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    <title>Research in Progress (RIP)</title>
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    <language>en-us</language>
    <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>Advancing AI Applications for Knowledge Discovery, Capture, And Delivery at State DOTs</title>
      <link>https://rip.trb.org/View/2712201</link>
      <description><![CDATA[State departments of transportation (DOTs) are facing a critical workforce transition as large numbers of experienced engineers, planners, maintenance managers, and technical experts approach retirement. This demographic shift threatens the loss of institutional and tacit knowledge that supports effective decision-making, project delivery, operations, and innovation. Existing knowledge-management approaches are often fragmented and insufficient for systematically capturing and transferring experiential knowledge across agencies.

At the same time, transportation agencies are becoming increasingly digital and data-driven, relying on technologies such as intelligent transportation systems, analytics, digital twins, and artificial intelligence (AI)-enabled tools. Advances in AI, particularly in Large Language Models (LLMs), semantic models, and Retrieval Augmented Generation (RAG), offer opportunities to improve knowledge discovery, synthesis, retrieval, and delivery within transportation agencies. AI applications such as chatbots, intelligent assistants, semantic search, and interactive knowledge exploration tools can help employees quickly locate technical standards, business processes, lessons learned, datasets, and expert guidance.

Several DOTs are independently piloting AI-based knowledge discovery and delivery (KDD) applications, but there is limited research on scalable, transferable frameworks that support knowledge capture, workforce onboarding, training, and enterprise-wide information access. There is also a need to address governance, data quality, privacy, interoperability, model transparency, and long-term maintenance of AI-enabled knowledge systems.

The objective of this research is to advance AI applications for knowledge discovery, capture, and delivery within state DOTs by developing a scalable transportation-specific LLM framework that captures, organizes, synthesizes, and disseminates institutional knowledge. The research will assess current AI-based KDD practices; identify promising applications and use cases; develop standardized protocols for data ingestion, annotation, and evaluation; and establish governance frameworks for responsible AI deployment.]]></description>
      <pubDate>Wed, 10 Jun 2026 11:08:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712201</guid>
    </item>
    <item>
      <title>Making Knowledge Management Work for DOTs: A Guide to Fostering Collaboration, Learning and Adaptation</title>
      <link>https://rip.trb.org/View/2712194</link>
      <description><![CDATA[Knowledge management (KM) is growing among state departments of transportation (DOTs), and culture is an essential ingredient of KM. Agencies must value and support learning; otherwise, employees are not likely to share what they know or invest the time needed for effective collaboration. Previous National Cooperative Highway Research Program (NCHRP) studies on innovation and learning cultures have identified several factors that are conducive to a learning culture. These studies have acknowledged the importance of culture but have not explored it in detail. There is a need to build on prior research dealing with KM and innovation in transportation agencies, along with foundational studies of learning cultures, and exploring the intersection of KM, learning cultures, and organizational change at DOTs.

