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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Pandemic-induced uncertainty and maritime terrorism: A quantile-on-quantile analysis of major maritime economies</title>
      <link>https://trid.trb.org/View/2680188</link>
      <description><![CDATA[Pandemic-induced uncertainty reshaped global dynamics, creating critical vulnerabilities in maritime security and intensifying terrorism threats at sea. Supply chain disruptions, weakened economies, and strained international cooperation further compounded the complexity and reach of maritime terrorism, amplifying its global implications. This study investigates the asymmetric impact of pandemic-induced uncertainty on maritime terrorism in 10 selected maritime nations (the USA, China, Somalia, Singapore, Brazil, India, Greece, Nigeria, Australia, and Russia). Unlike past investigations that focused entirely on COVID-19, the present study applies a comprehensive pandemic-related uncertainty index, integrating datasets from various pandemics, including Avian Flu, Ebola, MERS, COVID-19, SARS, and others. The Quantile-on-Quantile technique is applied instead of traditional panel data methods, which often overlook country-specific contexts. This advanced instrument enables an exhaustive analysis of the asymmetric linkage between variables within individual nations. Results reveal an inverse connection between pandemic uncertainty and maritime terrorism in the USA, China, Singapore, and Australia. Meanwhile, Somalia, Brazil, India, and Nigeria show a positive association. However, mixed findings emerge in Russia and Greece, reflecting complex and varied dynamics. These findings underscore the critical need for policymakers to formulate customized policies to monitor the evolving impact of pandemic uncertainty on maritime terrorism, which varies across different quantiles.]]></description>
      <pubDate>Thu, 25 Jun 2026 09:40:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680188</guid>
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    <item>
      <title>Multinational responses to Somali piracy: the emergence and contribution of combined task force 151 (2009–2023)</title>
      <link>https://trid.trb.org/View/2662680</link>
      <description><![CDATA[The spike in Somali piracy in the Gulf of Aden after 2008 pushed the international community toward a rare experiment in naval cooperation. Focusing on Combined Task Force 151 (CTF-151), this study traces how the task force was formed, what its mandate enabled, and how piracy evolved between 2009 and 2023. Drawing on UN resolutions, CMF/CTF-151 documents, and IMB incident records, it combines qualitative document analysis with a simple trend reading of reported attacks. The evidence suggests a steep and lasting drop in incidents after 2012, consistent with sustained patrols, coordinated transit protection, and tighter shipboard precautions. Still, the decline cannot be attributed to CTF-151 alone. Industry measures, parallel EU/NATO missions, seasonal constraints, and persistent onshore drivers—political fragility, illegal fishing grievances, and coastal poverty—remain part of the picture. The paper argues that deterrence at sea must be paired with long-term stabilization on land.]]></description>
      <pubDate>Fri, 01 May 2026 14:33:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2662680</guid>
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    <item>
      <title>The economic impact of piracy: a critical assessment of maritime security and trade disruptions in the Gulf of Guinea</title>
      <link>https://trid.trb.org/View/2658009</link>
      <description><![CDATA[The Gulf of Guinea (GoG) is a region that is used as a hub for piracy. In 2020, more than 95% of global piracy incidents took place in this region. The high incidence of piracy places a significant economic burden on trade, resulting in increased operational costs, higher insurance premiums, and reduced port efficiency. This study provides a comprehensive analysis of the economic impact of piracy in the GoG, based on both quantitative data and qualitative findings. Key drivers of piracy include poverty, unemployment, poor governance, and corruption in maritime security institutions. The study also assesses key projects in the fight against piracy, such as the Nigerian Deep Blue Project, the Yaoundé Code of Conduct (YCoC), and international cooperation, as well as technical issues such as shiprider agreements, unmanned systems, and advanced maritime surveillance systems. Despite some decline in piracy incidents in the GoG and some initiatives, foreign investment in the region remains insufficient, and regional trade cannot develop. The analysis concludes that piracy will continue to hinder the region’s development unless regional coordination is improved, legislation is harmonised, and comprehensive economic development is achieved. Addressing maritime security in the region, supporting strategic and security-related infrastructure reforms, and managing them with sustainable investments will also contribute to the region’s economic development.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658009</guid>
