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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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>Exploring the Use of VMT as an Evaluation Metric Within Virginia’s Transportation Planning Process </title>
      <link>https://trid.trb.org/View/2717163</link>
      <description><![CDATA[For several decades, transportation planners and engineers have used automobile Level of Service (LOS) to communicate transportation system conditions. In Virginia, stakeholders such as Fairfax County officials have shown interest in supplementing LOS with vehicle miles traveled (VMT), which can be a useful measure of vehicle travel and a proxy for other categories like vehicle emissions. Although using VMT to describe overall travel patterns is not new, some states and localities have adjusted their transportation analysis processes in recent years to focus on VMT in conjunction with VMT reduction goals. In a LOS-focused process, traffic congestion often drives mitigation strategies. In a VMT-focused process, the overall goal of reducing the negative effects of added local or regional vehicle travel from land development and transportation projects drives mitigation strategies. The purpose of this study was to explore how VMT might be used as a transportation evaluation metric in Virginia, based on reviewing how VMT has been applied elsewhere and translating such uses to the Virginia context, by (1) documenting LOS and VMT use in Virginia, (2) assessing how other states use VMT, (3) interviewing planners in California and Oregon, and (4) evaluating two Virginia pilot projects. Findings indicate that VMT is currently used in congestion management to understand induced demand, in environmental analysis to estimate mobile source air toxins and greenhouse gases, in safety evaluations as a measure of exposure, and in efforts to further equity and economic development. The drawbacks and complications of using VMT as a metric include difficulties collecting data or extrapolating VMT from travel demand models, the need for nuance when using VMT as a proxy measure for smart growth or environmental health, and the implementation difficulties that often attend novel applications. Two findings are noteworthy: (1) VMT is used at several points in Virginia’s planning process—more than was expected at the outset of this study—which may surprise some localities because they often focus on one particular planning element (land development), which uses LOS—thus, this topic could be a subject for greater Virginia Department of Transportation and locality collaboration—and (2) induced VMT calculators exist, but the geographical extent of the analysis greatly affects the interpretation—for example, whether to consider VMT on just a reconstructed segment or a certain distance away from the site—so choosing the right extent for such calculations would be an important implementation consideration. This report recommends that the Virginia Department of Transportation consider the pros and cons of using VMT when updating relevant guidance documents.]]></description>
      <pubDate>Sat, 04 Jul 2026 16:36:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717163</guid>
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    <item>
      <title>Quantifying Disproportionate User Costs Caused by Pavement Conditions</title>
      <link>https://trid.trb.org/View/2685575</link>
      <description><![CDATA[Pavement conditions are often linked to safety outcomes, greenhouse gas emissions, and a region’s economic development. While a pavement management program aims to improve overall network conditions over time, recent research shows that the burden of poor condition pavements falls proportionally on certain corridors or regions within the network. Moreover, recent studies have highlighted the lack of standardized performance measures for evaluating disproportional impacts among road users. For these reasons, this paper proposes new metrics to quantify the monetary impacts on road users, aiming to better understand the impacts. We compared the existing federal measures with the new metrics proposed to quantify the economic impact of pavement conditions on road users, followed by a detailed discussion of the proposed new set of performance measures. The effectiveness of these measures was demonstrated using New Mexico as a case study, a state with a 50.2% Hispanic population and 18.4% of residents living in poverty. The methodology was designed to be replicable using public data available to state departments of transportation. The new performance measures provide additional perspectives beyond those offered by federal pavement condition percentages. In summary, this paper demonstrates that the proposed measures help identify pavement condition disparities that could impact areas disproportionally and can help state departments of transportation assess the need for targeted, localized approaches to budget allocations and infrastructure investment.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685575</guid>
    </item>
    <item>
      <title>Operational Performance of Passenger Ferry Service</title>
      <link>https://trid.trb.org/View/2581634</link>