This objective of this research is to develop a guide for state DOTs to strengthen organizational cultures that foster collaboration, learning, and adaptability. ]]></description>
      <pubDate>Tue, 09 Jun 2026 17:13:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712194</guid>
    </item>
    <item>
      <title>Supervisor's Handbook</title>
      <link>https://rip.trb.org/View/2701239</link>
      <description><![CDATA[Supervisors at the State Highway Administration (SHA) play an essential role in ensuring the continuity and effectiveness of daily operations. They enforce policies, mentor staff, evaluate performance, and uphold compliance with safety and procedural standards. Despite their critical responsibilities, many supervisors operate without a centralized, reliable, and up-to-date knowledge resource. Instead, they depend on fragmented intranet pages, institutional memory, email threads, and informal peer networks. This
patchwork approach often leads to inefficiencies, inconsistent interpretations, and frustration among staff. Because there is no robust process for curating, linking, and maintaining policy knowledge, supervisors spend valuable time searching through repositories or verifying outdated manuals. Decisions become inconsistent, fairness and compliance are compromised, and confidence in institutional processes weakens.
Over time, these inefficiencies not only hinder operational performance but also erode supervisors’ ability to coach and support their teams effectively. Despite the critical role supervisors play, SHA lacks a unified, authoritative, and maintainable knowledge
system to support them. Existing resources are fragmented, outdated, and inconsistently connected, leading to misinterpretation, wasted effort, and diminished trust. Supervisors often must interpret policy on their own, resulting in variations in implementation and uncertainty about compliance. The absence of a structured, well-maintained knowledge system represents a systemic challenge for SHA—one that undermines efficiency, workforce engagement, and institutional learning. Lack of compliance and proper
employee management also places the organization at risk for litigation. i.e., mismanaged employee performance issues expose SHA to litigation risk. Supervisors lack central and authoritative knowledge resources. Current resources are fragmented, outdated, and inconsistently applied leading to policy misinterpretation, inefficiency, and diminished trust. A structured, maintainable system is critical to ensure consistent implementation, reduce legal exposure, and strengthen workforce engagement and organizational success. National workforce research underscores the urgency of addressing these challenges. According to the 2025 Retention Report, 75% of employee departures are considered preventable, with management and communication deficiencies among the leading causes (Work Institute, 2025). Similarly, the 2025 SHRM State of the Workplace Report finds that nearly half of turnover intent is linked to weak engagement and workplace culture, with organizations that invest in management capacity achieving markedly higher retention (SHRM, 2025). For SHA operating under tight budgets, stringent regulations, and increasing workloads, the cost of fragmented knowledge is not merely administrative—it affects workforce stability, operational consistency, and public trust. To address this gap, this research proposes a structured knowledge management architecture grounded in Garfield’s (2022) knowledge management principles. The Curate → Connect → Cultivate (C3) framework translates these principles into an actionable model tailored for supervisory environments within SHA. It envisions a digital ecosystem that curates authoritative resources, connects users through accessible pathways, and cultivates continuous learning and collaboration. The following section introduces the framework and its three integrated phases, illustrating how each supports a more coherent and resilient
supervisory knowledge system. 
● Curate: the systematic gathering, validation, structuring, and versioning of policy and procedural
knowledge
● Connect: enabling supervisors to find, navigate, and relate to relevant content via search,
recommendations, linking, and social features
● Cultivate: establishing governance processes, review cycles, feedback loops, and incentives to
keep the system current, trusted, and sustainable

By mapping each stage to the known pain points in SHA supervisory practice, this framework guides both the design and evaluation of a “Supervisor’s Knowledge Hub.” The research will prototype, deploy, and assess features corresponding to each stage, measuring outcomes such as time to find authoritative guidance, user satisfaction, accuracy of interpretations, and frequency of contributions. For the purposes of
this study, supervisory competencies emphasize people leadership, team management, communication, performance feedback, and consistent policy application across SHA rather than technical engineering or design skills.]]></description>
      <pubDate>Wed, 13 May 2026 09:22:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/2701239</guid>
    </item>
    <item>
      <title>Strategies to Foster the Implementation of Knowledge Management</title>
      <link>https://rip.trb.org/View/2689398</link>
      <description><![CDATA[State departments of transportation (DOTs) began to explore knowledge management (KM) in the early 2000s. Since then, several state DOTs and U.S. DOT administrations have implemented KM activities and programs. The transportation community has conducted several research projects that examined how other industries have adopted and implemented KM. Also, NCHRP and others have published reports on the value of KM, including NCHRP Report 813, A Guide to Agency-Wide Knowledge Management for State Departments of Transportation (https://www.trb.org/Publications/Blurbs/173082.aspx).  

Despite substantial research on the use of KM in transportation, loss of institutional knowledge due to retirements and turnover, and other workforce changes, state DOTs have not widely adopted formal KM practices. Some state DOTs are trying to develop KM practices to capture this institutional knowledge quickly but need more resources and strategies for KM implementation. 

Research is needed to document the evolution of KM stewardship at state DOTs and insights into their successes and challenges in adopting and implementing KM. Strategies are needed to help state DOTs foster KM investment, development, and sustainability.

 OBJECTIVE: The objective of this research is to provide strategies and proven approaches to foster KM investment, development, and sustainability. The research shall, at minimum, (1) include a summary of the evolution of KM stewardship at state DOTs, and (2) identify and analyze successes and challenges state DOTs have encountered in adopting and implementing sustained KM programs.]]></description>
      <pubDate>Mon, 06 Apr 2026 18:33:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2689398</guid>
    </item>
    <item>
      <title>Developing a Roadmap for Ultra-High Performance Concrete (UHPC)</title>
      <link>https://rip.trb.org/View/2684169</link>
      <description><![CDATA[The objectives of this pooled fund study are to: (1) Facilitate communication and information sharing among member states on the project topic, as well as with participants of the Fourth International Interactive Symposium on Ultra High Performance Concrete (UHPC). (2) Establish a forum for technology and knowledge exchange to enhance the practical understanding of UHPC implementation among member states. (3) Develop a strategic roadmap for future UHPC use and advancements, including the identification of research needs and the formulation of research ideas to be pursued through NCHRP, Pooled Funds, grants and other funding mechanisms.