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    <item>
      <title>Assessing the possible influence of maritime piracy on African Continental Free Trade Area (AfCFTA) in Nigeria</title>
      <link>https://trid.trb.org/View/2628050</link>
      <description><![CDATA[Maritime piracy has severely disrupted Nigeria’s maritime domain, undermining the numerous benefits promised by the African Continental Free Trade Agreement (AfCFTA) and posing a significant threat to its successful implementation. As this study highlights, maritime piracy in Nigeria emerges partly as a deviant response to the socio-economic pressures intensified by neoliberalism and globalization. By examining maritime piracy through the lens of Global Anomie Theory (GAT) and civic governance frameworks – supplemented by insights from interviewees – this research offers a deeper understanding of how such criminal activities could jeopardize Nigeria’s ability to fully realize the objectives of the AfCFTA. In doing so, it contributes to the growing body of literature on the intersection of free trade agreements and maritime security challenges. Given the AfCFTA protocols that emphasize Member States’ responsibilities to safeguard their security interests, this study argues that Nigeria must extend its anti-piracy strategies beyond domestic initiatives. Specifically, it recommends that Nigeria strengthen international cooperation mechanisms as a critical step toward ensuring the effective implementation of the AfCFTA agreement.]]></description>
      <pubDate>Thu, 26 Feb 2026 14:51:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628050</guid>
    </item>
    <item>
      <title>Assessment of the Applications of Artificial Intelligence in Predictive Models for Maritime Piracy Protection</title>
      <link>https://trid.trb.org/View/2637656</link>
      <description><![CDATA[Maritime piracy poses a significant threat to global transportation, particularly in high-risk regions such as the Gulf of Aden, the Strait of Malacca, and the Gulf of Guinea. This article examines the role of artificial intelligence (AI) in enhancing maritime security by analyzing currently used predictive models for detecting and preventing piracy attacks. The application of AI-based systems, integrating data from the AIS system, satellites, and radars, enables early threat detection and risk assessment. The paper discusses projects such as IPATCH, PROMENADE, and BLUE DOME, which use machine learning, real-time data analysis, and automated decision-making systems to improve piracy protection. Challenges related to data quality and evolving pirate strategies are identified. The future of AI in piracy protection relies on innovations such as deep learning, integration with 5G, and pattern recognition, which will enhance the effectiveness of predictive systems.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2637656</guid>
    </item>
    <item>
      <title>Pirate-GPT: A locally deployed large language model framework for reliable offline anti-piracy decision support and knowledge retrieval in maritime operations</title>
      <link>https://trid.trb.org/View/2623300</link>
      <description><![CDATA[Ensuring the reliability and safety of maritime transportation systems is critically impeded by the fragmentation, complexity, and redundancy of piracy-related information. This study introduces Pirate-GPT, a domain-specific question answering framework built upon large language models(LLMs), designed to advance anti-piracy decision support and maritime knowledge management. Pirate-GPT integrates a semantic sliding-window segmentation algorithm to construct a semantically complete and robust vector database, facilitating precise information retrieval. The framework further employs an Agent collaboration mechanism and a “two-stage retrieval” process, significantly improving answer relevance and explainability while reducing hallucination rates. Centered on the Qwen2.5 LLM and optimized through Generative Pre-trained Transformer Quantization (GPTQ), Pirate-GPT supports efficient, stable, and privacy-preserving local deployment in offline and resource-constrained maritime environments. The system was evaluated using 7399 piracy reports and 230 related documents, and it consistently outperformed baseline models, with LooseMatch scores exceeding 90% and marked reductions in hallucinations across various query types. Ablation studies confirmed the essential contributions of each module to the system’s overall performance. Consequently, Pirate-GPT offers a scalable, reliable, and practical solution, providing a systematic approach to integrating complex domain knowledge and supporting robust risk assessment and decision-making in real-world maritime operations.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623300</guid>
