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    <title>Research in Progress (RIP)</title>
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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>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>National Road Research Alliance (Phase-3)</title>
      <link>https://rip.trb.org/View/2678150</link>
      <description><![CDATA[This solicitation is for the continuation of the National Road Research Alliance (NRRA) for another 5 years and to continue to support Veda development to increase efficiency and effectiveness of both efforts. 

The NRRA exists to strategically implement cooperative pavement research. State agencies, industry, academia, consultants and associations work together to identify problems, complete research projects and implement results. The NRRA goal is to help agencies nationwide achieve consistent benefits from real world road research. It also seeks to provide members a forum to discuss issues and an outdoor, real-world laboratory the Minnesota Road Research Facility (MnROAD) for evaluating cutting-edge pavement technologies. The NRRA consists of five project teams: Flexible, Rigid, Geotechnical, Intelligent Construction Technologies, and Preventive Maintenance and is governed by an Executive Committee made up of two representatives from each government agency participating in the study. Each team activities include prioritization of short and long-term research, development of long-term research test sections at MnROAD and providing input for technology transfer. ]]></description>
      <pubDate>Fri, 06 Mar 2026 13:10:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/2678150</guid>
    </item>
    <item>
      <title>Develop Performance Models for Different Preventive Maintenance Treatments</title>
      <link>https://rip.trb.org/View/2604521</link>
      <description><![CDATA[The Texas Department of Transportation's (TxDOT) Pavement Management Information System (PMIS), recently implemented as Pavement Analyst (PA), stores and analyses network information and pavement performance data to select projects for maintenance and rehabilitation. After the network is analysed, an optimization algorithm produces one of the following recommendations: do nothing, preventive maintenance (PM), light, medium or heavy rehabilitation. PM includes several treatment options associated with very different cost and performance, e.g., seal coat, thin overlay, microsurfacing, etc. Since the performance and cost of these options are different, research is needed to quantify the difference and to incorporate this information into PMIS. Previous TxDOT-sponsored projects have developed performance models and decision trees that were last updated in 2021 as part of Project 0-6988, "Quantification of the Performance of Preventive Maintenance and Rehabilitation Strategies." This update was based on data available at that time, which was a combination of visual distress surveys and automated data. Now, more accurate automated data are available. Therefore, the research team will develop pavement performance models for different PM treatments, update the current decision trees and performance models, validate the models with new data, and develop an implementation plan to incorporate the findings into PMIS.]]></description>
      <pubDate>Mon, 29 Sep 2025 16:08:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2604521</guid>
    </item>
    <item>
      <title>Quantifying the Life Cycle Cost Implications of Preservation Treatments</title>
      <link>https://rip.trb.org/View/2479849</link>
      <description><![CDATA[Pavement engineers and researchers are in agreement that considerable savings can be obtained by adopting a pavement preservation approach. Pavement preservation provides a means for maintaining and improving the functional condition of an existing pavement segment through application of a preventative and responsive set of treatments that slow deterioration or correct isolated defects and thus increase the length of time between major rehabilitation projects which will benefit roadway users and decrease costs related to project administration. These treatments are designed to prolong the service life of the surface or near-surface layer without adding significant structural capacity to the pavement structure. One challenge for preventive maintenance strategies is that it is time-sensitive. Premature or delayed maintenance activities result in unnecessarily high maintenance costs.

The effects of preservation treatments are measurable and should be reflected in the overall models of pavement performance. Figure 1 shows a typical performance curve that illustrates the effects of applying preventive maintenance treatments. While the effects of preservation are easy to illustrate, their implementation and measured benefits are not as easy to quantify for various reasons.

This research proposes a framework for quantifying the effects of preservation treatments on pavement service life and life-cycle costs with a guide document to facilitate implementation of the framework. The proposed framework will investigate the adequacy of the use of collected condition variables such as cracking and rutting of asphalt pavements and cracking and faulting of concrete pavements to quantify the lifecycle cost implications of preservation treatments between pavement management sections that received them and those that did not. In addition, incorporating these cost implications in asset management systems would provide a means for promoting the use of preservation treatments and optimizing the allocation of resources. The findings from this study will be of immediate interest to state pavement design and maintenance engineers and others involved in the different aspects of pavements.]]></description>
      <pubDate>Wed, 18 Dec 2024 15:51:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/2479849</guid>
    </item>
    <item>
      <title>Evaluating Pavement Preservation Performance in Dry Freeze and Wet Freeze Regions Using LTPP Dataset and a Questionnaire Survey</title>
      <link>https://rip.trb.org/View/2440835</link>
      <description><![CDATA[The main goal of this proposed research project is to evaluate the effectiveness of various preventive maintenance treatments in cold regions, including both dry-freeze and wet-freeze areas. To achieve this, the project will begin with a comprehensive review of state-of-the-art practices and established methodologies in preventive maintenance. Following this, the research will involve collecting long term pavement performance data on pavement conditions and preventive maintenance treatments.

