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    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJzdWJqZWN0aWQiIHZhbHVlPSIxNzk4IiAvPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSI3MzAiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMTYiIC8+PC9wYXJhbXM+PGZpbHRlcnMgLz48cmFuZ2VzIC8+PHNvcnRzPjxzb3J0IGZpZWxkPSJwdWJsaXNoZWQiIG9yZGVyPSJkZXNjIiAvPjwvc29ydHM+PHBlcnNpc3RzPjxwZXJzaXN0IG5hbWU9InJhbmdldHlwZSIgdmFsdWU9InB1Ymxpc2hlZGRhdGUiIC8+PC9wZXJzaXN0cz48L3NlYXJjaD4=" rel="self" type="application/rss+xml" />
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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>Preparing the Airport Workforce for Emerging Technologies and Data-Informed Decision Making</title>
      <link>https://rip.trb.org/View/2772531</link>
      <description><![CDATA[Airports are operating in an increasingly complex environment driven by rapid technological change, expanding data availability, evolving safety expectations, and growing operational demands. At the same time, airports continue to face workforce challenges, including retirements, competition for skilled labor, recruitment and retention issues, and the loss of institutional knowledge. Although airports collect increasing amounts of workforce and operational data, these data often remain fragmented across separate systems, limiting their ability to align workforce capabilities and staffing decisions with operational needs and the adoption of emerging technologies.

