<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSJhbGwiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMCIgLz48L3BhcmFtcz48ZmlsdGVycz48ZmlsdGVyIGZpZWxkPSJpbmRleHRlcm1zIiB2YWx1ZT0iJnF1b3Q7UG9ydCB0cmFmZmljJnF1b3Q7IiBvcmlnaW5hbF92YWx1ZT0iJnF1b3Q7UG9ydCB0cmFmZmljJnF1b3Q7IiAvPjwvZmlsdGVycz48cmFuZ2VzIC8+PHNvcnRzPjxzb3J0IGZpZWxkPSJwdWJsaXNoZWQiIG9yZGVyPSJkZXNjIiAvPjwvc29ydHM+PHBlcnNpc3RzPjxwZXJzaXN0IG5hbWU9InJhbmdldHlwZSIgdmFsdWU9InB1Ymxpc2hlZGRhdGUiIC8+PC9wZXJzaXN0cz48L3NlYXJjaD4=" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <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>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
    </image>
    <item>
      <title>2025 Report from the European Commission on Greenhouse Gas Emissions from Maritime Transport: Commission Staff Working Document</title>
      <link>https://trid.trb.org/View/2700536</link>
      <description><![CDATA[This is the seventh report on GHG emissions from ships entering and leaving ports in the European Economic Area (EEA), collected under the EU MRV Maritime Regulation. This Regulation requires shipping companies to monitor during the reporting period key indicators such as GHG emissions, fuel consumption and other relevant information. This data is then checked by independent verifiers accredited by national accreditation bodies. Shipping companies have an obligation to report relevant data once satisfactorily verified through the dedicated IT system, THETIS-MRV . The Commission subsequently publishes the verified data and analyses main trends in the form of an annual report. The currently available set of MRV data is contributing to an enhanced understanding of the GHG emissions originating from the maritime transport sector. The published raw data represents a valuable asset to research organisations, public authorities, and other market actors for analyses and studies on the maritime transport sector and its energy and environmental performance. This data is important to support policy discussions and to support the implementation and track the effectiveness of climate policies. In addition, it constitutes an important input for the sector in order to take more effective and efficient climate measures. The main objective of this report is to examine trends in emissions and energy efficiency characteristics over the seven available reporting cycles since the entry into force of the EU MRV Maritime Regulation. This report is based on data from the EU MRV system over the period 2018-2024. The monitoring, reporting, and verification obligations apply since 2018 to ships above 5 000 gross tonnage (GT) while travelling to or from an EEA port to transport goods or passengers for commercial purposes. The Regulation is flag-neutral, which means that ships must monitor and report their emissions regardless of their flag.]]></description>
      <pubDate>Thu, 10 Sep 2026 16:57:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2700536</guid>
    </item>
    <item>
      <title>Navigating Possibilities: Unlocking Tennessee’s Waterways for Interstate Freight Transportation</title>
      <link>https://trid.trb.org/View/2752389</link>
      <description><![CDATA[The study evaluated the inland waterways and port facilities of the State and analyzed their potential for transportation services as part of the overall State Transportation plan. The focus of the study evaluated the current flows and costs of cargo movement and commodity class; the path related to origin and destination; the viability of potential port assets that could be utilized; the effectiveness of optimizing current State infrastructure and connecting waterways for enhancing the transportation network. By leveraging its inland waterways and investing in transportation infrastructure, Tennessee can enhance its competitiveness, promote sustainable development, and build a more resilient and prosperous future. Tennessee's geographical location creates both challenges and opportunities as a strategic multi-modal hub for national commerce. By developing its waterways for freight transportation, the state can capitalize on its central location to facilitate the movement of goods well beyond the state which would serve to attract businesses seeking efficient transportation routes, expand market access for Tennessee-based industries, as well as connect other industries to Tennessee.]]></description>
      <pubDate>Mon, 24 Aug 2026 09:03:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2752389</guid>
    </item>
    <item>
      <title>Delay-induced arrival autocorrelation and its regime-dependent impact on port reliability</title>
      <link>https://trid.trb.org/View/2697251</link>
      <description><![CDATA[Vessel arrivals at maritime ports are often modeled by Poisson processes with independent increments, yet real traffic data often exhibits short-term autocorrelation. Using daily arrival data derived from the Automatic Identification System (AIS), we detect significant positive autocorrelation at short lags even after removing weekly seasonality. This temporal dependence may reshape port congestion dynamics, affecting how congestion emerges, persists, and dissipates. We treat port congestion as a threshold-exceedance recurrent failure event and assess port reliability under uncertainty through failure recurrence, congestion duration, and recovery dynamics, recognizing that sustained congestion itself creates additional risk by propagating delays, slowing recovery, and increasing vulnerability to further disruption. This connects the temporally autocorrelated arrival process directly to port resilience assessment and capacity