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    <title>Research in Progress (RIP)</title>
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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>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Collaboration on Strategic Planning Models</title>
      <link>https://rip.trb.org/View/2780382</link>
      <description><![CDATA[VisionEval (https://visioneval.org) is an open-source family of strategic tools improved by two previous pooled funds since 2017 (“Collaborative Development of New Strategic Planning Models” and “Extending and Sharing Benefits of Strategic Planning”).  A supporting community of partner agencies and others share in its use and enhancement. VisionEval supports strategic planning by allowing users to run, visualize and explore thousands of scenarios, testing a broad set of policies and actions.  Past Pooled Fund enhancements have captured need to assess telework, vehicle and fuel technology adoption, autonomous vehicle technologies, pricing, accessibility, multimodal options such as car service, short trip diversion, and transit impacts, changes in population and employment forecasts, household budgets and land use. VisionEval’s range of inputs and quick runtime also make it valuable for conceptual framing prior to long range plans and testing plans under future uncertainties.  VisionEval requires considerably less time to run than traditional network-based travel demand models and thus can be used to explore a wide range of alternatives with the best performers advancing for additional analysis.

The VisionEval framework includes the Regional Strategic Planning Model (VERSPM) and the state-wide VisionEval model (VE-State). Numerous state departments of transportation and metropolitan planning organizations use VisionEval to assess possible future economic development, technology change, and policy implementation scenarios. The success of VisionEval presents an opportunity to help users implement it, further develop modules to address pressing transportation and land use trends , improve user experience ,establish a Community of Practice to share VisionEval implementation experience and how the tool supports improved transportation decision making.

This new pooled fund (“Collaboration on Strategic Planning Models”) will increase the range of applications supported by VisionEval models, reduce implementation time,  and enhance the interactive visualization of scenario results. Additionally, this new pooled fund will further those previous efforts and extend their benefits to the agencies who choose to participate. While it is feasible in principle for agencies to perform such work on their own, many agencies are facing similar challenges, and work done on behalf of one agency is likely to be useful to others. Participating agencies are encouraged to engage in the joint development and support activities. Participation ensures each agency has timely access to usable tools that will support their emerging planning needs.