    </item>
    <item>
      <title>Genetic Algorithm for Ship Robbery Emergency Reporting System</title>
      <link>https://trid.trb.org/View/2598396</link>
      <description><![CDATA[In contemporary maritime navigation, ships in distress primarily rely on satellite systems in conjunction with radio systems within the framework of the Global Maritime Distress and Safety System (GMDSS) to transmit distress signals. However, the insufficient confidentiality of satellite data enables pirates engaged in ship hijacking to intercept these signals, potentially endangering the safety of hostages on board. Additionally, the high communication costs associated with satellite information transmission often discourage fishing ships from incurring these expenses. Given these cost constraints, this study seeks to develop an intelligent emergency distress notification method integrated with the Automatic Identification System (AIS). Specifically, this study introduces an innovative intelligent radio emergency notification system by incorporating the concept of radio relay stations. The proposed system integrates the Genetic Algorithm (GA) with the Maritime Geographic Information System (MGIS) as an alternative rescue method for ships in distress. The system collects all relevant information from the distressed ship through shore stations, enabling it to respond to the ship and verify the receipt of distress messages transmitted via AIS. The proposed method functions as an intermediary for distress signal transmission and confirmation. By gathering ship positions, it establishes a mobile network for message dissemination, thereby enhancing the reliability and efficiency of emergency distress communications at sea.]]></description>
      <pubDate>Mon, 22 Dec 2025 17:03:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2598396</guid>
    </item>
    <item>
      <title>An examination of the pirate cycle theory: insights from modern piracy dynamics</title>
      <link>https://trid.trb.org/View/2606435</link>
      <description><![CDATA[In the 21st century, the understanding of piracy has remained under-theorized despite significant academic studies. This article examines contemporary maritime piracy through the theoretical framework of the Piracy Cycle Theory. The study examines the piracy incidents reported to the International Maritime Bureau (IMB) in 2023 through content analysis. The findings support the concepts of ‘initial formation’ and ‘transitional consolidation’ in the pirate cycle theory. Specifically, it reveals that piracy in Africa and America is currently in the transitional consolidation stage, while Asia is still experiencing the initial formation stage. Notably, no assaults were recorded at the ‘potential state-like establishment’ stage in the analysis. The findings largely support the pirate cycle theory. However, it is important to consider alternative explanations for the newly observed trends. It has also been revealed that shipping companies must take region-specific precautions to minimize the adverse effects of piracy and tailor their strategies to the risks present in different areas.]]></description>
      <pubDate>Mon, 17 Nov 2025 09:00:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2606435</guid>
    </item>
    <item>
      <title>Maritime insecurity and dhows' territory in the Arabian Sea</title>
      <link>https://trid.trb.org/View/2583422</link>
      <description><![CDATA[Containerized maritime transport exerts an increasing dominance over shipping routes, marginalizing traditional dhows in the Arabian Sea thanks to tremendous economies of scale it enables. Thus, neglected territories by container shipping lines are the only ones where dhows still operate. By supplying small coastal settlements, conflict regions, embargoed countries like Iran, or even embargoed products, dhows assume security risks that other actors—regular shipping lines and insurers—refuse to bear. Thus, the rising security risks in the Red Sea since November 19, 2023, appear as a windfall for dhow business and, by this way, for the gauge of its sensitivity to varying kinds and levels of risk so as to demonstrate the connection between security and the span of dhows territory. The purpose of this article is to utilize available port data from the region (mainly Djibouti's) and AIS data from ship tracking sites to identify and measure variations in dhow activity in the Gulf of Aden and the Red Sea. Then, after a characterization of various risks of on-shore and off-shore security in the region, the authors rely on indicators of war risk insurance market to assess the correlation of their evolutions with the level of dhows activity.]]></description>
      <pubDate>Fri, 24 Oct 2025 16:53:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2583422</guid>
