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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>
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      <title>Transport Research International Documentation (TRID)</title>
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    <item>
      <title>Novel Estimation Method and Interpretation of the Peak Hour Factor at Intersections</title>
      <link>https://trid.trb.org/View/2720609</link>
      <description><![CDATA[This study presents a statistically grounded method for estimating the peak hour factor (PHF) at intersections, using classical optimization techniques. Unlike the traditional approach, which computes a single ratio from aggregated turning movement volumes, the proposed method explicitly accounts for the count variability across individual turning movements and over multiple days. It produces not only a point estimate but also a confidence interval, offering a more defensible basis for analysis. The method implementation is quite straightforward: the optimization method revealed that PHF is actually the slope of the zero-intercept regression line between the peak interval flow rate and peak hourly volumes, in addition to generating its upper and lower 95th percentile estimates. This finding enables a simple spreadsheet application of the estimation method. Regardless of the data aggregation intervals studied in this paper (5, 10, and 15 min), the traditionally estimated PHF fell outside of the proposed method’s 95% confidence interval in many cases, indicating a statistically significant difference between the outcomes of the two methods. This could result in under- or over-estimation of the design demand volumes in some cases.]]></description>
      <pubDate>Sat, 04 Jul 2026 16:35:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720609</guid>
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    <item>
      <title>Oregon Traffic Safety Research Roadmap</title>
      <link>https://trid.trb.org/View/2719346</link>
      <description><![CDATA[To address the rising increase in fatal and serious traffic injuries, the ODOT Traffic Safety Research Roadmap establishes a structured, five-year research agenda listing research concepts for funding through ODOT Research Unit’s annual funding cycle as well as other funding opportunities. The study identifies 51 priority traffic safety research needs, spanning the Safe Systems topics of safe people, safe vehicles, safe speeds, safe roads, and post-crash care. An implementation playbook suggests pathways of achieving the desired research needs to support transportation safety practice.]]></description>
      <pubDate>Thu, 02 Jul 2026 16:04:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2719346</guid>
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    <item>
      <title>Integrated Design Flow Methodology for Open-Source Innovations in Smart Transportation: Empowering Accountable AI and Cybersecurity</title>
      <link>https://trid.trb.org/View/2671795</link>
      <description><![CDATA[Spearheading the adoption of trustworthy AI and cyber security across the triad of automotive, transportation, and logistics embark on rigorous evaluations of applications rooted in open hardware/software ecosystems. Open innovations at chip, embedded and/or system level foster research on security-, safety-, privacy-, and accountability-by-design. Cyber-physical system of systems amplifies the fortress of AI-powered solutions and cyber-physical security, with particular emphasis on open-source frameworks. This paper presents an integrated design flow methodology that incorporates chip, embedded and system-level design and development. The proposed methodology is aligned with the recent trends and state-of-the-art dealing with open-source hardware and software development.]]></description>
      <pubDate>Tue, 30 Jun 2026 16:05:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671795</guid>
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    <item>
      <title>Developing EU-CEM: A Common Evaluation Methodology for Evaluating Co-operative, Connected and Automated Mobility</title>
      <link>https://trid.trb.org/View/2671790</link>
      <description><![CDATA[Co-operative, Connected and Automated Mobility (CCAM) is of increasing interest to the transport community across the world, though is still maturing. The Horizon Europe project FAME is developing a European framework for testing CCAM on public roads. As part of this, a common evaluation methodology (EU-CEM) is being developed, which provides guidance on how to set up and carry out an evaluation or assessment of direct and indirect impacts of CCAM solutions on different user groups and wider society. Objectives include ensuring that evaluations can be complementary planned with results that are easy to compare, as well as establishing a common vocabulary to support projects in the CCAM community. This paper sets out how the EU-CEM is being developed and embedded into CCAM research in Europe, with a particular emphasis on how the project has adopted an agile and iterative approach to the CEM development alongside meaningful and sustained engagement with stakeholders.]]></description>
      <pubDate>Tue, 30 Jun 2026 16:05:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671790</guid>
    </item>
    <item>
      <title>A Methodology for Planning and Executing Mobility Data Labs: Fostering Collaboration, Data Sharing, and Innovation</title>
      <link>https://trid.trb.org/View/2670977</link>