The objective of this research is to develop practical guidance, tools, and implementation resources that help airports modernize workforce development while improving data-informed workforce decision-making. The research will produce an airport workforce framework, role-based training pathways, guidance for integrating workforce and operational data, and implementation resources that airports of varying size and complexity can use to strengthen workforce capabilities, support staffing and operational decisions, and complement existing workforce research while minimizing duplication.]]></description>
      <pubDate>Tue, 01 Sep 2026 10:02:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2772531</guid>
    </item>
    <item>
      <title>Safety Academy Phase II: Refinement, Deployment Planning, and Evaluation</title>
      <link>https://rip.trb.org/View/2768422</link>
      <description><![CDATA[Researchers previously developed a Safety Academy that addresses inconsistencies in safety knowledge across Kentucky Transportation Cabinet (KYTC) Districts as well as the disconnect between mid-level management and the employee safety and health program. Course modules have been piloted, however, early deliveries of the training revealed aspects of the curriculum that need refinement before agencywide deployment. Currently, KYTC lacks a structured deployment plan and the internal capacity to sustain the Safety Academy long term. Addition-ally, an evaluation framework should be developed to measure the academy's effectiveness in improving safety knowledge, managerial engagement, and workplace safety outcomes.]]></description>
      <pubDate>Wed, 26 Aug 2026 17:04:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2768422</guid>
    </item>
    <item>
      <title>Development of Bridge Preventive Maintenance Training</title>
      <link>https://rip.trb.org/View/2768416</link>
      <description><![CDATA[On suburban and urban roadways, recurring traffic congestion increases delays, makes travel times unreliable, and results in more crashes. Traditional capacity improvement projects involving roadway widening or bypasses may take several years to design, fund, and build, and in the long?term may increase travel demand for the corridor. The Georgia Department of Transportation (GDOT) has begun a highly successful Operational Improvement Program to rapidly identify and address these needs. The program looks for quick fix solutions with lower costs (typically less than $1 million), such as turn lane extensions, minor ITS deployments, and restriping. Projects are sought which have near?term implementation schedules of less than one year.]]></description>
      <pubDate>Wed, 26 Aug 2026 17:04:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/2768416</guid>
    </item>
    <item>
      <title>Improve the Approach to Measuring Highway Criticality</title>
      <link>https://rip.trb.org/View/2768415</link>
      <description><![CDATA[Preventive maintenance is critical for extending bridge service lives, reducing life cycle costs, and improving bridge performance. Kentucky Transportation Cabinet (KTC) researchers have identified preventive maintenance activities that should be prioritized and which require improved consistency, documentation, and workforce training across Kentucky. While technical guidance describing how to perform these activities is available, a clear need exists for a structured, hands-on training that presents this information in a uniform manner. KTC’s Technology Transfer (T2) Program specializes in proven techniques for conducting applied transportation training. Coordinating the development and delivery of bridge preventive maintenance training through T2 will promote effective knowledge transfer and long-term adoption of best practices by KYTC and local agency personnel.]]></description>
      <pubDate>Wed, 26 Aug 2026 17:04:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/2768415</guid>
    </item>
    <item>
      <title> 
Research Experience for Undergraduates (REU): Smart Cities Supplement Summer 2027
</title>
      <link>https://rip.trb.org/View/2762047</link>
      <description><![CDATA[Since 2020, the University of Nevada, Las Vegas (UNLV) has hosted an NSF Research Experiences for Undergraduates (REU) Site on Smart Cities focused on advanced mobility technologies, including Intelligent Transportation Systems (ITS), Connected and Automated Vehicles (CAVs), and vehicle-to-everything (V2X) communication. The program attracts more than 100 applicants annually and has trained over 45 students, producing more than one peer-reviewed publication per summer. This project supplements the existing site to support two additional undergraduate researchers working on Research and Education for Promoting Safety University Transportation Center (REPS UTC) safety-related projects.
The project will recruit two undergraduate students from relevant disciplines (electrical and computer engineering, civil engineering, computer science), with emphasis on outreach to institutions with varied student populations. Selected students will complete a ten-week summer research experience under faculty mentorship across the ITS, CAV, and V2X focus areas, complemented by co-curricular training including weekly cohort meetings, enrichment activities, and cohort-building. Key tasks include developing compelling safety research projects with UNLV mentors, national advertising and recruitment, candidate evaluation and selection, mentored summer research, and final reporting through the UNLV Undergraduate Research Symposium and academic publication venues.
Expected outcomes include expanded undergraduate participation in transportation safety research, student projects aligned with REPS UTC initiatives, student reports, presentations, and potential peer-reviewed publications. The project strengthens the pipeline of future transportation professionals and UNLV's research infrastructure in traffic safety, helping develop the next generation of researchers and practitioners equipped to address emerging safety challenges in transportation systems.
]]></description>
      <pubDate>Wed, 19 Aug 2026 15:59:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2762047</guid>
    </item>
    <item>
      <title>Workers as Co-designers of Workforce Development: Lessons for Transit Workforce Planning</title>
      <link>https://rip.trb.org/View/2761610</link>
      <description><![CDATA[This project documents and shares insights from a comparative study of workforce co-design initiatives in other regions. The main objective is to enhance hiring, retention, and leadership promotion within job areas and positions at regional transit agencies that are currently the hardest to staff and keep full. The research is designed to assist regional transit agencies in determining where there is the greatest potential for worker-informed co-design processes to make an impact on hiring and retention, and to support implementation of high-impact processes within regional transit organizations and partner organizations contracted for workforce hiring.

Co-design efforts recognize that current and prospective workers hold the key to unlocking access to new generations of workers because of their lived experience, cultural and social connections, and career awareness. Their involvement is helping to elevate public organizations and their hiring partners as "employers of choice," ensuring more diverse populations recognize and benefit from the quality of the jobs and career opportunities being offered. Equally, by giving workers a voice in workforce development design, these organizations amplify the dignity of work, ensuring employees gain a greater sense of purpose and meaning from their daily work and thus feel empowered to improve the work lives of others. ]]></description>
      <pubDate>Mon, 17 Aug 2026 10:49:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/2761610</guid>
    </item>
    <item>
      <title>Development and Evaluation of a Large Language Model and Virtual Reality Framework for Improving Flagger Training
</title>
      <link>https://rip.trb.org/View/2739298</link>
      <description><![CDATA[Flaggers are essential for maintaining traffic safety in work zones, serving as human traffic controllers who coordinate alternating traffic through the work zone, yet they work under extremely hazardous conditions in close proximity to high-speed traffic and heavy equipment. Traditional classroom-based training is often insufficient for developing situational awareness, hazard recognition, and communication skills, while real-world training exposes trainees to significant risk. Virtual reality (VR) offers immersive, hands-on practice without danger, but current VR systems rely on preprogrammed scenarios and require instructors to manually identify trainee errors.