    </item>
    <item>
      <title>Maritime piracy and armed robbery analysis in the Straits of Malacca and Singapore through the utilization of natural language processing</title>
      <link>https://trid.trb.org/View/2569503</link>
      <description><![CDATA[Piracy and armed robbery have become serious problems in maritime economic activities, particularly in the Straits of Malacca and Singapore. These crimes occur due to various influential factors, necessitating analysis through incident reports. This study aims to identify the factors influencing piracy and armed robbery in these areas using natural language processing (NLP) technologies. Data were obtained from reports compiled by relevant organizations such as the Global Integrated Shipping Information System (GISIS) from the International Maritime Organization (IMO) and Annual Reports on Piracy and Armed Robbery from the Regional Cooperation Agreement on Combating Piracy and Armed Robbery against Ships in Asia (ReCAAP). These data were reconstructed through NLP and further analyzed using the Bidirectional Encoder Representations from Transformer (BERT) model derivative, BERTopic. Several topics were obtained from the analysis, suggesting key factors influencing the outcome of piracy and armed robbery incidents. These topics will serve as the basis for suggestions and solution provisions that can be effectively applied and utilized to further decrease the frequency and success rate of piracy and armed robbery in the future. The findings provide crucial insights for developing strategies to mitigate the impact of these criminal activities on maritime economic activities.]]></description>
      <pubDate>Fri, 18 Jul 2025 09:03:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569503</guid>
    </item>
    <item>
      <title>A Bayesian network-based TOPSIS framework to dynamically control the risk of maritime piracy</title>
      <link>https://trid.trb.org/View/2437435</link>
      <description><![CDATA[Piracy has long plagued the maritime industry, and has led to significant losses of life and goods. The risk of maritime piracy is largely predicted at present based on static analysis. This does not suitably address practical needs because the behavior and activities of maritime pirates are dynamic. Selecting an appropriate strategy for reducing the risk of piracy under a dynamic environment featuring uncertainty thus remains a key challenge. In this study, the authors propose a two-stage technique for order of preference by similarity to an ideal solution (TOPSIS) model based on the Bayesian network (BN). A data-driven BN is constructed in the first stage of the proposed method to identify the causal relationships influencing the behaviors of pirates. The second stage involves calculating a decision matrix of the strategies by using TOPSIS, where this enhances the strength of risk prediction and dynamic diagnosis by the BN. The main novelty of the proposed model is that it can provide quantitative measurements of strategies for reducing the probability of piracy in a dynamic environment. It provides a decision-making tool for researchers, shipping companies, and national navies to assess the risk of piracy and select effective measures to reduce its likelihood.]]></description>
      <pubDate>Sat, 30 Nov 2024 15:26:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2437435</guid>
    </item>
    <item>
      <title>RETRACTED: Unraveling the Asymmetric Impact of Pandemic Uncertainty on Maritime Crimes: A Comparative Analysis of Ten Maritime Nations</title>
      <link>https://trid.trb.org/View/2410467</link>
      <description><![CDATA[At the request of Sage and the Journal Editors, the following article has been retracted: Cao, X., Cui, Z., Ali, S., & Nazar, R. Unraveling the Asymmetric Impact of Pandemic Uncertainty on Maritime Crimes: A Comparative Analysis of Ten Maritime Nations. Transportation Research Record: Journal of the Transportation Research Board. 2025; 2679(1). https://doi.org/10.1177/03611981241258755 Sage was made aware of concerns of overlapping figures between this article and several other articles by the same author group. Including: Figure 2a appears to overlap with Figure 2b in an article by the same author group; Figure 2c appears to overlap with Figure 2viii in an article by the same author group. The authors stated that the similarities between figures were related to the nature of the methods and provided raw data. However, review by the Journal Editor determined that the similarity in patterns observed in these figures was greater than suggested by the different data types present. During investigation of these concerns, Sage became aware that the submission contains indicators of third-party involvement. Due to concerns about the integrity of the research process and the authenticity of the research, this article has been retracted. The authors did not respond to the decision to retract.]]></description>