      <description><![CDATA[Data plays a pivotal role in modern mobility research, and data labs have emerged as powerful platforms for promoting collaboration, innovation, and data sharing in the mobility sector. This paper presents a comprehensive methodology designed to plan and execute data labs in the mobility sector, along with its successful implementation within the EU-funded MobiDataLab project context. Central to the methodology is the identification of critical stakeholders, the precise delineation of objectives and challenges, ensuring alignment with genuine mobility issues. It staunchly adheres to a user-centric approach, actively engaging end-users, entrepreneurs, developers, researchers, start-ups, and SMEs with data expertise through a systematic, replicable strategy. Additionally, this paper seeks to introduce the technical infrastructure that was designed and deployed to facilitate these endeavors. The methodology emphasizes the establishment of robust data management systems, protocols, and privacy safeguards. Simultaneously, the methodology advocates for the promotion of interoperability standards and open data formats to facilitate seamless access to diverse data sources. Advanced open data catalogues and data enrichment processors, with anonymization features, further enhance data collaboration and privacy. Capacity-building initiatives enhance stakeholder skills, supported by an Open Knowledge Base for sharing best practices. The methodology's efficacy is finally illustrated through case studies which underscore the concrete benefits of data labs in advancing formal innovation and collaboration within the mobility sector.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670977</guid>
    </item>
    <item>
      <title>nuMIDAS: The New Mobility Data and Solutions Toolkit</title>
      <link>https://trid.trb.org/View/2670976</link>
      <description><![CDATA[The mobility ecosystem is rapidly evolving, with the rise of new stakeholders and services, accompanied by new ways for the generation, collection, and storing of data. In the nuMIDAS (New Mobility Data and Solutions Toolkit) project, we provided insights into what methodological tools, databases, and models are required, and how existing ones need to be adapted with new data. We started from insights obtained through (market) research and stake-holders, as well as quantitative modelling. A wider applicability of the project’s results across the whole EU was guaranteed as all the research was validated within a selection of case studies in pilot cities, with varying characteristics, thereby giving more credibility to these results. Finally, through an iterative approach, nuMIDAS created a tangible and readily available toolkit that can be deployed elsewhere, including a set of transferability guidelines, thus thereby contributing to the further adoption and exploitation of the project’s results.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670976</guid>
    </item>
    <item>
      <title>Development of Dashboards and Procedures for Using Connected Vehicle Data to Prioritize Investments in Electric Vehicle Related Infrastructure</title>
      <link>https://trid.trb.org/View/2719343</link>
      <description><![CDATA[The National Electric Vehicle Infrastructure (NEVI) Formula Program and the Charging and Fueling Infrastructure Discretionary Grant Program together provide $7.5 billion to support states with building out a nationwide electric vehicle (EV) charging network. Indiana’s Charging the Crossroads program, funded through the NEVI program, plans to invest almost $100 million to build an EV charging network along Indiana interstates and highways. There is broad consensus among states, that these fast charging station investments should be based upon quantitative geospatial data with the objective of maximizing the impact of the NEVI program investments. However, traditional methods for monitoring EV usage have relied on time and cost intensive techniques that do not scale well. Travel diaries, surveys, camera detection and count stations are just some of the methods utilized in the past to monitor traffic volumes. Connected vehicle data with enhanced attributes have the potential to inform stakeholders of electric vehicle use at scale and year-round without additional fixed infrastructure or sensor investments. The motivation of this study was to explore the viability of CV data to provide data-driven insights to practitioners in helping prioritize the rollout of EV charging infrastructure. The study utilized connected vehicle data to develop methodologies and reporting procedures that document usage of transportation and charging infrastructure by EVs. Additionally, the study utilized publicly available data on public fast charging station locations to determine fast charging deserts along Alternative Fuel Corridors (AFCs).]]></description>
      <pubDate>Tue, 30 Jun 2026 08:51:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2719343</guid>
    </item>
    <item>
      <title>Transportation Public Finance Statistics (TPFS) Technical Documentation</title>
      <link>https://trid.trb.org/View/2717179</link>
      <description><![CDATA[The Bureau of Transportation Statistics (BTS) produces the Transportation Public Finance Statistics (TPFS) data series, which summarizes annual public-sector cash flows related to transportation [BTS 2026b]. TPFS data comprise transportation revenues and expenditures, including federal transfers to state and local governments. Data are presented by transportation mode, level of government, and revenue or expenditure type. BTS provides nationally aggregated tabulations of the TPFS data, referred to as the “Aggregate State TPFS.” For the Highways, Transit, and Air modes, BTS also provides state-level tabulations of the TPFS data, referred to as the “State-Level TPFS,” for the state and local level of government. This document provides detailed information about how the TPFS is developed including the content of the data tabulation tools, data visualizations, estimation methodology, and inflation approach.]]></description>
      <pubDate>Mon, 29 Jun 2026 09:11:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717179</guid>
    </item>
    <item>
      <title>Research on the Statistical Method of Real Driving Emission Data of
                    Commercial Vehicle under Low Load</title>
      <link>https://trid.trb.org/View/2706252</link>