This project develops a large language model (LLM)-based virtual flagger that provides dynamic, realistic interactions within a VR training environment rather than rigid, pre-scripted scenarios. The virtual flagger engages in natural radio communication, responds contextually to trainees’ actions, asks clarifying questions when communication is unclear, and adapts its behavior to create diverse, progressively challenging training experiences.

]]></description>
      <pubDate>Thu, 30 Jul 2026 16:26:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/2739298</guid>
    </item>
    <item>
      <title>Mississippi Summer Transportation Institute- 2027</title>
      <link>https://rip.trb.org/View/2732467</link>
      <description><![CDATA[The Mississippi Summer Transportation Institute (MSTI) Program aims at introducing a group of motivated pre-college students (9th to 12th grade) to the transportation industry. During the two-week program, students will participate in academic and enhancement activities designed to improve their skills in Science, Technology, Engineering, and Mathematics (STEM) and leadership.]]></description>
      <pubDate>Tue, 21 Jul 2026 16:46:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2732467</guid>
    </item>
    <item>
      <title>Flood-resilient Transport System Through Integrated Modeling, ML &amp; Immersive AR/VR </title>
      <link>https://rip.trb.org/View/2732359</link>
      <description><![CDATA[Extreme rainfall events increasingly disrupt urban transportation systems by overwhelming drainage infrastructure and causing localized road flooding that impedes last-mile freight delivery, delays emergency response, and disrupts the broader multimodal supply chain. These disruptions limit access to essential services, delay emergency response, and threaten public safety. Building on the research team's previously developed framework (F25-26), this project advances a data-driven approach for high-resolution prediction of urban road flooding in Jackson, Mississippi, integrating geospatial databases, process-based H-H modeling (aligning with rigorous U.S. Army ERDC methodologies), and machine learning (ML) and artificial intelligence (AI) techniques to identify flood-prone road and railway segments. The ML-based surrogate models will maintain computational efficiency, enable timely identification of vulnerable transportation networks, and support emergency response by feeding into JSU Water Lab’s broader web-based-visualization interfaces. This project introduces an interactive K–12 STEM module, age-appropriate hands-on activities along with STEM curriculum module designed for upper-level Civil Engineering undergraduate and graduate students at JSU. This initiative transforms research outcomes into the classroom to modernize workforce training using integrated Augmented Reality (AR) and Virtual Reality (VR) and will be tested with summer student exchange programs. Students can explore and 3D print several transportation infrastructure components, such as culverts, bridges, and urban drainage systems, and evaluate their performance under simulated flood conditions, and experience AR/VR based immersive simulators. Using AR/VR tools, including the Meta Quest platform, available in the PI lab, future transportation engineers will visualize flood scenarios in immersive 3D environments built from existing topographical assets in Unity or Unreal Engine. By combining advanced predictive modeling with experiential learning, the project promotes advanced STEM engagement, and high-tech workforce development, aligning with broader goals of improving multimodal transportation system resilience. While the primary focus is on urban road and rail flooding, these transportation corridors serve as critical connectors to Mississippi's inland waterway freight network, including facilities linked to the Pearl River system and regional multimodal freight movements. Roadway disruptions during extreme rainfall events can delay freight access to ports, intermodal terminals, water-dependent industrial facilities, and affect supply-chain resilience. By identifying flood-vulnerable roadway and railway segments, the proposed framework will support more reliable connectivity between surface transportation infrastructure and maritime freight operations]]></description>
      <pubDate>Tue, 21 Jul 2026 16:34:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2732359</guid>
    </item>
    <item>
      <title>Community Response Enhanced Education on Disasters (CREED): Virtual Reality Training to Enhance Transportation</title>
      <link>https://rip.trb.org/View/2732358</link>
      <description><![CDATA[Artificial Intelligence/Virtual Reality (AI/VR) simulation activities enhance critical emergency management functions—planning, forecasting, threat detection, security, and information sharing—ultimately improving the preservation of life and property. These tools create a safe, immersive environment where participants build problem-solving skills, decision-making ability, and confidence in disaster response. This project will deliver education, professional development, and continuous improvement in emergency preparedness for both aspiring and current professionals. The research team will invite high school and community college students to participate alongside university students and practitioners. Participants will engage in hands-on training and live demonstrations using advanced technologies such as virtual reality (VR) and artificial intelligence (AI)-driven simulations. The program fosters multidisciplinary collaboration among disciplines: Emergency Management Technology, Meteorology, Computer Science/Engineering, Health Science, and Journalism, and Media Studies. Through classroom instruction, workshops, and interactive training demos, students will work directly with emergency management professionals, strengthening real-world skills, supporting school-to-work transitions, and enhancing career readiness.]]></description>
