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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>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transforming the Marine Transportation System Through Multimodal Freight Analytics: Proceedings of the Fifth Biennial Marine Transportation System Research and Development Conference</title>
      <link>https://trid.trb.org/View/1575346</link>
      <description><![CDATA[In June 2018, the Transportation Research Board (TRB) hosted the conference Transforming the Marine Transportation System through Multimodal Freight Analytics at the National Academy of Sciences Building in Washington, D.C. This meeting was the fifth in a series of Biennial Marine Transportation System Research and Development conferences organized by the TRB and cosponsored by the Committee on the Marine Transportation System (CMTS).  Researchers, practitioners, and academicians gathered to explore innovative science and technology concepts for optimizing system performance through better freight flow forecasting.  This event provided an opportunity to share ideas and needs about multimodal freight analytics and to explore opportunities to harness robust, integrated, high-fidelity multimodal freight transportation data and analytics, offering an interactive format to engage in productive dialogue. The conference brought together those who generate new concepts and address transportation problems and opportunities and those who own and manage transportation systems. The conference considered potential research to address issues associated with transforming MTS. In addition to keynote speakers, the conference included plenary sessions focused on framing the issues related to multimodal freight operations, planning, and policy; presenting the challenges associated with the corresponding analytics; and making a case for its value to tactical and strategic planning. Participants had the opportunity to hear about and discuss issues and areas related to data analytics and decisions support in three concurrent breakout sessions and to interact with individuals providing active demonstrations. Speakers in the closing plenary session highlighted the topics and research ideas discussed during the conference. These proceedings consist of summaries of the introductory, plenary, breakout, and closing sessions as well as overviews of the keynote presentations. Abstracts from the student honor presentations and the active demonstrations are also provided.]]></description>
      <pubDate>Wed, 26 Dec 2018 09:09:10 GMT</pubDate>
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      <title>Workshop on Implementing a Freight Fluidity Performance Measurement System</title>
      <link>https://trid.trb.org/View/1573926</link>
      <description><![CDATA[Performance of the freight transportation system is important to shippers and carriers, planners and policy-makers, as well as the general public because it affects the efficiency and costs of goods and services, and thus the general performance of the economy. Freight performance measures guide decisions about operations, investments, policies, and regulations. During the past decade, interest has grown in measuring freight performance, including multimodal supply chains that move products from production to consumption to disposal. This workshop highlights recent developments in multimodal freight performance measurement, from developments in the United States to advances in North America and Europe. The workshop explored emerging tracking and measurement technologies, including blockchain, and examples of multisector data sharing to capture multimodal freight performance.  This report summarizes the proceedings from the conference, including introductions, panel discussions, and concluding remarks.]]></description>
      <pubDate>Wed, 19 Dec 2018 10:10:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/1573926</guid>
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      <title>Findings on Connector Designation, Data to Support Planning, and Incorporation into State Freight Plans</title>
      <link>https://trid.trb.org/View/1489841</link>
      <description><![CDATA[The purpose of this study is to identify and describe options for improving the use, condition, and performance of freight intermodal connectors through the provision of better data for planning and programming. Freight intermodal connectors are roads that provide local connections between major rail, port, airport, and pipeline terminals and the broader National Highway System (NHS) set of major roads. This study describes issues related to the designation of freight intermodal connectors; examines data needs and options for a long-term data program, including the potential for the development of a stand-alone intermodal connector database; reviews options for improving data quality and amount of data available for planning on intermodal connectors; and develops guidance on how to incorporate freight intermodal connectors into State Freight Plans.]]></description>
      <pubDate>Sat, 02 Dec 2017 17:49:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1489841</guid>
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    <item>
      <title>Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments</title>
      <link>https://trid.trb.org/View/1467189</link>
      <description><![CDATA[This report provides a guidebook for conducting benefit-cost analyses of proposed infrastructure investments on multimodal, multijurisdictional freight corridors for public and private decision makers and other stakeholders at local, state, regional, and national levels in order to arrive at more informed investment decisions.The guidebook is a resource and a reference for multimodal freight investment benefit-cost analysis, data sources, procedures and tools for projects of different geographic scales. To help practitioners get started, the guidebook is presented in a “how to” format relying on discrete steps that are accompanied with realistic and recent examples, a fully worked out case study, checklists of dos and don’ts, and supporting worksheets.]]></description>
      <pubDate>Thu, 18 May 2017 09:38:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1467189</guid>
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    <item>
      <title>Managing Performance and Assets; Freight Data and Visualization</title>
      <link>https://trid.trb.org/View/1455563</link>