      <description><![CDATA[Passenger ferry boats of different capacities operate and are one of the most affordable modes of transportation. This research investigates the effectiveness of passenger ferry services within Mumbai Municipal Boundary, operating in its backwater, creek networks, and western and eastern coastlines. Passenger ferries have the potential to promote sustainable and resilient transportation in the region. The literature review shows an absence of evaluation mechanisms to assess the quality and performance provided for passenger ferries in Indian cities using the Level of Service (LOS) concept. The study aims to assess operational performance by proposing a step-by-step evaluation framework for ferry services based on the LOS. Both passengers and operators’ perspectives are considered while suggesting proposals. The outcome is in the form of a procedure that can be adopted for forming and calculating route-wise LOS and recommendations for operators to generate additional revenue. The insights gained from this research will be valuable for policymakers, academics, and stakeholders, enabling them to assess, improve, and allot investments for ferry services in their respective cities as per their unique requirements.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581634</guid>
    </item>
    <item>
      <title>Integrating Traffic Signal Performance Measures into Agency Business Processes</title>
      <link>https://trid.trb.org/View/2711607</link>
      <description><![CDATA[This report discusses uses of and requirements for performance measures in traffic signal systems facilitated by high-resolution controller event data. Uses of external travel time measurements are also discussed. The discussion is led by a high-level synthesis of the systems engineering concepts for traffic signal control, considering technical and nontechnical aspects of the problem. This is followed by a presentation of the requirements for implementing data collection and processing of the data into signal performance measures. The remaining portion of the report uses an example-oriented approach to show a variety of uses of performance measures for communication and detector system health, quality of local control (including capacity allocation, safety, pedestrian performance, preemption, and advanced control analysis), and quality of progression (including evaluation and optimization).]]></description>
      <pubDate>Sun, 28 Jun 2026 18:51:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711607</guid>
    </item>
    <item>
      <title>Interim Automatic Traffic Advisory and Resolution Service (ATARS) Hardware Timing Analysis</title>
      <link>https://trid.trb.org/View/2705394</link>
      <description><![CDATA[The objective of Automatic Traffic Advisory and Resolution Service (ATARS) hardware timing analysis is to provide sufficient information on the execution time characteristics of ATARS to: (1) permit prospective contractors bidding on an ATARS request for proposals to realistically estimate the size of the system they are proposing, and (2) to provide the government proposal evaluators with a technical basis for evaluating proposed computer configurations. This report presents the methodology for acquiring the required data and for analyzing the data to satisfy the two objectives. It is concluded that the computer performance monitoring system, which was designed and built to measure the execution time of computer subtasks within the Discrete Address Beacon System (DABS) and to count the occurrence of events within the selected task, is a suitable instrument for collecting the required data. Multiple regression analysis was found to provide excellent execution time models and to provide information required to identify critical subtasks within ATARS.]]></description>
      <pubDate>Tue, 16 Jun 2026 09:35:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2705394</guid>
    </item>
    <item>
      <title>Measuring the Last-Mile: A Comprehensive Evaluation of Synthesis Approaches to Address Data Gaps for Local Freight Decision-Making (Phase 1)</title>
      <link>https://trid.trb.org/View/2712636</link>
      <description><![CDATA[The purpose of this study is to comprehensively review the current landscape of freight data available for local agency decision-making, to identify existing data gaps and limitations that inhibit data-driven decision-making, and to identify relevant machine learning, mathematical modeling, and generative artificial intelligence (AI) approaches to address these gaps. Specific project tasks included: (1) a comprehensive review of both academic and practical freight data literature to identify commonly used freight data sources, common applications of freight data for agency decision-making, and specific performance metrics needed for different decision types; (2) a detailed case study of the New York City Department of Transportation – including a stakeholder workshop and a systematic review of seven agency and commercial data sources; (3) mapping of performance metrics vs. specific local agency data needs and vs. available data sources; (4) identification of critical data gaps and limitations; and (5) comprehensive review of applications of machine learning, mathematical modeling, and advanced generative modeling techniques to identify promising approaches to address persistent data gaps. Key outputs from this analysis include a comprehensive summary of freight data sources and their potential applications; evaluation matrices mapping detailed performance metrics to specific local freight-related decisions and mapping detailed performance metrics obtainable from existing data sources; and recommended approaches for freight data synthesis to address remaining gaps.]]></description>