planning under real traffic. To account for autocorrelation, we develop a delay-induced arrival model that combines independent per-vessel and fractional block-wise delay components to reproduce observed short-lag correlations. Discrete-event simulations of parallel berth queues show that the proposed fractional delay mechanism introduces two distinct statistical effects. Under moderate loads, reduced marginal variance smooths daily transit times and lowers congestion frequency. Under near-capacity loads, positive autocorrelation yields longer and more severe congestion with slower recovery. Thus, temporal dependence has a regime-dependent impact on port reliability: it stabilizes performance under moderate utilization, but amplifies tail risk near saturation by prolonging congested episodes and increasing their severity. Recognizing and monitoring such dependence is essential for reliability assessment under uncertainty and for designing capacity policies that reduce extreme congestion and recovery time.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697251</guid>
    </item>
    <item>
      <title>The role of container port traffic, global value chains participation and logistics performance in Tunisia’s inclusive growth: evidence from quantile on quantile regression and hybrid quantile causality analysis</title>
      <link>https://trid.trb.org/View/2664109</link>
      <description><![CDATA[Maritime transport serves as a strategic foundation for international trade and economic development, providing essential channels for the efficient movement of goods across global markets. As trade volumes expand, maritime container transport emerges as a key driver of economic growth, job creation, and inclusive growth. Moreover, improved logistics performance and the integration of global value chains (GVCs) enhance maritime transport capacity to drive economic competitiveness and long-term prosperity. This study investigates the effects of container port traffic, GVC participation, and logistics performance on inclusive growth in Tunisia from 1990 to 2020. To ensure the reliability of the findings, the study adopts an advanced three-stage methodology that combines quantile-on-quantile regression, wavelet analysis, and hybrid quantile causality. The results reveal a significant positive impact of container port traffic, GVC participation and logistics performance on inclusive growth across various levels of economic development. Moreover, the quantile causality analysis in mean and variance confirms that these variables serve as essential determinants of inclusive growth across all quantiles of the distribution. The robustness of these findings is reinforced by the frequency domain causality test. This study recommends strategic investments in port infrastructure, expanded trade logistics, and the strengthening of international trade partnerships to improve Tunisia’s global competitiveness and accelerate its transition to inclusive growth]]></description>
      <pubDate>Wed, 29 Apr 2026 16:34:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664109</guid>
    </item>
    <item>
      <title>Integrated optimization of vessel sequencing and tugboat scheduling under extreme weather</title>
      <link>https://trid.trb.org/View/2644028</link>
      <description><![CDATA[In recent years, increasingly frequent extreme weather has posed severe challenges to designing vessel entry and exit sequences and tugboat schedules at ports. This study focuses on the integrated optimization of vessel sequencing and tugboat scheduling under extreme weather, emphasizing their coupling and the cascading effects that such conditions may trigger. The study proposes a weather-driven rolling decision mechanism that assesses the interference severity based on specific extreme weather conditions to determine the selected adjustment strategy (interference management or rescheduling strategy). On this basis, an integer programming model is formulated to minimize total vessel in-port time and total tugboat operation time, while incorporating tugboat-vessel coupling and resource constraints on the channel and tugboat under extreme weather. To solve the model efficiently, a hybrid algorithm combining a Genetic Algorithm and an Adaptive Large Neighborhood Search (GAALNS) is developed to generate integrated rescheduling plans. Finally, this study validates the approach through numerical experiments, demonstrates algorithmic superiority, and conducts three sensitivity analyses to examine the effects of key factors on the objective function value. The results provide practical guidance for port authorities in formulating timely vessel sequences and tugboat schedules after extreme weather.]]></description>
      <pubDate>Fri, 20 Mar 2026 14:47:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2644028</guid>
    </item>
    <item>
      <title>Optimizing maritime transport schedule recovery strategies: a novel approach for speeding up and port-skipping in case of disruption</title>
      <link>https://trid.trb.org/View/2618861</link>
