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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Resilience and efficiency of global container ports: A DEA–Malmquist analysis based on physical infrastructure and strategic typologies</title>
      <link>https://trid.trb.org/View/2658012</link>
      <description><![CDATA[Container port efficiency is vital for sustaining global trade, especially amid disruptions such as the COVID-19 pandemic, which exposed systemic weaknesses such as port congestion and schedule delays. However, limited research has systematically evaluated port performance dynamics across systemic shocks, especially from a resilience and investment-alignment perspective. In this study, a Malmquist data envelopment analysis (DEA) framework is applied to examine the efficiency and productivity trends of major container ports from 2018 to 2022. The proposed model addresses cross-port differences and data constraints by focusing on key physical infrastructure inputs—gantry cranes, port area, and quay length—and container throughput as output. The results show that ports such as Singapore and Shanghai consistently achieve high efficiency, whereas other ports lag behind. Productivity gains mainly reflect technological change (TC), not technical efficiency change (TEC), exposing a gap with the scale efficiency change (SEC) needed to realize investments. A strategic matrix classifies ports by overall performance and progress, identifying resilient and advancing ports such as Ningbo-Zhoushan and Qingdao. These insights help policymakers and port managers align investment with long-term resilience goals and respond more effectively to future disruptions.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658012</guid>
    </item>
    <item>
      <title>A Comparative Analysis of Crowdsourced and Kernel Density Approaches for Improved Accidents Blackspots Prediction Accuracy</title>
      <link>https://trid.trb.org/View/2642304</link>
      <description><![CDATA[The accurate identification of accident blackspots is indeed critical for implementing effective road safety measures. Blackspots, being areas with a higher incidence of accidents, demanding focused attention to mitigate risks and enhance overall road safety. This study investigates methods to improve the accuracy of predicting accident blackspot locations in a case study on the roads of Sistan Baluchistan province in Iran. A comprehensive dataset spanning five years of meticulously recorded accident records was collected in collaboration with on-duty traffic police officers. The research employs binary logit models to identify significant variables contributing to blackspot prediction accuracy. Noteworthy factors encompass driver attributes (such as age, gender), road features, environmental elements, weekday/weekend status, road type and traffic volume. Comparative analyses of individual implementations of Kernel density and Crowdsourcing methods revealed prediction accuracies of 62.3% and 65.3%, respectively. However, when these methods were jointly applied to extract common blackspots, the prediction accuracy significantly increased to 70.02%. This combined approach showcased the synergistic potential of utilizing diverse methodologies, emphasizing the necessity of integrating multiple data sources for precise accident blackspot identification. The findings underscore the effectiveness of amalgamating Kernel density and Crowdsourcing techniques, offering a promising avenue for enhancing predictive models and implementing proactive road safety measures within the diverse road networks. The combined method pinpoints high-risk locations validated by both crash data and driver behavior, giving road authorities a reliable tool to prioritize safety interventions with higher confidence.]]></description>
      <pubDate>Thu, 19 Feb 2026 09:44:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642304</guid>
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    <item>
      <title>A Model Typology Approach for Improving Spatial Transferability of Freight Demand Estimates: Case Study of Geographically Dissimilar Regions in India</title>
      <link>https://trid.trb.org/View/2571574</link>
      <description><![CDATA[Spatial transferability of freight demand models is a practice that is needed to enable the use of formerly developed models in estimating the freight demand of another region. This practice is particularly crucial for planning agencies in densely populated countries like India, needing more resources for comprehensive freight data collection. There are studies on the transferability of freight demand models. However, the transferability of non-parametric freight demand models has yet to be investigated. It is necessary to understand whether the extent of transferability of non-parametric models is greater than that of parametric models so that planning agencies can adopt more reliable modelling approaches/typologies. This paper investigates the spatial transferability of freight production models using parametric (ordinary least squares regression and robust regression) and non-parametric (multiple classification analysis and support vector regression) modelling approaches. The transferability assessment results show that the non-parametric models are more transferable than non-parametric models.]]></description>
      <pubDate>Tue, 02 Sep 2025 08:50:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2571574</guid>
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    <item>
      <title>Analyses of the container throughput: case study on the selected ports of Europe and China</title>
      <link>https://trid.trb.org/View/2528624</link>
