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    <atom:link href="https://rip.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>Research in Progress (RIP)</title>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Salem District Distributed Acoustic Sensing Pilot on I-81: Performance Evaluation Research Proposal</title>
      <link>https://rip.trb.org/View/2778217</link>
      <description><![CDATA[Virginia Department of Transportation (VDOT) has an extensive network of fiber optic cables that provide the opportunity for Distributed Acoustic Sensing (DAS) to monitor traffic. DAS operates on existing dark (i.e., unused) fibers, using vibrations to characterize events such as passing cars or incidents like vehicles stopping or crossing over rumble strips. By following traces along a cable, these systems can often identify vehicle trajectories and impute speeds and vehicle class. The accuracy and sensitivity of DAS systems is greatly impacted by fiber installation parameters, including the cable type, installation method, depth, and distance from the roadway. This has the potential to greatly add to VDOT’s sensing space along rural roads without additional capital investment, supplementing existing camera systems. Salem District is piloting a DAS unit at three different sites to determine its effectiveness for TOC alerts of events like disabled vehicles. This project will evaluate the system’s effectiveness for alerts and traffic parameter measurements, enumerate considerations for statewide deployment, and study how VDOT’s fiber installation policies impact DAS sensing capabilities.]]></description>
      <pubDate>Thu, 17 Sep 2026 09:02:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/2778217</guid>
    </item>
    <item>
      <title>Pavement Deterioration Models Review</title>
      <link>https://rip.trb.org/View/2764010</link>
      <description><![CDATA[The Virginia Department of Transportation (VDOT) maintains a pavement network consisting of more than 130,000 lane miles. Each year, VDOT uses the results of an automated condition survey to quantify the pavement condition in terms of a Critical Condition Index (CCI). From this survey and considering other constraints, VDOT employs a decision-tree process to suggest one of five treatment categories to program pavement maintenance treatments each year. Pavement deterioration models that were developed by a consultant in 2007 are used to predict the future condition of a pavement based on the pavement family type and previous maintenance treatment category. The purpose of this study is to review the pavement deterioration models used in VDOTs pavement management system to determine if they still reflect the current trends of VDOT’s pavement network and suggesting updates if required.   ]]></description>
      <pubDate>Thu, 20 Aug 2026 08:08:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2764010</guid>
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    <item>
      <title>Verification and Implementation of Production-Level Long-Term Durability Assessment for Asphalt Mixtures</title>
      <link>https://rip.trb.org/View/2726544</link>
      <description><![CDATA[The primary purpose of this study is to verify the suitability, practicality, and implementation viability of the recommended production-level long-term oven-aging (LTOA) protocols and associated cracking tolerance (CT) index threshold within Virginia Department of Transportation's (VDOT's) Balanced Mix Design framework. While the previous research established a practical design-stage LTOA protocol and recommended production-level aging procedures, additional evaluation is needed to confirm that the proposed production protocols and CT index threshold provide a reliable basis for future implementation into statewide production acceptance and quality assurance practices.]]></description>
      <pubDate>Thu, 09 Jul 2026 08:06:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2726544</guid>
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    <item>
      <title>Evaluation of Thick Lift Surface Asphalt Pavement Mixtures</title>
      <link>https://rip.trb.org/View/2721743</link>
      <description><![CDATA[When paving asphalt mixtures in a deep patching and rehabilitation application the Virginia Department of Transportation (VDOT) currently limits lift thickness to approximately three to four times the nominal maximum aggregate size (NMAS) of the mixture (VDOT, 2018). For a typical asphalt surface mixture having an NMAS of 9.5 mm, the practice generally limits lift thickness to approximately 1.5 inches. Where deeper distresses must be repaired multiple lifts will be required which increases construction time, prolongs traffic disruption, and introduces additional interfaces between lifts that may affect construction efficiency and field performance.