      <pubDate>Tue, 16 Jun 2026 07:28:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712636</guid>
    </item>
    <item>
      <title>Improved Signalized Intersection Performance Using Computer Vision and Artificial Intelligence</title>
      <link>https://trid.trb.org/View/2712641</link>
      <description><![CDATA[Signalized intersections are critical points in urban transportation networks where congestion, delays, and safety risks are most prominent. Traditional approaches for performance evaluation rely on manual field counts, loop detectors, or expensive infrastructure-based systems, which are often limited in accuracy, scalability, and adaptability. This project explored the use of computer vision and artificial intelligence (AI) to develop automated tools for intersection performance analysis. Three primary methods were investigated: (1) a vehicle counting framework based on detection–tracking–counting pipelines; (2) a queue detection approach integrated with traffic light state recognition; and (3) pedestrian behavior and interaction. Vehicle counting was implemented using a virtual line-crossing strategy combined with advanced detection and tracking models, enabling accurate measurement of turn movements across multiple lanes. Queue detection, in turn, was achieved by associating detected vehicles within lane-specific regions of interest with real-time traffic light states, providing insights into demand and delay at intersections. The pedestrian-vehicle interaction is based on trajectory extraction at the intersection. All methods were tested on drone- and camera-based video datasets collected from Louisiana intersections. Results demonstrate that the proposed algorithms achieved high accuracy, robustness to environmental variations, and efficiency suitable for near-real-time applications. A user-friendly graphical interface was also developed to allow engineers to apply these methods to raw video data, facilitating data-driven decisions for signal timing, intersection design, and congestion mitigation. The study highlights the feasibility of AI-based computer vision systems as cost-effective, scalable, and reliable alternatives for traffic performance monitoring.]]></description>
      <pubDate>Tue, 16 Jun 2026 07:28:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712641</guid>
    </item>
    <item>
      <title>Remote System Monitor Type FA-9852/1</title>
      <link>https://trid.trb.org/View/2703711</link>
      <description><![CDATA[Data were collected on the performance of the Remote System Monitor (RSM), type FA-9852/1, at the Federal Aviation Administration (FAA) Technical Center. The RSM supports the Radar Beacon Performance Monitor (RBPM) program. The performance was monitored in a real-world environment as a subtask of 9550-AAF-501-78-002. The parameters observed were azimuth, range, mode 3A code, altitude, and replies per scan. This data report contains the results of these tests.]]></description>
      <pubDate>Mon, 15 Jun 2026 17:09:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703711</guid>
    </item>
    <item>
      <title>Summary of Transponder Data May 1979 Through November 1979</title>
      <link>https://trid.trb.org/View/2703706</link>
      <description><![CDATA[The purpose of this effort was to determine the performance characteristics of air traffic control radar beacon transponders in an operational environment in general aviation aircraft. A transponder performance analyzer (TPA) was developed at the Federal Aviation Administration Technical Center to measure performance parameters of transponders installed in aircraft. The TPA was installed in a bus for mobility and simulates an air traffic control beacon interrogator (ATCBI) to facilitate measurement of 15 transponder parameters in approximately 30 seconds. A standard gain horn antenna is utilized to couple the signals between the TPA bus and the aircraft. Transponder data were collected at six different geographic locations resulting in more than 690 samples of general aviation transponders. Results show that 42 percent of the transponders met all measured parameters. This is a slight improvement over the 1977/1978 data and is attributed to inclusion of data collected at general aviation airports in the Atlanta area. It is recommended that a study be conducted to determine the effects of transponder performance on the air traffic control systems (Automated Radar Terminal System (ARTS) and National Airspace System (NAS)) by individually varying each of the 15 parameters outside of their specification limits.]]></description>
      <pubDate>Sun, 14 Jun 2026 16:17:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703706</guid>
    </item>
    <item>
      <title>Phase 2 Revised Performance Measurement and Evaluation Support Plan (PMESP) – Buffalo NY ITS4US Deployment Project</title>
      <link>https://trid.trb.org/View/2711615</link>