      <description><![CDATA[In case of disruption to the liner-shipping schedule, vessels cannot arrive at port calls on schedule, which creates a loss in service quality and credibility with a simultaneous increase in operating costs. Liner-shipping companies usually adopt two significant strategies: speeding up and skipping port calls to reduce such issues. This paper presents a mixed-integer nonlinear programming model for the simultaneous use of speed-up and port-skipping strategies for schedule recovery. The model, by taking into consideration lost revenue and the costs of transshipment for skipped ports, departs from the traditional cost-minimization approach by prioritizing profit maximization. It incorporates strategies for speed-up and port-skipping with loading and unloading variables in the process of optimally determining port calls as per demand and profitability. Decision variables on alternative port selections allow multiport alternatives that consider delays and transshipment costs. The nonlinear model is linearized using exact and approximate techniques and solved using CPLEX software. For large-scale cases, a self-learning particle swarm optimization algorithm is employed. Several test problems demonstrate the effectiveness of the metaheuristic. A real-world case is used to validate the model, showing its capability to derive optimal routes and schedules through the concurrent use strategies. The results show that the proposed model minimizes time deviations and operational losses. Moreover, sensitivity analysis highlights that while speed-up is adequate for shorter delays and less viable with high fuel costs, skipping strategies complement speed-up under significant delays, reinforcing the importance of integrated recovery strategies to address disruptions in the maritime transportation industry.]]></description>
      <pubDate>Wed, 11 Feb 2026 09:17:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2618861</guid>
    </item>
    <item>
      <title>Autonomous Port Traffic Safety Orientated Vehicle Kinematic Information Exploitation Via Port-Like Videos</title>
      <link>https://trid.trb.org/View/2628408</link>
      <description><![CDATA[This study proposes a framework for extracting automatic guided vehicle (AGV) kinematic information from port-like videos, which provides a solution for situation awareness of port surveillance videos. Firstly, vehicle pixel-wise positions in port-like videos are determined by the visual object tracking (SeqTrack) model. Secondly, the extrinsic parameters of the query images are estimated by the generalizable model-free 6-DoF object (Gen6D) pose estimation method. More specifically, a point cloud of AGV is reconstructed with multi-view AGV reference images and the image extrinsic parameters are obtained through structure form motion. The reference image which has the most similar viewpoint as the query image is identified with the Gen6D selection module; as a result, the extrinsic parameters of the reference image can be used to estimate the extrinsic parameters of the query image. After that, the extrinsic parameters of the query image are identified with the support of the Gen6D refinement module. Thirdly, we obtain vehicle displacement by mapping the vehicle point cloud coordinate into the camera coordinate, and then we estimate the vehicle movement information with the help of the generative adversarial network model. Experimental results suggest that the pose estimation metrics average discrepancy distance and 2D re-projection error of our method reach 0.76 and 0.75, respectively. The mean absolute error and root mean squared error of the estimated vehicle displacement reach 0.023, 0.030 for scene #1 (i.e., AGV moves along x-axis of camera coordinate) and 0.182, 0.298 for scene #2 (i.e., camera follows AGV to move along x-axis of camera coordinate).]]></description>
      <pubDate>Thu, 05 Feb 2026 11:52:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628408</guid>
    </item>
    <item>
      <title>2024 Port Performance Freight Statistics Program: Annual Report to Congress</title>
      <link>https://trid.trb.org/View/2651494</link>
      <description><![CDATA[This is the eighth edition of the Port Performance Freight Statistics Program Annual Report, which builds on the foundation of the 2016 Annual Report. This 2024 Annual Report expands upon the first edition in several ways. The throughput and capacity statistics included in the 2016 edition have been updated with the most recently available annual data and, in many cases, have been supplemented with available monthly data. This edition provides additional descriptions of global and national maritime trends to provide a more robust context for understanding port performance and the emerging issues and topics, including supply-chain challenges. This report includes the top 25 ports, port activities in 2022 and 2023, and port capacity and throughput measures. U.S. ports handled 42.9 percent (over $2.28 trillion) of the U.S. international trade by value in 2022. While not reaching the heights of growth in the 2020-2021 period, total U.S. imports of goods grew by almost $424 billion or 14.9 percent while the export of goods grew by more than $324 billion or 18.4 percent between 2021 and 2022. Waterborne vessels are the leading transportation mode for U.S.-international trade in goods. Vessels transported U.S.-international freight at record levels, with cargo value peaking at more than $206 billion in May 2022—up $106 billion (from the $100 billion low recorded in May 2020. In 2023, cargo value declined slightly from mid-2022, reaching $183 billion in August 2023.]]></description>
      <pubDate>Tue, 27 Jan 2026 09:19:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2651494</guid>
    </item>
    <item>
      <title>A Study on Events Held in the Vicinity of the Port Limit of Specified Ports - Considerations for Holding Events Safely, Using Maritime Traffic Regulations-</title>
      <link>https://trid.trb.org/View/2598684</link>