The anticipated benefits of this pooled fund are: (1) Minimized disruption to the traveling public by reducing the frequency and duration of bridge deck repairs. (2) Lower maintenance costs resulting from the enhanced durability and performance of UHPC wearing surfaces. (3) Improved worker safety through reduced exposure to on-site repair activities due to less frequent maintenance needs.

The participating state departments of transportation (DOTs) will provide input throughout the project and benefit from shared insights into technologies used to date, as well as lessons learned from past projects across various regions. Additionally, they will gain exposure to the latest advancements to be presented at the Fourth International Interactive Symposium on UHPC, which will cover topics including UHPC material innovations, recent applications, and the long-term performance of UHPC-designed structures. Pooled fund participants will attend the symposium free of charge.


]]></description>
      <pubDate>Thu, 26 Mar 2026 14:07:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684169</guid>
    </item>
    <item>
      <title>Successful Approaches to Integrating Artificial Intelligence (AI) Into Knowledge Management</title>
      <link>https://rip.trb.org/View/2681237</link>
      <description><![CDATA[As state Departments of Transportation (DOTs) and other transportation agencies expand their knowledge management (KM) programs, interest in incorporating artificial intelligence (AI) is increasing. Agencies are exploring how AI-enabled tools can support knowledge capture, organization, retrieval, and application.

This scan will examine current practices used by state DOTs and other organizations to implement AI in knowledge management. It will identify opportunities as well as common challenges, including data quality, security, governance, and ethical considerations. Careful and responsible integration of AI is essential to ensure effective and sustainable use within KM programs.]]></description>
      <pubDate>Tue, 17 Mar 2026 15:12:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2681237</guid>
    </item>
    <item>
      <title>Synthesis: Assess Transportation Agency Approaches to Training and Developing Hydrology and Hydraulics (H&amp;H) Staff</title>
      <link>https://rip.trb.org/View/2593192</link>
      <description><![CDATA[There is presently significant understaffing and turnover of staff specializing in Hydrology and Hydraulics (H&H) within agencies overseeing transportation infrastructure. H&H is a specialized field that requires unique training; however, given the understaffing and turnover, it is challenging to retain industry-specific knowledge in the absence of standardized training resources. To improve the training of H&H roles within transportation agencies, the research team will follow a systematic approach that (1) determines what training resources are being utilized, (2) determines which H&H training topics transportation agencies prioritize, (3) determines how specific needs of the DOT are assessed to support the development of training curricula, (4) determines how training is being delivered, (5) determines which technological innovations have been leveraged to improve training outcomes, (6) determines which topics are being taught, (7) determines whether states create their own training content or rely primarily on national resources, (8) determines whether transportation agencies are grappling with any specific gaps in H&H training resources, (9) determines how training is evaluated and implemented to improve efficacy, including the frequency of revisions, and (10) determines what approaches are utilized to transfer knowledge from seasoned staff to newer staff. Surveys and interviews will be conducted with relevant agencies throughout Texas and in other states to provide a comprehensive dataset on present practices and shortcomings. The research team will evaluate these findings in terms of the desired needs of H&H positions, in the context of transportation infrastructure and typical H&H training in engineering roles. The synthesis developed by the research team will be used as a guide to inform what resources are available to be maintained, leveraged, and/or refined to improve the depth and consistency of H&H training within transportation.]]></description>
      <pubDate>Tue, 26 Aug 2025 12:45:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/2593192</guid>
    </item>
    <item>
      <title>A Guide for Holistic Information and Knowledge Management



</title>
      <link>https://rip.trb.org/View/2558404</link>
      <description><![CDATA[As state departments of transportation (DOTs) generate and manage increasing amounts of data and undergo digital transformation, the importance of cohesively managing these data as an asset has grown. For example, most state DOTs have their data, email, web content, engineering content, and records managed within separate units or locations. Information management becomes even more fragmented within individual business units, where specialized applications support specific processes and units may pursue integration and accessibility in isolation. 