A questionnaire survey will be developed to gather information on current preventive maintenance techniques and their perceived effectiveness in cold regions across the United States. Statistical analysis will then be conducted to identify and assess the significant factors influencing the effectiveness of these maintenance treatments. The final objective is to evaluate the impact of different preventive maintenance treatments by measuring performance improvements or immediate enhancements in pavement conditions following treatment application.]]></description>
      <pubDate>Sun, 13 Oct 2024 15:53:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2440835</guid>
    </item>
    <item>
      <title>Improving the Quality of Preventive Maintenance Construction and Data Collection Practices </title>
      <link>https://rip.trb.org/View/2414392</link>
      <description><![CDATA[This pooled-fund study is being developed to assist state highway agencies (SHAs) and LPAs in reviewing and developing pavement preventive maintenance (PM) treatments which can advance their pavement preservation programs.  This study is also supplementing ongoing data analysis of existing pavement test sections in Minnesota (NRRA-MnROAD) and Alabama (NCAT) and support continued implementation activities established.  Combining these efforts will establish a national construction and data collection effort of pavement PM treatments applied to roadways at the direction of the study’s Technical Advisory Committee (TAC).  Participation in the study is being encouraged by SHAs, LPAs, FHWA, Federal Lands Highway Division, academia and industry representatives.  Collaboration with experts from these groups will help set criteria for identifying PM construction practices and data collection requirements, discuss optimal timing for placing of PM treatments and establishing the minimum number of pavement sections required for each type of PM treatment used for statistical analysis.  Non-financial participants can provide technical knowledge and input; however, financial contributors will make final decision on treatments to be constructed.

Using the outcome from the above collaborative activities, the study partners will initiate and monitor State, local, and Federal PM treatments and projects to develop preventive maintenance solutions (i.e. decision trees, toolboxes, etc.).  Implementation of practical research results from other PM cooperative projects (i.e. NCAT, MnROAD, NCPP) will be used to access the impact of preventive maintenance treatments on extending service life of pavements.  Lessons learned will be documented and shared along with information to assist in the updating of the national pavement preservation research roadmap.]]></description>
      <pubDate>Fri, 09 Aug 2024 16:30:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2414392</guid>
    </item>
    <item>
      <title>National Partnership to Improve the Quality of Preventative Maintenance Treatment Construction and Data Collection Practices</title>
      <link>https://rip.trb.org/View/2414323</link>
      <description><![CDATA[Proper use of pavement preservation treatments can effectively maintain or improve pavement condition and extend pavement life. While the benefits of pavement preservation are well-known, they are often not well-quantified. A significant research effort has been conducted under Phases I (TPF-5(267)) and II (TPF-5(375)) of the Pavement Preservation Group (PG) Study to develop performance models for a variety of treatments under different conditions, and to better quantify their expected benefits. The findings show that factors such as existing pavement condition (i.e. project selection) and the use of best practices during construction are critical to achieve good long-term performance and maximize benefits. This project is being developed to assist agencies in the implementation of pavement preservation treatments through systematic, data-driven processes to benefit their overall network condition. The main objectives of this study are to: (1) Assist agencies in the planning, construction, monitoring, documentation, and analysis of test sections.
(2) Continue data collection and analysis of existing test sections in Minnesota and Alabama. (3) Promote implementation of findings through various outreach activities.