      <pubDate>Tue, 21 Jul 2026 16:29:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2732358</guid>
    </item>
    <item>
      <title>Enhanced Understanding of Geotechnical Processes</title>
      <link>https://rip.trb.org/View/2731975</link>
      <description><![CDATA[There is a need for a multidisciplinary hub for advancing geotechnical engineering practices in support of Michigan’s surface
transportation infrastructure. In alignment with the objectives outlined by the Michigan Department of Transportation (MDOT), the
Center will engage in a comprehensive suite of activities, including but not limited to education and workforce development, public
and stakeholder outreach, applied and theoretical research, implementation of innovative technologies, laboratory and field testing,
analytical modeling, and investigative services. These efforts will be guided by MDOT’s strategic priorities and may be further refined
through specific tasks detailed in this Scope of Services. The overarching goal of this center is to function as a responsive and
collaborative resource for MDOT by facilitating in the development, evaluation, and deployment of novel geotechnical solutions that
enhance the safety, durability, and sustainability of Michigan’s transportation systems. This can be done by fostering innovation and
continuous improvement in geotechnical engineering. The Center aims to bridge the gap between research and practice, ensuring
that emerging technologies and methodologies are effectively translated into real-world applications that benefit the traveling public
and support the long-term stewardship of the state’s infrastructure assets.]]></description>
      <pubDate>Fri, 17 Jul 2026 15:11:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/2731975</guid>
    </item>
    <item>
      <title>Update Standardized Measurement Systems and Laboratory Test Procedures to Improve Motorist Safety</title>
      <link>https://rip.trb.org/View/2727316</link>
      <description><![CDATA[The growth in construction and maintenance activities throughout the state has prompted an increase in the throughput for standardized measurements, laboratory tests, and similar processes performed by TxDOT on a routine basis. TxDOT, as well as its affiliated stakeholders, must meet this increased demand with a limited availability of trained workforce while ensuring high quality and consistent work products. While many of these processes have been developed and used for several decades, recent advances in technologies such as sensors, computing, logic controllers, machine vision, and actuators have now made it feasible to fully or partially automate several of the existing processes or, where feasible, replace some archaic processes with modern advanced and automated methods. The research teams will conduct one or more scouting tours of divisions and districts to create an inventory of processes and identify their potential to be automated. The research teams will use a scoring system with input from TxDOT to prioritize processes that can be partially or fully automated and benefit TxDOT. The research teams will develop, validate, and facilitate implementation of selected solutions with appropriate workflow integration and training of TxDOT’s personnel.]]></description>
      <pubDate>Fri, 10 Jul 2026 14:52:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2727316</guid>
    </item>
    <item>
      <title>2026 Employee Survey 
</title>
      <link>https://rip.trb.org/View/2719330</link>
      <description><![CDATA[The primary objectives are assist with the review and update of 2026 employee survey, review and select methods of survey implementation, conduct survey, analyze the survey results, assist in presentation of survey results to Georgia Department of Transportation (GDOT) Division and District Offices, and develop executive summaries and survey findings reports.
]]></description>
      <pubDate>Thu, 25 Jun 2026 13:01:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/2719330</guid>
    </item>
    <item>
      <title>Evaluation of Surveying Workforce Needs to Support Highway Construction</title>
      <link>https://rip.trb.org/View/2712197</link>
      <description><![CDATA[The U.S. surveying and geomatics profession is a multidisciplinary field requiring extensive knowledge of math, science, and geography. Civil engineering curricula may provide only limited exposure to surveying and geographic information systems (GIS), which may contribute to the growing shortage of the technical talent needed for delivering accurate and timely survey data. This challenge is further compounded across all education levels with limited enrollment in existing geomatics programs and limited availability of geomatics and geospatial technology courses, even as the use of geospatial information through digital devices continues to increase.