      <description><![CDATA[This paper examines container throughput and port efficiency in selected ports in Europe and China using Data Envelopment Analysis (DEA) and provides information on the competitiveness and performance of the ports studied. The selection of regions is based on the fact that the recorded bilateral trade flows, most of which are handled by sea, have increased significantly in recent years. The DEA analysis shows that ports such as Shanghai, Qingdao, Antwerp and Ningbo-Zhoushan have different technical efficiency indices, which indicates potential for improvement in the rationalization of processes and the allocation of resources. In contrast, the ports of Rotterdam and Piraeus show optimal efficiency, indicating effective utilization of resources. This paper emphasizes proactive management, operational adjustments, and investment in port infrastructure to improve port resilience and performance. While the paper provides insightful conclusions, it also recognizes limitations and the need for further research on qualitative aspects that influence port efficiency.]]></description>
      <pubDate>Thu, 29 May 2025 09:21:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2528624</guid>
    </item>
    <item>
      <title>Factors Affecting the Injury Severity of Head-On Crashes on Undivided Rural Roads under Different Weather Conditions</title>
      <link>https://trid.trb.org/View/2521812</link>
      <description><![CDATA[Head-on collisions are among the most severe types of crashes, consistently resulting in more severe injuries than other types of collisions. One of the most important factors affecting these crashes is weather conditions. In this study, for the first time, the effect of different weather conditions on the severity of head-on crashes on undivided rural roads was investigated using a parametric and nonparametric algorithm approach. With a parametric and non-parametric algorithm approach, this study aimed to analyze head-on crashes on undivided roads and the factors influencing their severity under different weather conditions. Recorded data on head-on crashes in the study area over a 5-year period were categorized into two groups based on weather conditions: clear (sunny) and adverse (cloudy, rainy, snowy and foggy). By identifying the factors affecting crash severity using the Classification and Regression Trees (CART) algorithm, the logistic regression algorithm was employed to determine the significance and impact of each variable. The results revealed that summer affects both clear and adverse weather conditions, increasing the crash severity by 11% and 27%, respectively. Motorcycle-to-motorcycle collisions were significant in both clear and adverse weather conditions, with over 90% resulting in injuries or fatalities. The familiarity of at-fault drivers, wet surface and early morning significantly affected the severity of head-on collisions in adverse weather. Specifically, night-dark increased the crash severity by 30% in clear weather. At-fault young drivers and heavy vehicle-to-motorcycle collision increased the severity, while road geometry and afternoon reduced the severity of head-on collisions in clear weather conditions. The findings guide weather-specific safety strategies, like improving visibility and addressing motorcyclist and young driver risks, to reduce head-on collision severity.]]></description>
      <pubDate>Wed, 16 Apr 2025 11:24:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2521812</guid>
    </item>
    <item>
      <title>Analysis of Sustainable Efficiency of Freight Transport in Major European Economies: An Integrated Multi-Region Input-Output and Dea Approach</title>
      <link>https://trid.trb.org/View/2479820</link>
      <description><![CDATA[This paper integrates the multi-region input-output model (MRIO) and data envelopment analysis (DEA) methods to analyze the freight transport efficiency in Europe. Social, economic, and environmental influences were combined into a sustainable efficiency rating of the freight transport sector of Germany, France, Italy, Spain, and the Netherlands. First, the freight transport sector's carbon footprint (CFP) was quantified using the MRIO model. The lifecycle-based CFP emissions of freight transport activities were assessed using a dataset from 2000 to 2018. Nineteen stochastic model-based MRIO lifecycle assessments were built for each country. Secondly, sixty instances of DEA models were created using a linear program for each mode in the selected countries. Thirdly, the sustainable efficiency scores were determined for each freight transport mode in each country over four periods: 2000–2004, 2005–2009, 2010–2014, and 2015–2018. The results illustrate that the sustainable efficiency score of inland, water, and air transport modes ranged from 0.38 to 1.]]></description>
      <pubDate>Thu, 23 Jan 2025 09:31:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2479820</guid>
    </item>
    <item>
      <title>Unraveling stochastic fundamental diagrams with empirical knowledge: Modeling, limitations, and future directions</title>
      <link>https://trid.trb.org/View/2440405</link>
      <description><![CDATA[Traffic flow modeling relies heavily on fundamental diagrams. However, deterministic fundamental diagrams, such as single or multi-regime models, cannot capture the underlying uncertainty in traffic flow. To address this limitation, this study proposes a non-parametric Gaussian process model to formulate the stochastic fundamental diagram. Unlike parametric models, the non-parametric approach is insensitive to parameters, flexible, and widely applicable. The computational complexity and high memory requirements of Gaussian process regression are also mitigated by introducing sparse Gaussian process regression. This study also examines the impact of incorporating empirical knowledge into the prior of the stochastic fundamental diagram model and assesses whether such knowledge can enhance the model’s robustness and accuracy. By using several well-known single-regime fundamental diagram models as priors and testing the model’s performance with different sampling methods on real-world data, this study finds that empirical knowledge benefits the model only when small inducing samples are used with a relatively clean and large dataset. In other cases, a purely data-driven approach is sufficient to estimate and describe the density–speed relationship pattern.]]></description>