      <description><![CDATA[The Buffalo NY ITS4US Deployment Project seeks to improve mobility to, from and within the Buffalo Niagara Medical Campus by deploying new and advanced technologies with a focus on addressing existing mobility and accessibility challenges. Examples of the technologies to be deployed are electric and self-driving shuttles, a trip planning app that is customized for accessible travel, intersections that use tactile and mobile technologies to enable travelers with disabilities navigate intersections, and Smart Infrastructure to support outdoor and indoor wayfinding. The deployment geography includes the 120-acre Medical Campus and surrounding neighborhoods with a focus on three nearby neighborhoods (Fruit Belt, Masten Park, and Allentown) with underserved populations (low income, vision impaired, deaf, or hard of hearing, wheeled mobility device users and older adults). This document describes the Performance Measurement and Evaluation Support (PMESP) Plan, originally drafted during Phase 1 and now updated during Phase 2 of the Complete Trip Deployment in Buffalo, New York. This PMESP lists the performance measures and targets based on deployment goals and use case scenarios, describes the confounding factors in measurement and proposed mitigation approaches, details the experimental design for each use case, and defines the proposed data collection plan for deployment to ensure the required data is collected for system measurement.]]></description>
      <pubDate>Fri, 12 Jun 2026 16:00:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711615</guid>
    </item>
    <item>
      <title>Create a Performance Management 'Blue Book'</title>
      <link>https://trid.trb.org/View/2712195</link>
      <description><![CDATA[Transportation performance management (TPM) is a strategic approach that uses system performance data to guide decision-making and optimize the planning, operation, and maintenance of transportation networks. As states, regions, and local governments increasingly face challenges like budget constraints, aging infrastructure, population growth, and the need for sustainability, effective performance management (PM) becomes essential in ensuring that transportation investments deliver maximum value.

Federal legislation has established a national framework for performance-based transportation management. These mandates have encouraged state departments of transportation and metropolitan planning organizations to adopt a performance-driven approach to managing transportation assets, reducing congestion, improving safety, and advancing environmental sustainability. Research is needed to develop a resource that will standardize and document practices, metrics, methodologies, and case studies to help transportation agencies effectively implement TPM frameworks. This TPM “Blue Book” will serve as a critical resource for state and local transportation agencies to benchmark their PM efforts, identify gaps, and integrate PM into long-term planning and investment strategies.

The objective of this research is to create a guide that standardizes effective practices, performance metrics, and methodologies for transportation agencies in the United States. The Blue Book will offer actionable guidelines to implement TPM frameworks effectively, aiding agencies in data-driven decision-making, resource optimization, and alignment with federal mandates. By addressing challenges like data management and funding limitations, the TPM Blue Book aspires to build more sustainable, efficient, and safe transportation systems.

 ]]></description>
      <pubDate>Tue, 09 Jun 2026 17:31:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712195</guid>
    </item>
    <item>
      <title>Phase 2 Performance Measurement and Evaluation Support Plan (PMESP) Heart of Iowa Regional Transit Agency ITS4US Deployment Project</title>
      <link>https://trid.trb.org/View/2706015</link>
      <description><![CDATA[Heart of Iowa Regional Transit Agency (HIRTA) is one of four awardees for Phase 2 of the ITS4US program for its proposed concept “HIRTA Health Connector: Bridging the Gap Between Healthcare and Transportation” (Health Connector) by the United States Department of Transportation (USDOT). Per the goals of the program, Health Connector project is focused on improving transportation access to healthcare for all in Dallas County, Iowa. This Performance Management and Evaluation Support Plan (PMESP) provides an approach for measuring the outcomes of the Health Connector system. This document defines goals and objectives and identifies relevant performance measures and targets. The performance measures take into account the user scenarios developed as part of ConOps. Further the PMESP defines the approach for conducting analyses to calculate performance measures. PMESP also provides our approach for supporting the Independent Evaluation (IE) team identified by the USDOT. This document has been updated from the PMESP submitted as part of Phase 1 to reflect the new expectations and understanding around data, data sources, and goals established as part of Phase 2. As part of Phase 2, updates to the design of each performance measure and updates to the data used to assess each performance measure were the most critical changes made. Note that all performance measures require cross referencing of demographic data to evaluate impacts on each of the user groups. Therefore, all measures will also involve profile data on whether a Traveler is in one or more of those groups. The original numbering of performance measures was maintained for clarity and consistency purposes when referencing previous project documents.]]></description>