OBJECTIVE: This pooled fund will support the investment in new and upgraded tools, avoiding duplicative expenditure of public funds on similar efforts, and facilitating efficient development of innovations built on existing working tools. ]]></description>
      <pubDate>Sun, 20 Sep 2026 14:01:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2780382</guid>
    </item>
    <item>
      <title>Advanced Air Mobility (AAM) Strategic Plan for New Hampshire</title>
      <link>https://rip.trb.org/View/2775489</link>
      <description><![CDATA[This research will position New Hamphshire to quickly integrate Advanced Air Mobility (AAM) safely and expeditiously into the state’s transportation system.  AAM will provide alternative transportation means for the movement of goods and passengers thereby reducing congestion in other transportation modes. This project will identify strategies for incorporating Advanced Air Mobility (AAM) operations that provide service through scheduled, on-demand, or as part of intermodal transportation links throughout NH’s communities and across state boundaries including how to accommodate a wide range of AAM operations, infrastructure, and legislative needs. A Strategic Plan detailing the current and expected trajectory of AAM in New Hampshire and throughout the industry will provide a roadmap for stakeholders to use in developing flexible solutions to integrating AAM technologies into NH’s existing transportation system.]]></description>
      <pubDate>Wed, 09 Sep 2026 10:41:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2775489</guid>
    </item>
    <item>
      <title>Automated Vehicle (AV) Pooled Fund Study (PFS) Phase 2</title>
      <link>https://rip.trb.org/View/2734822</link>
      <description><![CDATA[Automated Vehicles (AVs) are an emerging technology that will dramatically change the transportation system, potentially reducing crashes, expanding access, and promoting sustainability, safety, and efficiency. With over 41 states actively advancing AV testing, research, policy, and planning, state departments of transportation face challenges understanding what strategies and actions are needed to prepare for this evolution in emerging technology. While many states are advancing strategic plans and roadmaps, strategies vary and ideas of what it means to be implementation ready differ. The original Automated Vehicle (AV) Pooled Fund Study (PFS) [TPF-5(453)] started in 2020 to collaboratively coordinate funding, strategies and research to help State DOTs understand their role in this changing environment, and how to proactively prepare. The objectives of this new pooled fund study, AV PFS Phase 2, are to continue and expand on the achievements of TPF-5(453). The key goals of the AV PFS Phase 2 are to conduct research that supports the following items: (1) Infrastructure readiness: What infrastructure investments do DOTs need to be making to plan and prepare for AVs; (2) Operations: How do AVs impact operations, traffic safety and maintenance; (3) Policy frameworks: What laws and policies do states need to enact to develop clear, more uniform policy across regions to avoid a patchwork approach; (4) Interstate freight and multi-modal harmonization – How can DOTs advance freight harmonization and interstate networks to support autonomous delivery; (5) Workforce development: How do we skill the current and future workforce for new technologies, processes and impacts; (6) Communications and engagement: How do we message this work to internal and external stakeholders and engage partners, industry and communities; (7) Partnerships: How can infrastructure owner-operators (IOOs) partner with industry, researchers, communities and non-profits to plan for this unknown future; (8) Strategic investment: How can IOOs make strategic investments with limited resources that plan for emerging technology and AV innovation; (9) Planning: How should DOTs plan for AV technology in the short and long-term horizons How can DOTs follow trends and develop shared future scenarios; (10) Industry forum: How can we develop a collaborative forum where states together can meet with AV industry to share ideas and learn about industry goals similar to the CAT Coalition’s IOO-OEM forum.]]></description>
      <pubDate>Thu, 23 Jul 2026 14:52:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/2734822</guid>
    </item>
    <item>
      <title>Phase 2: Leveraging Surface Monitoring to Guide Emergency Response and Long-Term Strategic Planning</title>
      <link>https://rip.trb.org/View/2725299</link>
      <description><![CDATA[Conventional monitoring, site investigation, and assessment of landslides for mitigation often requires drilling along with installation of piezometers and inclinometers which is not always feasible due to the significant expense of drilling, short lifespan of subsurface instruments, safety concerns about working on an active landslide, and difficult site access. A continued need exists to expand the capabilities of near-real-time surface monitoring of ground movements for (1) existing, monitored landslides to gather longer time-series of landslide response to variable wet seasons, and (2) newly-monitored landslides that reflect uncharacterized climatic and geologic conditions to extrapolate a spectrum of landslide impacts to Oregon Department of Transportation (ODOT) right-of-way, and (3) landslide events that occur and require quantitative information for decision-making. Such data is key for evaluating highway safety, repair and mitigation needs, and strategies for reopening after failure. The absence of this information places critical infrastructure and ultimately ODOT customers at risk.

The data from this expanded monitoring would inform important ODOT planning activities and research questions. For planning purposes, this data has already demonstrated benefits for emergency response to landslide events, planning around mitigation plans and Goal 18 discussions, maintenance considerations, and reduced ODOT time for inspection of landslides. Expanding these efforts would further support ODOT’s ability to monitor problematic slopes and make informed decisions regarding prioritization, planning, and sustaining mobility.]]></description>
      <pubDate>Wed, 08 Jul 2026 16:07:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2725299</guid>
    </item>
    <item>
      <title>SDDOT 2024 Statewide Customer Satisfaction Assessment</title>
      <link>https://rip.trb.org/View/2704024</link>
      <description><![CDATA[The South Dakota Department of Transportation (SDDOT) has commissioned statewide customer satisfaction assessments in 1997, 1999, 2002, 2004, 2006, 2011, 2015, 2018, and 2021. These surveys identified SDDOT’s key products and services and assessed perceptions of their importance and quality of delivery. Survey findings raised SDDOT’s awareness of customers’ concerns, provided valuable insights into their degree of satisfaction, influenced SDDOT’s strategic plans, and allowed SDDOT to gauge progress in addressing customers’ priorities. Some of the assessments included comparisons with similar assessments in other states in the region. Important recurring questions the SDDOT’s assessment intends to address: Have perceptions of SDDOT’s performance changed significantly? If so, how? Have SDDOT’s responses to issues identified in prior surveys been effective? Are more proactive or effective responses possible? Do key customer segments perceive SDDOT's services and performance differently from the population at large? Do perceptions vary by age, region or between urban and rural populations? Have new issues emerged that are important to the Legislature, the general public, or key customer segments? In light of increasing costs and constrained funding, have customers’ perceptions changed regarding the need for and relative priority of capital improvements, maintenance, operations, and other services? How have external factors, such as demographic changes, rural and urban development, agricultural and shipping practices, and technological developments affected customers’ perceptions of the need for and relative priority of SDDOT’s services? Have changes in SDDOT business processes, such as increased use of consultants, remote work arrangements, traveler information systems, and its external communications plan affected customers’ perceptions of the quality of service delivery? How have customers’ needs, preferences, and satisfaction levels regarding communication with SDDOT changed? How can SDDOT increase customers’ interest, trust, and engagement? How effectively does SDDOT conduct business with key business partners, particularly the contracting industry? Does the SDDOT respond innovatively and effectively to issues and concerns important to stakeholders? What is the public’s perception of driver behavior and the transportation safety culture in South Dakota?