      <pubDate>Wed, 31 Jul 2024 10:45:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2410467</guid>
    </item>
    <item>
      <title>A Bayesian network-based tool for crisis classification in piracy or armed robbery incidents on passenger ships</title>
      <link>https://trid.trb.org/View/2375607</link>
      <description><![CDATA[Piracy and armed robbery continue to pose significant security threats to the shipping industry. This paper presents a real-time threat assessment and crisis classification tool for piracy or armed robbery incidents. The tool is part of a crisis classification module that addresses various categories of security threats. This module is currently being developed as part of the EU-funded research project ISOLA, which aims to introduce an intelligent security superintendence ecosystem. The ecosystem is designed to complement the existing ship security processes and measures applied onboard passenger ships. The tool operates by providing real-time threat classification and subsequent warnings by analysing data collected from the ship’s legacy systems and installed sensors with the utilisation of Bayesian probabilistic techniques, particularly Bayesian Networks. The BN model developed for this purpose is thoroughly examined, and its validation is presented through indicative case studies involving piracy and armed robbery. The main objective is to improve situational awareness, enhance vigilance and early threat detection, and support the decision-making process for the Master and crew, especially under time-sensitive circumstances and stressful conditions.]]></description>
      <pubDate>Sun, 30 Jun 2024 16:02:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2375607</guid>
    </item>
    <item>
      <title>A Threat to Maritime Trade: Analysis of Piracy Attacks Between 2015 and 2022 and the Period of COVID-19</title>
      <link>https://trid.trb.org/View/2350427</link>
      <description><![CDATA[More than 80 percent of world trade is transported by sea. Maritime piracy negatively affects international maritime transport and trade. The aim of the study is to analyze maritime piracy attacks between 2015-2022 and during the coronavirus disease-2019 (COVID-19) period. In the study, a literature review, main reasons and statistics for piracy and armed robbery attacks, international efforts to combat maritime piracy were examined and maritime piracy attacks were analyzed in 2015-2022 and the COVID-19 period. The results of the main findings are as follows; the most piracy attacks occurred in 2015, the most attacks were occurred in March-April-May majority of attacks occurred between the hours 24: 00-04: 00, the most attacks occurred in South East Asia, the most types of attacks against to ships was boarded. Marshall Islands-flagged ships were the most attacked. There is a weak statistical relationship between the piracy attacks by months and regions and between the piracy attacks by years and type of attacks. There is no statistical relationship between other variables.]]></description>
      <pubDate>Fri, 28 Jun 2024 14:00:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2350427</guid>
    </item>
    <item>
      <title>Analysis of maritime piracy trends and patterns using spatial autocorrelation in Africa</title>
      <link>https://trid.trb.org/View/2381690</link>
      <description><![CDATA[Many studies have analyzed causation factors for piracy, but failed to quantitatively examine how piracy trends in regions have changed. The research aimed to establish the changing patterns of maritime piracy in Africa. The study utilized world piracy data from the National Geospatial Intelligence Agency, which was analyzed using spatial auto-correlation tools. Getis-Ord Gi* statistic identified piracy clusters and hot spot comparison tool compared the hot spot layers in East and West Africa. Autocorrelation analysis results suggest changing frequency of piracy incidents in the study areas before and after 2012. The mean Getis-Ord Gi* values for East Africa were 0.35946 and 0.07839 before and after 2012, illustrating agreater change. However, West Africa mean values were 0.60917 and 0.43408 pre and post 2012, suggesting minimal change. The comparison analysis results generated a smaller similarity value for East Africa (0.43350) and a larger index for West Africa (0.9867). West Africa recorded many incidents in the study period; hence, piracy intensity was almost similar. The study revealed high similarities in piracy events in West Africa, and low similarities in East Africa pre and post 2012. These have implications for understanding the changing dynamics of maritime piracy in Africa, and asserting spatial analysis.]]></description>
      <pubDate>Fri, 14 Jun 2024 10:27:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2381690</guid>
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