      <description><![CDATA[This issue contains ten papers on performance management, asset management, and freight data and visualization.  Specific topics addressed in this issue include the following:  enterprise collaboration technologies; economic impacts from geological hazard events; urban multimodal transportation system performance management; life-cycle assessment tools; infrastructure asset management in developing countries; guardrail system preservation policies; cost estimation of congestion for the trucking industry; truck GPS data in freight modeling and planning; commodity flow modeling; and visualizations of travel time performance.]]></description>
      <pubDate>Fri, 17 Feb 2017 10:42:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1455563</guid>
    </item>
    <item>
      <title>Managing Performance and Assets; Freight Data and Visualization</title>
      <link>https://trid.trb.org/View/1398132</link>
      <description><![CDATA[This issue contains seven papers on performance management, asset management, and freight data and visualization.  Specific topics addressed include:  system performance measures and target-setting requirements of the Moving Ahead for Progress in the 21st Century Act; computing performance measures with the National Performance Management Research Data Set; wall and geotechnical asset management implementation; valuation of road infrastructure; transportation simulation and visualization in emergency evacuation scenarios; classification of freight data elements; and conversion of large streams of truck global positioning system data into truck trips.]]></description>
      <pubDate>Fri, 19 Feb 2016 12:00:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/1398132</guid>
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    <item>
      <title>Air Cargo Facility Planning and Development—Final Report</title>
      <link>https://trid.trb.org/View/1378106</link>
      <description><![CDATA[This report reviews the process and information used in preparing ACRP Report 143: Guidebook for Air Cargo Facility Planning and Development. The guidebook explores tools and techniques for sizing air cargo facilities, including data and updated metrics for forecasting future facility requirements as a function of changing market and economic conditions. This final report describes the study’s progress through on-site collection and evaluation of data and the initial structuring of the content of the Guidebook itself. This includes the team’s research, review, and assessment of a variety of previously prepared academic journal articles, and white papers that had been funded by the private industry, aviation trade organizations and the Federal Aviation Administration (FAA) over the years. The report serves as a summary of the results of ACRP 03-24 research project. This report also provides a glimpse industry trends in terms of its current issues related to air cargo facilities communicated to the research team by industry stakeholders and case study airports who participated in the research project survey and interview efforts. The research efforts led to the development of spreadsheet models for air cargo facility planning and design.]]></description>
      <pubDate>Mon, 04 Jan 2016 13:36:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/1378106</guid>
    </item>
    <item>
      <title>Information Extraction for Freight-Related Natural Language Queries</title>
      <link>https://trid.trb.org/View/1357709</link>
      <description><![CDATA[The ability to retrieve accurate information from databases without an extensive knowledge of the contents and organization of each database is extremely beneficial to the dissemination and utilization of freight data. Advances in the artificial intelligence and information sciences provide an opportunity to develop query capturing algorithms to retrieve relevant keywords from freight-related natural language queries. The challenge is correctly identifying and classifying these keywords. On their own, current natural language processing algorithms are insufficient in performing this task for freight-related queries. High performance machine learning algorithms also require an annotated corpus of named entities which currently does not exist in the freight domain. This paper proposes a hybrid named entity recognition approach which draws on the individual strengths of models to correctly identify entities. The hybrid approach resulted in a greater precision for named entity recognition of freight entities-a key requirement for accurate information retrieval from freight data sources.]]></description>
      <pubDate>Fri, 26 Jun 2015 17:12:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1357709</guid>
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    <item>
      <title>Urban Freight Survey Sampling: Challenges and Strategies</title>
      <link>https://trid.trb.org/View/1338798</link>
      <description><![CDATA[In this paper, the authors analyze data from a large-scale survey, the 2003 Tokyo Metropolitan Freight Survey (TMFS), to examine some of the sampling issues associated with urban freight surveys. The TMFS data indicate that the variables commonly obtained from freight surveys, such as tons shipped and truck trips generated at a facility level, have highly skewed population distributions, making it difficult to obtain accurate estimates when the sample size is modest. Using bootstrap method, the authors compared the performances of stratified sampling against simple random sampling. The analysis indicates that, under the ideal condition, stratified sampling with Neyman allocation can improve the accuracies of the estimates. However, two-phase sampling, which is often used in practice to obtain the information that is necessary to implement the Neyman allocation, tends to produce poor results. The findings presented in this study underscore the importance of sample size in freight surveys and the efforts to capture mega shippers in freight surveys.]]></description>
      <pubDate>Wed, 18 Feb 2015 12:00:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1338798</guid>
    </item>
    <item>
      <title>Analysis of Railway Freight Customer Satisfaction Evaluation Method Based on Business Intelligence</title>
      <link>https://trid.trb.org/View/1326726</link>
      <description><![CDATA[With the development of a customer-oriented business philosophy in the railway freight industry of China, the degree of customer satisfaction has become more and more important as one of the factors that influences the competitiveness for railway freight. In this paper, the features of multiple data sources of railway freight business are analyzed and evaluation parameters are selected. Then, the customer satisfaction evaluation index system is established, and the acquisition method of measure indicators is analyzed. Finally, a case is presented.]]></description>