      <pubDate>Tue, 02 Jun 2026 11:02:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706015</guid>
    </item>
    <item>
      <title>Sustainable Transport Appraisal: A Literature Review and Implications for Policy Makers</title>
      <link>https://trid.trb.org/View/2580083</link>
      <description><![CDATA[Questions have arisen regarding whether current transport appraisal methodologies and parameters are prejudicial to sustainable transport solutions. With the emergence of the climate change and sustainability agenda, there is wide recognition of the need for modal shift from private-car-based modes to sustainable modes such as public transport and active travel. Despite this policy re-orientation, the use of the traditional appraisal methods and parameters with their inherent assumptions does not always support the policy. Cost-benefit analysis (CBA) is likely to recommend options that do not necessarily align with current sustainable policy goals. To cater for hard-to-monetise benefits, multi-criteria analysis (MCA) is employed in transport appraisal. However, there is a concern that multi-criteria analysis (MCA) is difficult to operate given the need for agreed weightings among stakeholders. This study summarises the challenges of the current appraisal frameworks through a literature review and analysis of the appraisal framework in Ireland. By doing so, this study aims to outline what should be improved for transport appraisal to work under the sustainability policy agenda.]]></description>
      <pubDate>Fri, 29 May 2026 15:36:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580083</guid>
    </item>
    <item>
      <title>Asset Management Developments in Transport Infrastructure Ireland (TII)</title>
      <link>https://trid.trb.org/View/2580081</link>
      <description><![CDATA[Transport Infrastructure Ireland’s (TII) primary functions are to operate, maintain and extend the life of national roads, tunnels, and light rail infrastructure in Ireland. Among the priorities for investment include the use of asset management principles to manage assets safely, sustainably, efficiently, and effectively over their useful life. This paper describes TII’s journey in asset management including the development of TII’s recently published Asset Management Policy, Strategy and Framework, as well as the ongoing development of Strategic and Group-level Asset Management Plans for the various asset classes within TII to align with its overall strategic objectives and organisational goals. A best-fit approach has been developed which addresses TII’s changing operational conditions and commitments in terms of sustainability, circular economy, and climate adaptation. A hierarchical structure based on the “line of sight” principal is presented in which TII proposes to achieve its overall asset management objectives in line with an ISO 55000 integrated asset management system approach.]]></description>
      <pubDate>Fri, 29 May 2026 15:36:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580081</guid>
    </item>
    <item>
      <title>Maintenance Decision Support System Refinement</title>
      <link>https://trid.trb.org/View/2705945</link>
      <description><![CDATA[The objectives of the Maintenance Decision Support System are to: (1) Assess current road and weather conditions using observations and reasonable inferences based upon observations and physical laws. (2) Provide time- and location-specific weather forecasts along transportation routes. (3) Predict how road conditions would change due to the combined effects of the forecast weather and the application of several candidate road maintenance treatments. (4) Notify state agencies of approaching adverse conditions and suggest optimal maintenance treatments that can be achieved with resources available to the transportation agencies. (5) Evaluate the reliability of predictions and the effectiveness of applied maintenance treatments for specific road and weather conditions so that the decision support logic can be improved. Continuing the efforts of the previous phases of work, the member agencies voted on the future direction and tasks of the Maintenance Decision Support System (MDSS) pooled fund study (PFS). Some of these tasks represent continuation of previous phases of work and others are new endeavors for the project. The primary research areas selected by members of the MDSS project panel include: (1) Investigate methods to improve the MDSS model for better support of frost, freezing rain and other weather conditions; (2) Assess recommendations based on user feedback in real-time with post-recommendation analysis to improve MDSS modeling; (3) Analyze the use of Level of Service in DOT operations and understand how this functionality can be improved within MDSS; (4) Focus on Liquids as a priority treatment recommendation and develop processes that facilitate specialty liquids within MDSS; (5) Conduct a discovery process on Performance Measurement methods that would be applicable for MDSS with the goal of implementing these methods to demonstrate MDSS value; and (6) Improve the Route Configuration Process by implementing automated functionality, clear guidance for users, and preparing for the future of MDSS.]]></description>
      <pubDate>Thu, 21 May 2026 22:52:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2705945</guid>
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