      <pubDate>Thu, 24 Oct 2024 15:04:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2440405</guid>
    </item>
    <item>
      <title>Non-parametric and parametric damage indices through a case-study of a reinforced concrete bridge pier</title>
      <link>https://trid.trb.org/View/2427621</link>
      <description><![CDATA[Parametric indices are empirically related to two or more response parameters with a combination coefficient and do not conform to a physical definition of damage. The combination parameter is expected to be contingent on the loading and the state of calibration other than failure. Damage is also defined as the ‘deterioration of a physical quantity’ and the resulting non-parametric index does not involve any empirical constant. However, the non-parametric indices saturate much before unity. This paper first aims to assess the performance of some of the existing non-parametric indices. Experimental response until failure of a circular RC bridge pier under cyclic loading is numerically simulated for this purpose. A new physical-definition based non-parametric damage index is proposed. Setting this alternate definition as the benchmark, performance of parametric Park-Ang index, some of its variants and other non-parametric indices are studied at levels other than failure through a damage progression analysis using cyclic and seismic excitations. A parametric index and its simplified form consistent with that physical-definition are next proposed with weighted-hysteretic-energy and normalized-deformation as parameters. The same calibrated model is used in subsequent assessment. Associated combination-coefficient exhibits a stable relationship with peak drift and a loading-independent functional form is proposed.]]></description>
      <pubDate>Mon, 07 Oct 2024 08:37:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2427621</guid>
    </item>
    <item>
      <title>Connectivity and competitiveness of the major Mediterranean container ports using ‘Benefit-of-the-Doubt’ and ‘Common Sets of Weights’ methods in Data Envelopment Analysis</title>
      <link>https://trid.trb.org/View/2382035</link>
      <description><![CDATA[Port connectivity has become a key factor for the competitiveness of countries, ports and importing and exporting companies. In this regard, industries integrated into global value chains are dependent of shipping services and, consequently, the level of port connectivity determines their access to international markets in a reliable and flexible way. Given the growing importance of this issue, this paper aims to study foreland port connectivity by constructing a composite port connectivity indicator applied to the major Mediterranean container ports. In the construction of composite indicators, the weight assigned to each variable is a critical aspect as it affects the objectivity of the score provided. In methodological terms, it can be extremely complex to find the optimal set of weights. For this reason, the present research uses the novel approach of Benefit-of-the-Doubt-type Data Envelopment Analysis (DEA), and the Common Set of Weights method in DEA, to generate an accurate weighting scheme. The paper is the first to study the connectivity of major Mediterranean container ports: An area characterised by fierce competition between a large number of hub, gateway and mixed ports, where connectivity is a key factor of their competitiveness.]]></description>
      <pubDate>Fri, 09 Aug 2024 15:31:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2382035</guid>
    </item>
    <item>
      <title>Using mechanistic-empirical simulations and nonparametric testing to explore variability in the expected performance of reference asphalt pavement designs</title>
      <link>https://trid.trb.org/View/2375762</link>
      <description><![CDATA[This study explored the variability in expected performance of eight reference asphalt pavement designs using AASHTOWare pavement ME software. Nonparametric tests showed that structures with a high-modulus asphalt base on an unbound base significantly delayed maintenance. Varying pavement layer materials significantly affected the simulations, except the asphalt surface and asphalt base (when used on an unbound base). Moreover, recycling rates in AC asphalt bases over 60% significantly improved performance over no recycling; however, air void content and effective binder percentage seemed to be key in these findings. Finally, this study showed that meeting material specifications does not guarantee equal performance.]]></description>
      <pubDate>Wed, 29 May 2024 09:29:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2375762</guid>
    </item>
    <item>
      <title>Model Predictive Current Control for PMSM Drives Based on Nonparametric Prediction Model</title>
      <link>https://trid.trb.org/View/2364810</link>
      <description><![CDATA[To essentially solve that the control performance of model predictive current control (MPCC) is affected by the accuracy of model parameters, an MPCC of permanent magnet synchronous motors (PMSMs) based on the nonparametric prediction model (NPM-MPCC) is proposed. First, the control principle of MPCC method is introduced, and the influence of model parameter errors on the control performance under the conventional prediction model is analyzed. Then, an NPM for PMSM prediction control is proposed, which consists of d-axis current prediction model and q-axis current prediction model. The proposed model does not include any motor parameters and has a real-time model updating mechanism. The accurate current prediction can be achieved, only by using current prediction difference, sampling, and storing information, and the control performance of the system can get rid of the dependence on the precision of model motor parameters. Finally, the effectiveness of the MPCC method based on NPM is verified by the experimental results.]]></description>