Through the combined effort of continued research and implementation guidance, this study will support state and local agencies to develop and/or improve their pavement preservation programs by identifying and characterizing effective preservation treatments for their local conditions.]]></description>
      <pubDate>Fri, 09 Aug 2024 14:56:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2414323</guid>
    </item>
    <item>
      <title>Artificial Intelligence Driven Preventive Maintenance for Coastal Bridges in Marine Environments </title>
      <link>https://rip.trb.org/View/2406734</link>
      <description><![CDATA[Project objectives are: (1) to develop a proof-of-concept Artificial Intelligence (AI) model for optimal maintenance of coastal bridges in harsh marine environments, aimed at achieving the required performance and safety with the minimized overall maintenance cost; and (2) to pioneer a novel AI lifelong learning framework that incorporates historical records, domain knowledge, expert insights, and in-situ sensor data to transform maintenance practices across transportation systems. Problem Statement: Bridges along coastlines are inevitably subject to accelerated, corrosion-induced deterioration caused by sea salt and humidity. The maintenance of these bridges presents unique challenges but has received limited research focus. Preventive maintenance involves planned strategies of cost-effective treatments that retard deterioration and maintain or improve the function of these structures. The USDOT mandates a systematic approach to the preventive maintenance of bridges. Current maintenance often relies on engineers' judgment, which may not always maximize benefits or minimize costs. Optimized preventive maintenance can theoretically be addressed through reinforcement learning (RL). However, traditional data sources are currently insufficient for training AI models. Additionally, traditional RL struggles with handling uncertainty due to environmental variability. Recently, AI advancements, particularly in natural language processing and probabilistic deep RL, have provided new ways to address these challenges. This project will innovatively explore the use of historical textual data from bridge annual inspection reports, maintenance logs, construction documents, and national weather databases, as well as relevant research publications - data that have not previously been utilized with RL for preventive maintenance. It will also pioneer the use of probabilistic deep RL and a brand-new class of neural networks, GFlowNets, which have not yet been explored in preventive maintenance with limited and noisy datasets. Proposed Method: The method encompasses the following perspectives: (1) It involves collecting historical documents, including bridge annual inspection reports, maintenance records, construction documents, and relevant research publications related to deterioration in marine environments. This data will be utilized to fine-tune a large language model (LLM), such as BERT, to incorporate domain-specific knowledge, enabling the LLM to accurately represent text concerning deterioration and maintenance actions from relevant documents. The fine-tuned LLM can be used to generate text tokens for identifying and representing units of text clusters related to deterioration conditions, maintenance actions, costs, and the condition after maintenance from documents, exploring different text pooling and transforming methods to develop features that describe varying conditions, actions, costs, and consequences of actions across different sequences from historical documents in a similar way as the Named Entity Recognition. (2) The transformer-based AI, in a similar way to BERT, will be developed and trained to predict the masked conditions or consequences in a manner similar to how an LLM predicts the masked words in sentences, using sequences of text clusters in historical documents. This training allows the AI model to understand the underlying rules of deterioration and maintenance processes, akin to the language of natural laws, enabling it to generate simulated data for various conditions and maintenance scenarios. For instance, given a specific condition, if a certain maintenance action is taken, the model can probabilistically determine the cost of the action and the resulting condition of the bridge based on rules implied in the historical documents. (3) This simulated data will be employed to further train reinforcement learning (RL) agents through probabilistic RL or GFlowNets. The developed model will offer not just a single policy but a range of policy options whose probability distribution aligns with the cost function, allowing decision-makers to evaluate various actions and understand the associated costs and the renewed conditions. (4) The data will be continuously collected and utilized to refine the AI model further, incorporating Reinforcement learning from human feedback to include expert input within the loop, enabling it to operate in a lifelong learning mode as more data is gathered, thus enhancing the reliability of decision-making. This innovative approach will empower AI agents to make optimized decisions based on domain knowledge, historical data, current sensor data, and expert insights while accounting for uncertainty. (References will be provided upon request.)]]></description>
      <pubDate>Tue, 23 Jul 2024 16:22:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2406734</guid>
    </item>
    <item>
      <title>Guidelines for Pavement Preventive Maintenance Inspector Training</title>
      <link>https://rip.trb.org/View/2381717</link>
      <description><![CDATA[Pavement preventive maintenance is increasingly recognized by state departments of transportation (DOTs) as a valuable way of maintaining existing roadways, delaying the need for costly and disruptive full-depth repairs or replacements.

Effective preventive maintenance of roadways requires a skilled workforce and specialized equipment from state DOTs and private sector contractors who conduct construction inspection. Agencies must ensure that their inspection workforce is properly trained to meet project requirements and deadlines.

Research is needed to develop guidelines for inspector training to support agencies in successfully developing their inspection workforce. These guidelines will help improve the quality of pavement preventive maintenance treatments.