      <description><![CDATA[Current emission regulation in China (National VI b) adopts the work-based window                     (WBW) method to statistically analyze PEMS experimental data. This method cannot                     fully account for experimental data under low load and cold start conditions. In                     light of this, this paper proposes a statistical method for low-load condition                     experimental data. Firstly, the adaptability of the WBW method to low-load                     condition experimental data is analyzed. Secondly, the representativeness and                     authenticity of statistical results from different methods are compared. The                     results indicate that when the power threshold of the WBW method is set at 20%,                     the effective window qualification rate in six experiments is less than 40%. And                     as the load decreases, the power threshold required to meet regulatory                     requirements needs to be further reduced, meaning more low-power data points are                     discarded. The WBW method eliminates many low output power data points with high                     CO and NOx emissions from test data on an urban road section with low                     driving speed, significantly underestimating the CO and NOx emission                     data under low load conditions, with NOx emissions 56.8% lower than                     the cumulative averaging (CA) method results. It is recommended to use the CA                     method for calculating CO and NOx emissions under low load                     conditions.]]></description>
      <pubDate>Mon, 29 Jun 2026 09:11:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706252</guid>
    </item>
    <item>
      <title>A Sectoral Strategic Roadmapping Framework for Combining Regulatory and Industry Perspectives: The Case of Advanced Air Mobility in Canada</title>
      <link>https://trid.trb.org/View/2714344</link>
      <description><![CDATA[This paper presents a sectoral roadmap development framework-testing process for the Canadian Advanced Air Mobility (AAM) industry, to evaluate a methodology for expanding technological roadmaps into comprehensive sectoral frameworks. The procedural framework incorporates the regulatory perspective to the technological, infrastructural, social, and economic ones, using the S-PLAN framework to identify important strategies and practical actions. Insights were gathered from interviews with cross-disciplinary experts in the public (regulatory) and private (industry) sectors across the industry using the Delphi method to consolidate strategic topics and crucial tactical insights for the sector evolution. The research aims at proposing a methodology for broadening the scope of existing technological roadmaps, applying it in the case of Canada. This methodology is then illustrated in its application to establish the foundation for iterative advancements in the AAM sector, emphasizing a collaborative approach to address the identified challenges. The concluding strategic topics, classified by Advanced Air Mobility Maturity Levels, serve as foundations for the ongoing transformation of Canada’s aviation landscape from its current state towards a more autonomous and expansive future. While this study focuses on the AAM sector, the framework’s design offers broader applicability, providing a valuable tool for other emerging, complex, and rigidly regulated industries.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714344</guid>
    </item>
    <item>
      <title>Assessment of Temperature Correction Factors for Falling Weight Deflectometer Deflections</title>
      <link>https://trid.trb.org/View/2712639</link>
      <description><![CDATA[This study presents the development of an improved temperature correction methodology for falling weight deflectometer (FWD) deflections in full-depth asphalt pavements. The objective was to address the limitations of existing correction methods by integrating viscoelastic pavement behavior, structural properties, and realistic thermal gradients. Field temperature data from instrumented sites in Indiana were used to train a machine learning model capable of predicting pavement temperature profiles in flexible pavements. These predictions informed a series of finite element simulations that captured pavement responses to FWD loading under a range of thermal and structural conditions. Temperature correction factors were then derived and modeled using a unified sigmoidal function, whose parameters depend solely on asphalt thickness, subgrade stiffness, and effective pavement temperature. For full-depth asphalt pavements, the temperatures at the surface–base interface and quarter-depth were found to be the most accurate representations of the effective pavement temperature for use in the proposed deflection correction methodology. Field validation demonstrated that the proposed methodology consistently outperformed the traditional American Association of State Highway and Transportation Officials (AASHTO) 1993 AASHTO Guide for Design of Pavement Structures correction approach, offering a more accurate and practical solution for temperature correction in pavement structural evaluation.]]></description>
      <pubDate>Tue, 16 Jun 2026 07:28:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712639</guid>
    </item>
    <item>
      <title>Investigating Travel Survey Representativeness</title>
      <link>https://trid.trb.org/View/2712628</link>
      <description><![CDATA[Household travel surveys are a critical data source for transportation planning and forecasting, offering insights into traveler behavior such as trip purpose, mode choice, travel time, and temporal patterns. However, declining response rates, increasing response biases, and measurement errors pose growing challenges to survey data quality. This project develops and applies a methodological framework to evaluate the representativeness and behavioral bias of household travel surveys. Using 2021– 2022 data from the Minneapolis–St. Paul metropolitan region, we examine how oversampling, the inclusion of convenience samples, and calibration weighting affect the bias and precision of travel behavior estimates. The framework builds upon a review of recruitment practices, sampling methods, and survey evaluation techniques, including findings from multiple metropolitan regions and recent literature. The resulting approach offers an accessible, theoretically grounded, and practically relevant tool for assessing survey design and improving data quality]]></description>