      <description><![CDATA[Based on the Port Regulations Act, various powers are granted to the captain of the port, such as the requirement that event organizers must obtain the permission from the captain of the port when holding an event in the specified port. However, for the event, marine fireworks festivals and drone shows, held in the vicinity of port limit of specified ports, the current Port Regulations Act restricts the measures that the captain of the port can take to ensure the view of navigational safety, despite the possibility that an accident occurred during the event could have a negative impact on port traffic. In this paper, the authors point out the 6 problems with the Port Regulations Act, such as article 32, and propose improvements, referring to the foreign example of fireworks festivals that was held at Singapore in 2022.]]></description>
      <pubDate>Mon, 29 Dec 2025 09:35:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2598684</guid>
    </item>
    <item>
      <title>Managing Risk in the Nation’s Most Consequential Port</title>
      <link>https://trid.trb.org/View/2617662</link>
      <description><![CDATA[The United States Coast Guard's Sector New York refers to New York Harbor as the "Nation's Most Consequential Port" given that up to one-third of the nation’s gross domestic product is located within 250 miles of the harbor. The daunting task of ensuring the safety, security, and environmental protection of these waters, as well as those up to 200 miles offshore and up the Hudson River past Albany, New York, falls upon the captain of the port of Coast Guard Sector New York. Potential risks include: increased vessel sizes, renewable energy projects, autonomous systems, alternative fuels, increased recreational traffic, and cybersecurity threats. Internally, the Coast Guard has adopted a risk management framework that includes a five-step process—identifying hazards, assessing hazards, developing controls and making decisions, implementing controls, and supervising and evaluating controls. While captains of the port do not always consciously follow this five-step process in managing risks to the port, it is a process that is nonetheless routinely used both locally and holistically across the nation in a layered approach. This layered approach to identify and manage evolving and emerging risks helps ensure the safety, security, and environmental protection of the marine transportation system.]]></description>
      <pubDate>Thu, 20 Nov 2025 17:07:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617662</guid>
    </item>
    <item>
      <title>Functional differentiation of container ports: a case in China</title>
      <link>https://trid.trb.org/View/2606437</link>
      <description><![CDATA[The overcapacity in China’s ports has spurred port integration across many provinces but not in the Pearl River Delta (PRD) due to its unique institutional environment. Effective port integration often involves coordinating differentiated functions. We therefore wonder whether port functional differentiation occurs in the PRD. Traditionally, port throughput has been a primary indicator for functional differentiation, constraining the exploration of diverse shipping-related characteristics. This study aims to propose an analytical approach to identify various port functions with seven indicators, considering the multifaceted shipping characteristics of ship traffic and shipping services within a regional port system. The research approach is applied to the PRD container port system in South China, utilizing Automatic Identification System (AIS) data from 2015 to 2022. Furthermore, the study investigates how geographical conditions, industrial development, institutional factors, and port governance structures contribute to the observed functional differentiation. The results reveal evolving functional specialization among the core ports within the PRD. Hong Kong primarily focuses on imports and transshipment, Shenzhen establishes its strength in exports and serves as a gateway, while Guangzhou handles the majority of domestic traffic. We found that the port functional differentiation in the PRD has been largely spontaneous, with minimal proactive policy interventions.]]></description>
      <pubDate>Mon, 17 Nov 2025 09:00:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2606437</guid>
    </item>
    <item>
      <title>Mixed-frequency data-driven forecasting port throughput: a novel attention-DeepAR-MIDAS model</title>
      <link>https://trid.trb.org/View/2576970</link>
      <description><![CDATA[Forecasting cargo throughput is an essential albeit challenging task for national and port optimisation decision-making, resource allocation, and control planning. To this end, a novel forecasting model is developed for mixed-frequency data called attention-DeepAR-MIDAS (ADM) by introducing the mixed data sampling (MIDAS) technique and attention mechanism into the DeepAR forecasting algorithm in this study. The proposed ADM model is specifically designed with an attention mechanism to accurately identify and prioritise the most influential variables, both endogenous and exogenous, over time. Hence, it can effectively use the nonlinear information of mixed-frequency data, which is conducive to port throughput forecasting. Furthermore, the ADM model possesses both long-term and short-term high-precision forecasting capabilities, enabling multi-step probability forecasting and better tracking of abnormal changes in endogenous and exogenous variables of port throughput, fitting their fluctuation trends. By analysing the differences in model performance before and after improvement based on forecast accuracy metrics, probability interval testing, and DM testing methods, the ADM model achieves accurate forecasting. Finally, China's monthly port throughput forecast results also illustrate the superiority of the ADM model, which provides decision-makers with more timely, accurate, and comprehensive forecasts.]]></description>