The objective of this project is to develop guidelines for pavement preventive maintenance inspector training. These guidelines shall detail the necessary skills, training, and competencies for inspectors involved in the common pavement preventive maintenance techniques for asphalt and concrete pavements as well as strategies for effective inspector workforce development, deployment, and oversight.]]></description>
      <pubDate>Tue, 21 May 2024 17:01:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/2381717</guid>
    </item>
    <item>
      <title>Develop Best Practices for Flexible Pavement Repairs</title>
      <link>https://rip.trb.org/View/2255821</link>
      <description><![CDATA[This research study aims to perform a study focusing on best practices for performing pavement preparatory work in advance of preventive maintenance (PM) surfacing contracts. The study will respond to answer, "What are the best practices for repairing a roadway before a new surface is placed?" Seal coats or thin overlays are typical PM surfacing projects. The preparatory work performed by in-house maintenance forces or maintenance contracts may include crack sealing, fog seal, repairs, milling, and level-up. The preparatory work should be completed well before the PM contract. This study will identify the main flexible pavement repair types and investigate best practices for performing both in-house and contracted repairs. A procedure will be developed to determine the limits and type of flexible pavement repair. An evaluation process of the repair, including its performance and effects on the PM surfacing, will be developed.]]></description>
      <pubDate>Wed, 27 Sep 2023 14:06:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2255821</guid>
    </item>
    <item>
      <title>National Partnership to Improve the Quality of Pavement Preservation Treatment Construction &amp; Data Collection Practices (PG Phase III)</title>
      <link>https://rip.trb.org/View/2226003</link>
      <description><![CDATA[This pooled-fund study is being developed to assist state highway agencies (SHAs) and local public agencies (LPAs) in reviewing and developing pavement preventive maintenance (PM) treatments which can advance their pavement preservation programs. This study is also supplementing ongoing data analysis of existing pavement test sections in Minnesota (NRRA-MnROAD) and the National Center for Asphalt Technology (NCAT) in Alabama and support continued implementation activities established. Combining these efforts will establish a national construction and data collection effort of pavement PM treatments applied to roadways at the direction of the study’s Technical Advisory Committee (TAC). Participation in the study is being encouraged by SHAs, LPAs, the Federal Highway Administration (FHWA), Federal Lands Highway Division, academia and industry representatives. Collaboration with experts from these groups will help set criteria for identifying PM construction practices and data collection requirements, discuss optimal timing for placing of PM treatments and establishing the minimum number of pavement sections required for each type of PM treatment used for statistical analysis. Non-financial participants can provide technical knowledge and input; however, financial contributors will make final decision on treatments to be constructed.