      <pubDate>Mon, 15 Jun 2026 08:40:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712628</guid>
    </item>
    <item>
      <title>National Transportation Noise Map Documentation: Version 3</title>
      <link>https://trid.trb.org/View/2709440</link>
      <description><![CDATA[By most forecasts, the U.S. population is projected to grow by over 100 million by 2050. As demand for transportation increases and our methods of transportation change and evolve, so too will transportation-related noise. The Bureau of Transportation Statistics (BTS) has started a national, multi- modal transportation noise mapping initiative to facilitate the tracking of trends in transportation- related noise over time. This document describes the methodology and assumptions included in the National Transportation Noise Map (NTNM) which consists of noise inventory layers for aviation, roadway, passenger and freight rail transportation sources. Future versions are envisioned to include additional transportation noise sources as transportation modes and trends evolve and data sources mature.]]></description>
      <pubDate>Thu, 11 Jun 2026 13:20:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2709440</guid>
    </item>
    <item>
      <title>Post-World War II Institutional Buildings: Expediting Section 106 Review through a Better Understanding of Practices at a National Level</title>
      <link>https://trid.trb.org/View/2712187</link>
      <description><![CDATA[In the postwar era, many Americans moved from cities to newly developed suburbs. This extensive postwar construction is or is approaching fifty years old and must be considered for eligibility for listing on the National Register of Historic Places (NRHP). Institutional buildings, the community-focused resources tied to the spread of residential development, are found in large numbers across the country. These include schools, hospitals, city halls, courthouses, fire and police stations, libraries, churches, veteran’s and fraternal organization buildings, National Guard armories, post offices, airports, and parks.

Section 106 of the National Historic Preservation Act requires that federal agencies and recipients of federal funds consider the effects of construction projects on properties that are eligible for listing on the NRHP. The volume of postwar property evaluations can be overwhelming for state departments of transportation (DOTs), FHWA division offices, and state and tribal historical preservation officers. In addition, evaluations of these properties are highly diverse in physical form and materials, reflecting a wide range of historic trends and architectural contexts, and have not been extensively studied or documented. As a result, evaluations may use inconsistent approaches and require significant time and staff resources.

The objective of the research is to develop a constituent evaluation methodology to determine NRHP eligibility of postwar institutional buildings, which would be replicable throughout the United States at different levels of government. The research should provide a definition of common institutional property types and a tool for evaluating ubiquitous, vernacular versions of institutional resources that pose the greatest challenge to practitioners and consulting parties.]]></description>
      <pubDate>Tue, 09 Jun 2026 16:14:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712187</guid>
    </item>
    <item>
      <title>Computationally Informed Methodologies for Capturing the Effect of Intervening Structures During Truck Impact Events: Phase II</title>
      <link>https://trid.trb.org/View/2709180</link>
      <description><![CDATA[Reinforced concrete (RC) barriers are often used as railings to protect bridge piers against vehicular collision force (VCF). RC barriers absorb collision energy and/or redirect vehicles. According to bridge design specifications of the American Association of State Highway and Transportation Officials (AASHTO), barriers used to protect bridge piers should have a minimum height of 42 in. and survive MASH Test Level 5 (TL-5). Although many barriers in current use do not meet this requirement, these substandard barriers can reduce the severity of vehicle-pier collisions and decrease the AASHTO-specified VCF for pier resistance in upgraded bridges. The primary objective of this research was to assess the performance of sub-standard RC barriers as protection for bridge piers against VCF and quantify their reduction of the equivalent static force (ESF) that piers must resist according to AASHTO specifications. This report describes current procedures to determine the transverse static capacity of RC barriers and proposes alternative, accurate methodologies. A matrix of crash scenarios is simulated in dynamic explicit analysis using the finite element software LS-DYNA to comprehensively encapsulate the behavior of sub-standard RC barriers. The investigated parameters include energy dissipation, velocity reduction, contact force absorption, and lateral displacement. This research also utilized a simulation matrix on a bridge pier that failed to withstand the ESF under the required AASHTO’s extreme load event behind a sub-standard barrier. A series of dynamic impact force time histories was used to extract the ESF and compare the resulting ESF to the AASHTO-required force, leading to a proposed reduction in the ESF due to the presence of sub-standard RC barriers. Research results showed that AASHTO’s existing procedure to determine the transverse static capacity of RC barriers may underestimate capacity by approximately 50%. In addition, the inadequacy of sub-standard barriers to absorb and/or redirect an impacting vehicle was shown to relate to geometrical deficiency (insufficient height), meaning that sub-standard barriers can resist high-impact load demands and protect piers if the barrier is a sufficient height (i.e., 42 in. for TL-4). Sub-standard barriers may reduce the AASHTO-required ESF for bridge piers by at least 25%.]]></description>
      <pubDate>Mon, 08 Jun 2026 08:32:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2709180</guid>
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