data for regional and global Arctic analyses, maritime safety, and environmental decision-making.</div></div>","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"8 ","pages":"Article 100129"},"PeriodicalIF":3.9,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Maritime safety and risk analysis","authors":"Jasmine Siu Lee Lam","doi":"10.1016/j.martra.2024.100127","DOIUrl":"10.1016/j.martra.2024.100127","url":null,"abstract":"","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"8 ","pages":"Article 100127"},"PeriodicalIF":3.9,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ports as business eco-systems in transition","authors":"Elvira Haezendonck , Peter W. de Langen","doi":"10.1016/j.martra.2024.100125","DOIUrl":"10.1016/j.martra.2024.100125","url":null,"abstract":"","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"7 ","pages":"Article 100125"},"PeriodicalIF":3.9,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142698382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Big data and artificial intelligence in maritime transport research","authors":"Shuaian Wang , Ran Yan , Min Xu","doi":"10.1016/j.martra.2024.100123","DOIUrl":"10.1016/j.martra.2024.100123","url":null,"abstract":"","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"7 ","pages":"Article 100123"},"PeriodicalIF":3.9,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nazanin Sharif , Mikael Rönnqvist , Jean-François Cordeau , Jean-François Audy , Gurjeet Warya , Trung Ngo
{"title":"Multi-objective vessel routing problems with safety considerations: A review","authors":"Nazanin Sharif , Mikael Rönnqvist , Jean-François Cordeau , Jean-François Audy , Gurjeet Warya , Trung Ngo","doi":"10.1016/j.martra.2024.100122","DOIUrl":"10.1016/j.martra.2024.100122","url":null,"abstract":"<div><div>This paper provides a review of vessel route planning with a focus on safety considerations and the complexity of multi-objective decision-making processes. This complexity arises from the difficulty of finding an appropriate balance between several objectives and safety concerns, often conflicting, that adequately reflects the preferences of the decision makers. The maritime industry faces the challenge of enhancing vessel route optimization for safety, operational efficiency, and cost-effectiveness. We thus describe quantitative methods to find routes that effectively balance multiple objectives, including safety, fuel consumption, and route duration. A significant focus is on the complexity of multi-criteria decision making in this area, highlighting various methodologies for balancing the different objectives. Safety is critical in this context, involving a thorough consideration of navigational risks, environmental factors, and compliance with International Maritime Organization regulations. Specifically, we introduce quantitative approaches for integrating key safety aspects into the decision-making process, including dynamic stability, the probability of bow slamming, and the occurrence of green water.</div></div>","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"7 ","pages":"Article 100122"},"PeriodicalIF":3.9,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Operations Research in Maritime Logistics","authors":"Kjetil Fagerholt , Frank Meisel","doi":"10.1016/j.martra.2024.100119","DOIUrl":"10.1016/j.martra.2024.100119","url":null,"abstract":"","PeriodicalId":100885,"journal":{"name":"Maritime Transport Research","volume":"7 ","pages":"Article 100119"},"PeriodicalIF":3.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}