      <pubDate>Tue, 23 Sep 2025 17:10:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2576970</guid>
    </item>
    <item>
      <title>State and Projection of the Port Traffic in the Port of Split: Post-COVID Era</title>
      <link>https://trid.trb.org/View/2406822</link>
      <description><![CDATA[This paper analyses the total port traffic in the Port of Split comprising both the passenger port basin, nominated as the City port, and cargo terminals situated in the northern part of the city and specified as the North port. The overview of the annual trend of traffic handled by individual port area is elaborated in detail. Considering the main objective of this research, the central part of the paper provides the breakdown of the overall ship throughput concerning the criterion of ship type and size together with the monthly distribution of arrivals for the two most important categories in the port, passenger and cargo ships. The traffic of tourist and other smaller vessels is also taken into account. The passenger and cargo ship traffic data from 2019 represents the basis of the analysis, with an indication that the overall traffic in 2020 is described separately mainly due to the impact of the COVID-19 pandemic on the decline in total port traffic. In addition to the presented statistical analysis, the final part of the paper provides an assessment of the ship traffic recovery in the Port of Split based on the application of linear trend projection. The obtained results confirm that a positive trend of ship traffic growth in the Port of Split may still be expected in years to come, regardless of the temporary decline in traffic caused by the COVID-19 pandemic. It can be expected that a positive growth trend will correlate primary with the passengers and cars traffic, as well as tourist activities within the wider port area.]]></description>
      <pubDate>Thu, 31 Jul 2025 13:58:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2406822</guid>
    </item>
    <item>
      <title>Zero Emissions Locomotives—How One California Port Is Moving the Needle</title>
      <link>https://trid.trb.org/View/2559462</link>
      <description><![CDATA[The Ports of Long Beach (POLB) and Los Angeles (POLA) adopted a Clean Air Action Plan (CAAP) in 2006 to reduce air emissions. Recently, the Harbor Commissions have set new zero emission goals for year 2035 for port drayage trucks, and 2030 for container handling equipment. Statewide, the California Air Resources Board (CARB) and in Southern California, the local air regulatory agency, South Coast Air Quality Management District (SCAQMD), have adopted rules and commenced rulemaking to further restrict air emissions from mobile sources from rail locomotives. Federal agencies such as the US EPA and US DOT have been awarding grants to incentivize development of zero-emissions equipment. Zero emissions (ZE) infrastructure has been installed and is going through testing. Battery-electric-powered marine terminal equipment, transit bus equipment, and hydrogen fuel cells are now becoming a reality. ZE Locomotive technology is not yet as far advanced. Ongoing demonstration locomotive trials have been underway with Class 1 and short lines in the US and Canada. This paper outlines how the Port of Long Beach is planning improvements into the Pier B Railyard to allow for a ZE Locomotive future.]]></description>
      <pubDate>Fri, 27 Jun 2025 11:04:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2559462</guid>
    </item>
    <item>
      <title>Monte-Carlo Simulation Method for Ship Collision Avoidance Performance Considering Various Encounter Situations in Port Congestion Zones</title>
      <link>https://trid.trb.org/View/2549750</link>
      <description><![CDATA[As interest in autonomous maritime technology continues to grow, various collision avoidance algorithms for autonomous vessels have been developed. However, evaluating and comparing the performance of these algorithms presents challenges due to the significant influence of factors such as the number of obstacles, specific encounter scenarios and obstacle arrangements. To address these challenges, the present study employs a Monte Carlo simulation technique to quantitatively evaluate the performance of ship collision avoidance algorithms in port congestion zones. To accurately reflect the conditions of real congested harbor areas with high ship traffic, four major encounter scenarios were defined, with the positions, velocities, and heading angles of obstacles randomly generated within predefined ranges to incorporate randomness into the simulation environment. Using the developed Monte Carlo simulation technique, the performance of the Worst Case Velocity Obstacle (WVO) algorithm and a hybrid algorithm combining WVO with modified Artificial Potential Field algorithm(APF) were qualitatively evaluated. The simulation results revealed the limitations of the WVO algorithm, particularly in scenarios involving crossing and converging encounters, due to frequent heading changes and passive rudder actions. In contrast, the hybrid algorithm, which incorporate WVO algorithm with modified APF method, demonstrated improved collision avoidance performances, including maintaining greater safe distance and reducing collision occurrence through actively using rudder angles.]]></description>
      <pubDate>Mon, 16 Jun 2025 09:17:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2549750</guid>
    </item>
  </channel>
</rss>