Using the outcome from the above collaborative activities, the study partners will initiate and monitor State, local, and Federal PM treatments and projects to develop preventive maintenance solutions (i.e. decision trees, toolboxes, etc.). Implementation of practical research results from other PM cooperative projects (i.e. NCAT, MnROAD, NCPP) will be used to access the impact of preventive maintenance treatments on extending service life of pavements. Lessons learned will be documented and shared along with information to assist in the updating of the national pavement preservation research roadmap.]]></description>
      <pubDate>Tue, 08 Aug 2023 06:35:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2226003</guid>
    </item>
    <item>
      <title>Performance of Coatings Used for Preventive Maintenance</title>
      <link>https://rip.trb.org/View/2096566</link>
      <description><![CDATA[This project will study the performance of new advanced coatings used for preventive maintenance and condition-based preservation.]]></description>
      <pubDate>Fri, 13 Jan 2023 14:49:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2096566</guid>
    </item>
    <item>
      <title>Benefits of Preventive Maintenance</title>
      <link>https://rip.trb.org/View/1764316</link>
      <description><![CDATA[The objective of this research will be to quantify the impact and benefits of preventive maintenance treatments on pavements in Minnesota. Previous research studies have typically addressed decision-making frameworks for selection of preventive maintenance treatments, challenges in quantifying the value of preventive maintenance and cost of deferred maintenance, or best practices from other agencies in maintenance decision-making. Frameworks and decision trees that may be utilized for guiding project selections for preventive maintenance, or pavement rehabilitation or construction projects, typically assume the value of pavement treatments based on expert elicitation. Comprehensive data analysis to quantify the value of preventive maintenance in asset management research has been limited. However, quantifying preventive maintenance based on actual data is critical for transportation agencies to effectively use decision support tools that utilize parameters that estimate these benefits. The proposed research will gather and analyze data on treatment histories of Minnesota pavement sections, in conjunction with 
Minnesota Department of Transportation (MnDOT) historic pavement condition and pavement characteristics, to quantify the impact of preventive maintenance on increased pavement life, improved pavement condition measures, or increased intervals between treatment needs. Final anticipated research product will be a set of decision trees that will guide decision makers to make cost-effective decisions for preventive maintenance. The decision trees will be developed by considering life cycle costs through engineering economic analysis. The trees will incorporate the pavement treatment cost data, and the goal is that they will inform decision makers of the ideal timing and frequency of pavement treatments.]]></description>
      <pubDate>Tue, 19 Jan 2021 16:00:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/1764316</guid>
    </item>
    <item>
      <title>Bridge Low Slump Concrete Overlay Mix Design for Mobile Mixers</title>
      <link>https://rip.trb.org/View/1764271</link>
      <description><![CDATA[Low slump overlays are an important technique to extend the life of bridge decks. The mixture for low slump overlays has not changed in the last 30 years and shows extensive cracking within a few years of placement. The objective of this project is to minimize the cracking in low slump concrete overlays for mixtures placed with a volumetric mixer. These mixtures need to obtain a low permeability in the NT Build 492 and achieve a 28 day compressive strength of 4000 psi.
The objectives of the research include:
(i) Reviewing mixture designs and specifications from other states; 
(ii) Examining the most promising mixtures and documenting their performance; 
(iii) Implementing the most promising mixtures on a field project and documenting their performance]]></description>
      <pubDate>Tue, 19 Jan 2021 15:01:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/1764271</guid>
    </item>
    <item>
      <title>Enhancement of MDOT SHA Pavement Preservation Program </title>
      <link>https://rip.trb.org/View/1715421</link>
      <description><![CDATA[The Pavement and Geotechnical Division is faced with the challenge of maximizing funding and enhancing the Preventive Maintenance Program.  This research would provide a resource to help Maryland Department of Transportation State Highway Administration (MDOT SHA) enhance the current program.  It is intended to promote the implementation of several pavement preservation treatments in Maryland, provide for the development of strategies, documents and training to successfully expand and implement pavement preservation and new pavement technologies throughout all levels of MDOT SHA.  The following preservation treatments have been identified for the purposes of this study: crack fill & crack zeal (for both asphalt and concrete surfaces), joint zealing (and resealing), saw and seal, fog seal, rejuvenators, cape seal, chip seal, sand seal, thin overlays (ultra thin bonded wearing course, high performance thin overlays, etc.), unbonded and bonded PCC overlay, cross-stitching, undersealing/slab stabilization, surface abrasion, cold In-place asphalt recycling (CIR), rubblization and asphalt overlay, full-depth reclamation (FDR), high friction surface treatment.   Most of these treatments are relatively new and are either in the pilot phase or have been utilized. This research will focus on the following: (1) perform a comprehensive literature review of best practices and lessons learned from other transportation agencies; (2) research the availability of contractors for each treatment; (3) review the successful contract advertisement procedures for each treatment by reaching out to peers at other transportation agencies; (4) identify the lane-mile-year benefit of each treatment (both as-designed and as-built) at other transportation agencies; (5) review the criteria for placement of each treatment (ambient temperatures, pre-treatment operations, specification requirements, lane-mile-year benefit, advantages and disadvantages etc.); (6) identify challenges faced by transportation agencies to implement new treatments (i.e. push back/opposition from industry); (7) compile specifications using information from the FHWA resource library and other transportation agencies and evaluate the readiness of the specification for use by MDOT SHA;  (8) evaluate the level of utilization of each treatment at MDOT SHA relative to its use at other transportation agencies and determine if the treatment should be considered further; and (9) develop a shortlist of treatments that can be pursued by MDOT SHA, based on the findings from Steps 1-8 above.
]]></description>
      <pubDate>Fri, 19 Jun 2020 15:11:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/1715421</guid>
    </item>
    <item>
      <title>A Guide for Incorporating Maintenance Costs into a Transportation Asset Management Plan</title>
      <link>https://rip.trb.org/View/1628640</link>
      <description><![CDATA[The objective of this research is to develop a guide for state DOTs and other transportation agencies on incorporating maintenance costs in a risk-based Transportation Asset Management Plan (TAMP), including but not limited to the following: (1) a detailed presentation of procedures for identifying, collecting, and managing required data; (2) using life-cycle planning tools and techniques to demonstrate financial requirements and cost-effectiveness of maintenance activities and preservation programs and the potential change in costs and liabilities associated with deferring these actions; (3) formulating strategies that identify how to invest available funds over the next 10 years (as required by the TAMP) using life-cycle and benefit-cost analyses (and other applicable tools and techniques) to measure tradeoffs between capital and maintenance activities in alternative investment scenarios; and (4) designing components of a financial plan showing anticipated revenues and planned investments in capital and maintenance costs for the next 10 years.  ]]></description>
      <pubDate>Tue, 04 Jun 2019 16:24:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/1628640</guid>
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