This limited coordination creates multiple repositories with different search interfaces, access requirements, and use restrictions, which lead to further data duplication and quality issues. These issues, in turn, make it difficult for employees to find what they need, affecting their proficiency, decision-making, and the timely performance of their jobs. Stakeholder outreach activities conducted as part of NCHRP Project 23-14, “Research Roadmap for Knowledge Management” and described in NCHRP Research Report 1134: Knowledge Management at State Departments of Transportation highlighted state DOTs’ concerns about fragmentation of information, data, and knowledge at their agencies. Research is needed to provide guidelines on holistic approaches to managing these resources. 

OBJECTIVE: The objective of this research is to develop a guide on holistic information and knowledge management (IKM) that (1) provides methods for how state DOTs can align, coordinate, and execute practices for managing and governing information, data, and knowledge; (2) identifies key risks, opportunities, and challenges and how to address them; and (3) conveys the benefits gained from implementing successful IKM practices identified in the research. 

]]></description>
      <pubDate>Wed, 28 May 2025 09:45:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/2558404</guid>
    </item>
    <item>
      <title>Project Cohorts</title>
      <link>https://rip.trb.org/View/2553661</link>
      <description><![CDATA[The objective of this project is to review the 151 projects that are ongoing or recently completed to categorize each into research topics (buckets) to increase agility in sorting and reporting on strategic topic areas, themes, and investments. This will include a focus on enabling useful gap analyses and improving knowledge management.]]></description>
      <pubDate>Wed, 14 May 2025 13:29:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/2553661</guid>
    </item>
    <item>
      <title>AI and Immersive AR/VR for Sustained Material and Construction Inspection Training and Knowledge Retention</title>
      <link>https://rip.trb.org/View/2507233</link>
      <description><![CDATA[This project leverages advancements in Large Language Models (LLMs), such as OpenAI’s ChatGPT, which can interpret and generate human-like responses using extensive data. LLMs have demonstrated proven capabilities in related areas, such as contextual knowledge retrieval, interactive training, and generating domain-specific insights, making them highly suitable for addressing challenges associated with inspection training and knowledge retention. Building on these capabilities, the research team proposes the development of InspectionGPT, a specialized LLM tailored for inspection training. The system will consist of two key components: the InspectionGPT chatbot and a 3D VR training environment. InspectionGPT chatbot will be developed using existing foundation LLM models, such as LLaMA, GPT-4, Falcon, and BLOOM. These models will be trained with NDOT’s inspection guidelines, standards, reports, and past training materials stored in NDOT’s local repository(called knowledge base). Once trained, InspectionGPT chatbot will provide personalized guidance and dynamic learning experiences to trainees, communicating in English. The system also allows for easy updates as new knowledge can be added simply by storing relevant documents and descriptions in the knowledge base. A central feature of the system is the GPT Protocol, a plain-English document that defines how InspectionGPT should respond to user requests. This protocol enables NDOT to adjust and customize InspectionGPT’s behavior without any programming expertise, ensuring the system is flexible, user- friendly, and easy to maintain.]]></description>
      <pubDate>Mon, 10 Feb 2025 11:02:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2507233</guid>
    </item>
    <item>
      <title>An Introduction to Knowledge Management and Workforce Issues for CEOs: A CEO Leadership Workshop</title>
      <link>https://rip.trb.org/View/2437878</link>
      <description><![CDATA[N/A]]></description>
      <pubDate>Tue, 08 Oct 2024 15:04:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2437878</guid>
    </item>
    <item>
      <title>Building a Construction Inspection Toolkit</title>
      <link>https://rip.trb.org/View/2417069</link>
      <description><![CDATA[Kentucky Transportation Cabinet's (KYTC’s) construction program has an annual budget that exceeds $1 billion. Section Engineers assume considerable responsibility for delivering this program by spearheading management and inspection services. However, the loss of senior personnel and a contracting workforce have increased the challenge of streamlining processes needed to deliver projects on time and on budget. Knowledge gaps created by the departure of experienced staff must be filled to shore up the construction program’s resiliency and efficiency. To fill knowledge gaps, KYTC must develop inspection resources and best practices documents that Section Engineers, project inspectors, and consultant inspectors can review to work through field inspection requirements. Making inspection workflows accessible via mobile devices will give in-house and consultant construction inspectors easy access to resources they need to perform effective inspections.]]></description>
      <pubDate>Mon, 12 Aug 2024 13:26:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/2417069</guid>
    </item>
    <item>
      <title>Ahead of the Curve - Migration from NCHRP to AASHTO Technical Training Solutions (TTS)</title>
      <link>https://rip.trb.org/View/2397882</link>
      <description><![CDATA[In 2011, raising the profile and stature of transportation research became a major theme during meetings of the Transportation Research Board (TRB) Technical Activities Council, the TRB standing committees on Conduct of Research and Technology Transfer, and the summer meeting of the American Assocation of State Highway and Transportation Officials (AASHTO) Research Advisory Committee (RAC) and TRB state representatives. It quickly became established that a standardization of transportation research management was needed.  