Therefore, there is a need to evaluate whether asphalt surface mixtures can be placed in a single thick lift without compromising construction quality or long term performance. The study addresses this need by investigating 1) the performance of a 9.5 mm NMAS asphalt mixture in a single 4 inch lift and (2) evaluating the performance of that layer using a combination of laboratory testing, controlled construction, and accelerated pavement testing to assess compaction behavior, material properties, and structural performance.]]></description>
      <pubDate>Thu, 02 Jul 2026 10:54:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/2721743</guid>
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    <item>
      <title>Enhanced Risk Management for Surface Transportation Projects</title>
      <link>https://rip.trb.org/View/2702875</link>
      <description><![CDATA[Threats to develop transportation projects on-time and on-budget should first appear as project risks. Not properly identifying, evaluating, or responding to these risks can directly jeopardize the project’s success. The existing risk management guidance from Virginia Department of Transportation (VDOT) recommends practices that approach risk through a qualitative lens. The result is risk management practices among VDOT and locality project managers that vary widely. This initiative will create a Risk Library that quantifies risk in terms of impacts on project success, including budget impacts, schedule impacts, and realization of the project, along with strategies to reduce and mitigate risks at various stages in project development.  Project risks will be identified by an extensive literature review and stakeholder outreach. Risk quantitative characteristics will be vetted by industry experts and approved by VDOT Project Management Office (PMO). The result will be a new Risk Library that will empower project managers and their teams to be more effective and efficient, while positioning VDOT to pursue unprecedented consistency of risk governance and risk integration into the development of their Six Year Improvement Program (SYIP).]]></description>
      <pubDate>Thu, 14 May 2026 11:07:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2702875</guid>
    </item>
    <item>
      <title>Real-Time Anomaly Detection System for Signalized Intersections</title>
      <link>https://rip.trb.org/View/2673038</link>
      <description><![CDATA[Automated Traffic Signal Performance Metrices (ATSPMs) rely on high-resolution controller data to support signal operations and maintenance. While existing ATSPM Watchdog tools can identify certain detector malfunctions, they typically rely on static thresholds set across the entire system, limiting their ability to detect issues promptly and adapt to site-specific traffic patterns. This project develops and evaluates a statistical, spatiotemporal anomaly detection framework that leverages historical detector behavior and agreement among neighboring detectors to improve alert timeliness and accuracy. The research will characterize practitioner needs, define normal detector behavior, develop and test statistical detection and classification methods, and quantify benefits relative to static thresholds. Results will inform a roadmap for potential real-time implementation within Virginia Department of Transportation (DOT) systems.]]></description>
      <pubDate>Tue, 24 Feb 2026 10:25:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2673038</guid>
    </item>
    <item>
      <title>Developing Simplified and Unified Planning-Level Metrics for Operational Benefits </title>
      <link>https://rip.trb.org/View/2663585</link>
      <description><![CDATA[Transportation agencies increasingly rely on Performance-Based Planning and Programming (PBPP) to make transparent, data-driven investment decisions and to evaluate and prioritize projects. In Virginia, Virginia Department of Transportation (VDOT) and the Office of Intermodal Planning and Investment have advanced PBPP through VTrans, Project Pipeline, and SMART SCALE, a recognized program for ranking investments across safety, congestion, accessibility, environmental quality, and economic development. In addition, VDOT’s Project Planning function establishes a long-term vision for the transportation system. Despite progress in Virginia’s planning framework, no rapid and transferable methodology exists to quantify operational benefits of roadway and ITS improvements. Current approaches, such as the Interstate Operations and Enhancement Program and SMART SCALE , provide valuable insights but lack standardized lightweight measures of operational benefit metrics. When VDOT needs to compare alternatives or screen early-stage concepts, analysts must rely on microsimulation, HCM procedures, or project-specific before–after studies. These methods are accurate but slow, data-intensive, and not scalable to dozens or hundreds of candidate projects. The absence of standardized, easy-to-apply operational metrics constrains Virginia’s ability to efficiently screen projects, communicate benefits, and ensure consistent decision-making within PBPP. This research will define Operational Modification Factors, a proportional before/after change derived from operational benefit metrics, and develop a reusable and transferable planning-level methodology that enables VDOT to estimate operational benefits rapidly using limited inputs (e.g., v/c ratio, facility type, AADT, geometry, improvement type). 
]]></description>
      <pubDate>Tue, 03 Feb 2026 10:42:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2663585</guid>
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    <item>
      <title>Evaluating Fuzzed Connected Vehicle Data to Support Travel Demand Modeling </title>
      <link>https://rip.trb.org/View/2663276</link>
      <description><![CDATA[The Virginia Department of Transportation (VDOT) is currently developing a method to use connected vehicle (CV) data to support the development of travel demand models. The work includes estimating nuanced information about trip time, trip distance, and path patterns with fine geographic and temporal resolution. CV trajectory data providers may use algorithms that affect the raw vehicle trajectory data for privacy reasons. These algorithms may affect the feasibility, accuracy, and robustness of VDOT’s application of CV data for planning purposes. This project assesses the impact of such algorithms used by two different CV trajectory data providers on potential VDOT application scenarios related to calibration and validation of transportation planning models. This research will further assess the potential of using such data to support the development of truck ODs, and if feasible, a valuable enhancement to the current VDOT truck origin-destination (OD) estimation procedure.