      <pubDate>Mon, 20 May 2024 09:17:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2364810</guid>
    </item>
    <item>
      <title>Empirical Study on Performance Assessment Of Listed Logistics Companies In China With DEA</title>
      <link>https://trid.trb.org/View/2282110</link>
      <description><![CDATA[This paper applies Data Envelopment Analysis (DEA) to study the performance assessment of seventeen China listed logistics companies from 2003 to 2006. It proves that their aggregate efficiency is low, and that the differences among them are significant. From the group perspective, the aggregate efficiency of the transportation group and the port group are almost the same, where as the number of transportation companies with DEA efficiency is more than that of the number of port organizations. From a purely technical efficiency perspective, it is relatively stable with the average value is 0.9165. From a scale efficiency perspective, it is worse with the average value of 0.8859. It concludes that poor scale performance is the dominant reason for poor performance of the China logistics companies.]]></description>
      <pubDate>Fri, 10 May 2024 16:51:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2282110</guid>
    </item>
    <item>
      <title>Operating Efficiency Analysis of Listed Companies of China's Airlines Industry Based On the DEA Model</title>
      <link>https://trid.trb.org/View/2282109</link>
      <description><![CDATA[This paper makes a simple improvement to the data envelopment analysis (DEA) model, and analyzes the operating efficiency of China's airlines industry listed companies using the DEA model. The authors selected the main business costs, total assets and numbers of employees as input indicators, and selected earnings per share and main business income as output indicators. The results show that Air China and China Southern Airlines are DEA effective, having the best technical efficiency and the economies of scale unchanged. The way to improve efficiency is to strengthen the cost management under its current scale. China Eastern Airlines, Hainan Airlines and Shanghai Airlines are not DEA effective, having weak technical efficiency and the economies of scale increased. The ways to improve efficiency are to increase the economies of scale and technological input.]]></description>
      <pubDate>Fri, 10 May 2024 16:51:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2282109</guid>
    </item>
    <item>
      <title>A review of stochastic finite element and nonparametric modelling for ship propulsion shaft dynamic alignment</title>
      <link>https://trid.trb.org/View/2239230</link>
      <description><![CDATA[Ship propulsion shafting is inevitably subject to various uncertainties during navigation. Uncertain numerical models can reflect the dynamic behaviour of the shafting more accurately, enabling the dynamic alignment. This review investigates the progress of research on two type of uncertainty modelling methods, stochastic finite element and nonparametric modelling, in the dynamic alignment of shafting. First, the development of the alignment of ship propulsion shaft systems is outlined, and the calculation methods are summarised according to different alignment principles in two directions: static and dynamic. Second, the uncertainties affecting the ship propulsion shafting are distinguished, and the corresponding modelling methods are applied. i.e., stochastic finite element methods for data uncertainty and nonparametric modelling methods for nonparametric uncertainty. Both the methods are discussed detailedly, including the basic principles, constraints, advantages, and limitations. Then, propulsion shafting dynamic characteristics, such as bearing loads, bending moments, and bending angles, are described under various uncertainties. Additionally, the root mean square value of vibration at the bearing seat and the spectral and natural characteristics will be analysed to determine the uncertainty of the shafting. Finally, the development of both methods for the alignment of ship propulsion shafting is described, as well as the future research directions.]]></description>
      <pubDate>Mon, 16 Oct 2023 17:24:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2239230</guid>
    </item>
    <item>
      <title>Statistical Models of Interactions between Vehicles during Overtaking Maneuvers</title>
      <link>https://trid.trb.org/View/2212378</link>
      <description><![CDATA[A practical challenge facing the adoption of self-driving vehicles is the complex influence of the lateral dimension in vehicle traffic. This phenomenon has received little attention in the literature and few quantitative descriptions of interactions between vehicles are available for model validation. This paper proposes an analysis of the kinematic variables describing vehicle interactions on both axes during overtaking maneuvers using linear as well as nonlinear and nonparametric models based on real-world highway data. The principal findings are as follows: (a) a mutual influence between pairs of vehicles, especially at small lateral separation distances; (b) the higher the longitudinal velocity, the greater the lateral distances, no doubt to avoid collisions; and (c) lateral accelerations that tend to narrow lateral distance are associated with longitudinal accelerations that tend to widen it. These results are consistent across the different models applied and also with previous studies.]]></description>
      <pubDate>Mon, 17 Jul 2023 14:42:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2212378</guid>
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