      <pubDate>Sat, 18 Oct 2014 16:03:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/1326726</guid>
    </item>
    <item>
      <title>Application of Value-Added Service for Railway Freight Information Resources</title>
      <link>https://trid.trb.org/View/1326737</link>
      <description><![CDATA[At present, there are some serious problems in the use of information from the Chinese railway departments, such as:  (1) the low degree of transparency; (2) the precipitate waste of historical data; and, (3) the low utilization rate of resources. First, the pattern of railway freight valued-added services, which is based on the classification of railway freight information, is discussed. Then, the potential consumers of freight information value-added services is discussed. Finally, several value-added measures which the railway can provided are proposed.]]></description>
      <pubDate>Sat, 18 Oct 2014 16:03:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/1326737</guid>
    </item>
    <item>
      <title>Application of Big Data Technology in Marketing Decisions for Railway Freight</title>
      <link>https://trid.trb.org/View/1326736</link>
      <description><![CDATA[Currently, railway freight has basically established a marketing decision support system. Here, the application of big data technology in the marketing of railway freight is discussed. Then, the sources of railway freight marketing data and data collection methods are analyzed. Furthermore, the processing architecture of big data for railway freight marketing is given. Finally, marketing decision-makers of railway freight can use the big data technology to provide the new decision basis.]]></description>
      <pubDate>Sat, 18 Oct 2014 16:03:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1326736</guid>
    </item>
    <item>
      <title>Mode of Data Visualization for Customer-Oriented Railway Freight</title>
      <link>https://trid.trb.org/View/1326723</link>
      <description><![CDATA[With the improvement of railway information systems, there are already calls, e-commerce, Wechat and other service platforms with many features such as dynamic information inquiries, delivery formalities and real-time order tracking. However, the railway system has less research on the basic data and its display platform. Here, the visualization technology will be used to display the data in a new way. First, customers' requirements are analyzed in order to make better use of data. Then, the data visualization technology and platform architecture are analyzed to translate the existing railway freight data into information charts that customers want to see and a variety of information release channels are compared. Finally, not only will transparency and customer experience be enhanced, but customer loyalty will also be improved.]]></description>
      <pubDate>Sat, 18 Oct 2014 16:03:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1326723</guid>
    </item>
    <item>
      <title>Innovations in Freight Demand Modeling and Data Improvement</title>
      <link>https://trid.trb.org/View/1320537</link>
      <description><![CDATA[This report summarizes the events of the Transportation Research Board Second Symposium on Innovations in Freight Demand Modeling and Data, held on October 21-22, 2013 in Herndon, Virginia. The symposium provided key insights into the progress of innovative freight modeling approaches as recommended by the Freight Demand Modeling and Data Improvement Strategic Plan.  Sessions highlighted:  state department of transportation freight modeling; regional/urban tour modeling; international models; private-sector supply-chain decision making; freight data innovations; and business implications.]]></description>
      <pubDate>Mon, 18 Aug 2014 15:29:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/1320537</guid>
    </item>
    <item>
      <title>Adapting Freight Models and Traditional Freight Data Programs for Performance Measurement. Summary of a Workshop</title>
      <link>https://trid.trb.org/View/1275502</link>
      <description><![CDATA[The Transportation Research Board (TRB), in collaboration with the Federal Highway Administration’s Office of Freight Management and Operations, hosted the Adapting Freight Models and Traditional Freight Data Programs for Performance Measurement Workshop to consider the adequacy of freight data and modeling to support performance measurement in public- and private-sector decision making.  The workshop had four objectives: (a) identify the data and models necessary for estimating key performance measures of freight system condition, efficiency, and safety and the economic and environmental impacts that support public and private decision making; (b) consider the adequacy of existing data programs and models, including the Freight Analysis Framework, for meeting performance measurement needs; (c) define critical gaps in data programs and modeling tools and identify essential actions needed to close them; and (d) explore a focused research framework, with supporting research needs statements, that could lead to improvements in data and models for estimating freight transportation performance measures. To accomplish these objectives, the workshop included general sessions, breakout sessions, and an electronic poster session. Speakers in the general sessions provided public- and private-sector perspectives on freight performance measures, data needs, and opportunities and challenges. The freight-related elements of Moving Ahead for Progress in the 21st Century Act (MAP-21) were also highlighted. The breakout sessions focused on defining needs and opportunities to adapt freight data and models to support performance measurement and identifying research needs.  This document presents the proceedings of the workshop. The major topics addressed in the general sessions and the breakout sessions are presented in these proceedings. A list of attendees is provided at the end of this document. The abstracts prepared by the authors of the electronic posters are provided in the appendix.]]></description>
      <pubDate>Fri, 15 Nov 2013 15:26:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1275502</guid>
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