]]></description>
      <pubDate>Sun, 01 Feb 2026 11:00:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2663276</guid>
    </item>
    <item>
      <title>Assessing Bat Use of Culverts in Virginia and Identifying Opportunities for Streamlining the Consultation Process for VDOT Projects: Phase I Study</title>
      <link>https://rip.trb.org/View/2617664</link>
      <description><![CDATA[The Virginia Department of Transportation (VDOT) must comply with the Endangered Species Act (ESA) for transportation projects that may impact federally listed bat species. In 2024, the U.S. Fish and Wildlife Service (USFWS) released several updates relevant to these requirements, including the updated Federal Highway Administration (FHWA) Programmatic Biological and Conference Opinion (PBO) for transportation projects. 

Although these updates and associated tools include several changes to improve consultation efficiencies, certain aspects of the coordination process remain outside their scope. In addition, structure assessments for bat occupancy represent a significant workload for VDOT and USFWS staff and an area where additional research is needed in Virginia. An understanding of culvert use by bats is an issue that has not yet been examined through a robust statewide study.

This research will inform the development of Virginia-specific tools and strategies to improve the efficiency and effectiveness of regulatory coordination for project reviews. The project will be conducted in two phases. Phase I will use literature findings VDOT bat survey data to develop a targeted sampling plan for Phase II field surveys to identify potential conditions where bat presence may be highly unlikely.  Phase I will also include a review of programmatic agreements from other states and gather input from VDOT, USFWS, and other DOT staff to find opportunities to increase the efficiency of consultation process.  The study findings will inform regulatory decisions for streamlining the project review processes and decreasing the workload for Virginia’s transportation and regulatory staff.
]]></description>
      <pubDate>Tue, 04 Nov 2025 10:05:56 GMT</pubDate>
      <guid>https://rip.trb.org/View/2617664</guid>
    </item>
    <item>
      <title>Experimental Approaches for Integrating External Factors into Pathway for Planning (P4P) Traffic Volume Forecasting</title>
      <link>https://rip.trb.org/View/2573011</link>
      <description><![CDATA[Traffic volume forecasts are critical for effective transportation planning, helping to assess future roadway demand and allocate resources efficiently.  Virginia’s Department of Transportation (VDOT) uses the Pathway for Planning (P4P) web-based application to provide historical and forecasted traffic volume data.  However, P4P’s current trend-based approach, which relies on linear regression, may either under- or over-predict future traffic volumes due to the lack of consideration for socioeconomic changes.

The purpose of this study is to evaluate alternative methods for forecasting annual traffic volumes by incorporating external socioeconomic factors such as population growth, employment trends, and a forecast change in personal income from reliable sources.  This research focuses on annual average daily traffic volumes (AADT) only and excludes daily, seasonal, and project induced traffic variations. The research will include a literature review, a survey focused on segment-level traffic forecasting, an exploration of available external data, and the development of a pilot forecast model in VDOT Fredericksburg District as a case study.  Statistical analyses will be conducted to ensure region-specific predictions and to evaluate the effectiveness of alternative models for enhancing the P4P platform.  The goal of this work is to incorporate socioeconomic factors into what are currently trend-based traffic volume forecasts.  If this modification improves forecast accuracy, it may also improve infrastructure planning and policy decisions across Virginia.
 
]]></description>
      <pubDate>Thu, 10 Jul 2025 08:17:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2573011</guid>
    </item>
    <item>
      <title>Improving Holiday Congestion Forecasting on Interstate Highways</title>
      <link>https://rip.trb.org/View/2571772</link>
      <description><![CDATA[Holiday travel periods present a significant challenge for speed and congestion prediction due to highly variable travel behavior, event-driven surges, and inconsistent congestion patterns. The Virginia Department of Transportation (VDOT) currently relies on historical averages of travel speeds based on INRIX TMC data from the past three years, averaged by day and week of the holiday period, to predict likely congestion levels during holidays. While this method has shown good accuracy for holidays that fall on the same day of the week and month, it is less effective for holidays that occur on specific dates, such as the 4th of July and Christmas Day, where travel patterns shift year to year based on the day of the week of the holiday.
This research aims to develop an advanced framework to improve predictions of travel speeds and the expected levels of congestion during holidays designated by the Commonwealth of Virginia. The project will explore a variety of modeling techniques- including machine learning classifiers, regression models, and rule-based systems to determine the most effective method for this application. The models will leverage 30-minute interval INRIX XD speed data between 7:00 AM and 12:00 AM for holidays, on Virginia’s interstate network for 2022–2024.  Additional input features will include such factors as time of day, date context (e.g., "day before holiday," “day after holiday”, day of week), direction of travel (e.g., inbound, outbound, or balanced conditions), urban/rural classification, and VDOT district. In addition to XD data, the research team will evaluate the incorporation of supplementary data sources such as roadway weather information system (RWIS) or National Oceanic and Atmospheric Administration (NOAA) weather data, incident reports, and historical volume trend overlays to enhance model performance. Non-holiday data will also be analyzed to adjust for annual baseline changes in traffic volume, supporting more robust holiday comparisons.     