Discussions among TRB staff and volunteers led to recommend a program that in 2012 that came to be known as “Ahead of the Curve (AOTC) Mastering the Management of Transportation Research and Innovation.”  

The mission of the initiative was ‘to develop and deliver a TRB program that enhances the knowledge, skills and abilities of managers of transportation research programs and those responsible for innovation in a coordinated manner and on a continuing basis.  An article in the January-February 2020 issue of TR News describes the evolution and benefits of this program.

The AOTC Program is comprised of four required core courses that are built upon the research cycle and twelve more subject detailed electives presented through webinar format. Below is a list of the required core courses and descriptions:  1) Making Research Relevant; 2) Running a Research Program; 3) Delivering the Program; 4) Quality Improvement.

OBJECTIVES: The primary objectives of this pooled fund study are as follows: Transfer AOTC information from NCHRP to AASHTO; Update and transfer existing information into AASHTO Technical Training Solutions (TTS) format; Make all courses 508 compliant.]]></description>
      <pubDate>Wed, 26 Jun 2024 09:49:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2397882</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Highway Practices. Topic 56-01. Occupational Safety Training and Knowledge Transfer Practices for State DOT Employees



</title>
      <link>https://rip.trb.org/View/2384690</link>
      <description><![CDATA[Safety training and knowledge transfer practices are important tools for state DOT employees to identify workplace hazards, increase department-wide risk awareness, and develop strategies to eliminate or mitigate risk. A wide range of occupational and workplace hazards exist for all employees within state DOTs. Safety training programs and knowledge transfer strategies increase hazard recognition to improve employee health and safety. Industry driven safety practices and regulations require specific training for workers and supervisors to address workplace safety.

OBJECTIVE: The objective of this synthesis is to document state DOT practices regarding safety training programs and knowledge transfer.]]></description>
      <pubDate>Tue, 28 May 2024 16:36:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/2384690</guid>
    </item>
    <item>
      <title>Anticipatory Knowledge Delivery for Transportation Agencies</title>
      <link>https://rip.trb.org/View/2381736</link>
      <description><![CDATA[Anticipatory knowledge (AK) refers to knowledge that is proactively generated, identified, or made available in advance of a need or event. AK delivery focuses on the mechanisms and processes through which AK gets to the right people at the right time. The goal of AK and AK delivery is to prepare individuals or organizations to respond effectively to future scenarios by leveraging systems to provide relevant information to them. An AK delivery system can provide targeted guidance to employees based on their roles; prompted by career milestones such as onboarding or assignment of first project management; and necessitated by unforeseen events such as passage of new legislation, economic changes, or natural disasters. The AK delivery concept is of great interest to state departments of transportation (DOTs) and other transportation agencies; however, AK delivery has not yet been widely explored or adopted by these agencies. 

Transportation agencies are seeking a guide on how to anticipate what employees need to know at different points in time and deliver that information in an automated, convenient, coordinated, and efficient manner. Research is needed to (1) identify types and sources of information required for a set of agency roles, career milestones, unforeseen events, or business processes and (2) create frameworks that could be used by transportation agencies to implement an AK delivery system. 

OBJECTIVE: The objective of this project is to develop a guide for transportation agencies on creating, implementing, and integrating AK delivery into existing agency systems. AK delivery will provide employees with relevant, role-specific information that enhances decision-making and helps them perform their duties more efficiently and effectively. 

]]></description>
      <pubDate>Wed, 22 May 2024 11:35:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2381736</guid>
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