In addition to the intellectual and technical considerations associated with effectively utilizing geospatial data, several factors can influence its broader adoption and application. One key consideration is the learning investment needed to fully leverage geospatial datasets while adapting to this evolving field to maintain proficiency. Furthermore, recent studies have highlighted growing workforce demand in geomatics engineering and related disciplines nationwide. Therefore, research is needed to identify and assess the current surveying workforce status and needs for supporting highway construction.

The objective of this research is to help state departments of transportation (DOTs) to: (1)       Identify the educational and knowledge gaps contributing to workforce shortages, (2)      Develop data-driven fundamentals for workforce planning, program development, and recruitment investments, and (3) Develop strategies to prepare for emerging technologies and future needs in highway construction and digital project delivery.]]></description>
      <pubDate>Tue, 09 Jun 2026 17:38:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712197</guid>
    </item>
    <item>
      <title>Developing Data Literacy Competencies and Practices for State Transportation Workforce</title>
      <link>https://rip.trb.org/View/2712190</link>
      <description><![CDATA[State departments of transportation (DOTs) are undergoing a major transformation in how they collect, manage, and use data. Historically reliant on manual observations and field reports, DOTs now collect large and diverse datasets from traffic monitoring, asset condition assessments, maintenance records, freight compliance, Global Positioning System (GPS) probe data, light detection and ranging (LiDAR), drones, and video analytics. These technologies support more data-driven decisions related to infrastructure management, operations, and planning.

The growing volume and diversity of transportation data have created significant challenges for integration, governance, and analysis. To address these issues, many DOTs are adopting standardized data formats and centralized governance structures that improve interoperability, reduce duplication, and support collaboration with external stakeholders. At the same time, data access has expanded across agencies, allowing planners, engineers, managers, and policy staff to work directly with increasingly complex datasets.

Artificial intelligence (AI) and machine learning applications are accelerating this shift, particularly in areas such as traffic incident detection, pavement performance prediction, asset management, and safety analysis. However, many transportation professionals lack foundational competencies in data governance, statistical reasoning, ethical data use, visualization, and interpretation of analytical outputs. The shortage of qualified data-science personnel within public agencies further increases reliance on undertrained staff and external consultants. Communication gaps between technical teams and transportation practitioners also hinder effective implementation of data-driven tools and practices.

The objective of this research is to improve data literacy within transportation agencies by identifying current skill gaps and workforce needs, evaluating data usage practices, and developing strategies to improve the ability of staff to collect, interpret, manage, and apply data effectively.

This research will identify baseline competencies required for transportation data literacy; examine barriers related to training, governance, and organizational silos; evaluate the impacts of limited data-science staffing; and explore best practices for training, communication, and knowledge management. The study will develop actionable recommendations for tailored training, improved data governance, reduced reliance on external consultants, and stronger data-driven decision-making across transportation agencies.]]></description>
      <pubDate>Tue, 09 Jun 2026 17:01:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712190</guid>
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