]]></description>
      <pubDate>Thu, 03 Jul 2025 09:08:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/2571772</guid>
    </item>
    <item>
      <title>Utilizing Big Data to Verify and Enhance Route Choice Models in Travel Demand Modeling</title>
      <link>https://rip.trb.org/View/2553840</link>
      <description><![CDATA[Virginia Department of Transportation (VDOT) has invested roughly $5M to maintain and improve its long-range travel demand models, which are needed to help analyze candidate transportation projects.  A key step within these models is “trip assignment” where the path vehicles follow is represented in the network.  High-resolution global positioning system (GPS)-level data offers the potential to improve the accuracy of this step.  However, VDOT staff are finding some discrepancies between route choice as currently represented in demand models and route choice as observed by GPS data—and it is not immediately clear how to resolve this discrepancy.  This research effort will determine the best way to use the GPS data to enhance model accuracy.  Note that a substantial amount of effort needed to make this determination has already been completed through an earlier research effort, and thus, this new study adds additional work to address this trip assignment step.]]></description>
      <pubDate>Thu, 15 May 2025 09:16:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/2553840</guid>
    </item>
    <item>
      <title>Updating VDOT’s Concrete Permeability Requirements</title>
      <link>https://rip.trb.org/View/2476010</link>
      <description><![CDATA[This study aims to update Virginia Department of Transportation's (VDOT’s) concrete permeability requirements by revising the Virginia Test Method (VTM) 112 and VDOT’s Road and Bridge Specifications. The focus is on enhancing VDOT’s concrete permeability testing by expanding the use of resistivity-based methods, such as the surface resistivity, AASHTO T 358 (VTM 112 - Method B), which correlate well with results from the rapid chloride permeability test (RCPT), ASTM C1202 (VTM 112- Method A). Resistivity-based methods are faster and easier to conduct while providing a reliable indicator of concrete durability. This study will determine the effects of various curing methods and mixture compositions on resistivity and chloride permeability, aiming to establish new resistivity-based specifications. The outcome of this study will be a revised VTM 112 and updated permeability requirements that improve concrete approval and acceptance processes, reduces time consuming testing, and enhances the durability assessment of concrete materials across Virginia. ]]></description>
      <pubDate>Sat, 14 Dec 2024 08:50:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/2476010</guid>
    </item>
    <item>
      <title>Meaningful Public Involvement in Transportation Decision-Making: A Comparative Analysis of State Policies and Practices</title>
      <link>https://rip.trb.org/View/2470851</link>
      <description><![CDATA[This project examines public engagement processes in state transportation planning and project design across Delaware, Maryland, Virginia, and West Virginia. Building on our Year 1 study of decision-making in the Delaware Department of Transportation (DelDOT), this Year 2 research expands the scope to assess engagement strategies used by state Departments of Transportation (DOTs) in the region. Using a multiple case study design, we will conduct a document review and informational interviews with key informants to analyze the consistency, variation, and effectiveness of public engagement practices. Key research questions include: (1) How effective are public engagement processes in state transportation planning and design? (2) What methods are used to engage different communities? and (3) How have engagement strategies evolved, particularly in response to the COVID-19 pandemic? Rather than critiquing state agencies, this study aims to document engagement processes constructively and provide insights for improving participation efforts. Findings will be shared with state DOT leadership and local government officials, contributing to both transportation planning research and practice. This study will also inform a potential Year 3 project that identifies engagement challenges and evaluates strategies to enhance public participation in transportation decision-making.]]></description>
      <pubDate>Fri, 06 Dec 2024 16:30:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2470851</guid>
    </item>
    <item>
      <title>Development of an Evaluation and Acceptance Process for Traffic Count Devices </title>
      <link>https://rip.trb.org/View/2433965</link>
      <description><![CDATA[As new traffic count device technologies emerge, it is crucial to establish guidelines for their evaluation and acceptance for use by the Virginia Department of Transportation (VDOT). These guidelines should consider factors such as count accuracy and reliability. Having guidelines will ensure that the most effective and efficient technologies are implemented for traffic monitoring and management. This project aims to develop an evaluation process for assessing the suitability of traffic count sensors for traffic monitoring purposes. The methodology will be tested and validated using a vision-based classification device as a pilot. The potential implementation of this research is that the Traffic Operations Division (TOD) can utilize the research results to establish an official traffic count device verification and acceptance procedure. This standardized procedure can be applied to all future traffic count devices seeking verification for use by VDOT.]]></description>
      <pubDate>Tue, 24 Sep 2024 10:05:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2433965</guid>
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