SDDOT’s emphasis on strategic planning and its participation in the Baldrige Excellence Framework assessment process elevates the need to reassess perceptions of SDDOT’s performance and to identify how SDDOT can effectively respond.
]]></description>
      <pubDate>Wed, 20 May 2026 09:33:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2704024</guid>
    </item>
    <item>
      <title>Administration of Highway and Transportation Agencies. Support for Development of AASHTO’S 2027-2032 Strategic Plan</title>
      <link>https://rip.trb.org/View/2692291</link>
      <description><![CDATA[The American Association of State Highway Transportation Officials (AASHTO) and its state department of transportation (DOT) members look to the AASHTO Strategic Plan to guide the organization over a multiyear period to achieve its highest priorities. AASHTO's 2020–2026 Strategic Plan has successfully articulated AASHTO’s vision, mission, values, goals, and objectives, and consistently guided the work of each AASHTO council and committee through their annual action plans. The next Strategic Plan presents an opportunity to build on this success while strengthening its resonance with AASHTO’s full range of constituents, ultimately enhancing service to its members and the public.

The objective of this research is to provide planning and analytical support for the development of the AASHTO 2027-2032 Strategic Plan, including reviewing current vision, mission, values, goals, and objectives to determine what remains relevant and what should be updated or revised. 

This work will engage AASHTO members, staff, and external partners to gather input on potential updates and changes to the Strategic Plan. The project will help establish a clear and shared strategic direction for the work of AASHTO, including alignment with AASHTO council and committee work plans, while supporting staff in advancing AASHTO’s priorities. The research will consider opportunities to strengthen and sustain AASHTO’s member-volunteer model, which remains foundational to advancing state DOT priorities. In addition, the project will develop communication and performance-tracking tools to support implementation of the Strategic Plan.

The selected subcontractor will be expected to work closely with the AASHTO deputy director–chief policy officer, deputy director–chief of staff, and Strategic Plan Advisory Committee. The Advisory Committee will be composed of AASHTO’s elected officials and other state DOT chief executive officers (CEOs), non‑CEO state DOT leaders from AASHTO councils and committees, and AASHTO staff representatives.]]></description>
      <pubDate>Mon, 13 Apr 2026 16:41:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2692291</guid>
    </item>
    <item>
      <title>State DOT Council for Strategic AI Adoption</title>
      <link>https://rip.trb.org/View/2678092</link>
      <description><![CDATA[The rapid advancement of Artificial Intelligence (AI) technologies presents significant opportunities for enhancing transportation systems across the United States. However, the fragmented approach currently observed among State Departments of Transportation (DOTs) in AI adoption leads to duplicated efforts and missed opportunities for collaboration. Some agencies often face challenges in accessing the necessary resources and expertise to implement AI effectively. A unified effort through a transportation pooled fund (TPF) study can address these challenges by fostering collaboration, accelerating adoption, reducing risks, and ensuring access to AI resources. This TPF project aims to bring together State DOTs to share insights, practical application of AI implementation strategies, and best practices, thereby maximizing the benefits of AI in the transportation sector. The State DOT Council for Strategic AI Adoption will focus on the practical application of AI technologies in state-level transportation operations. While national efforts are addressing governance, standards, and policy frameworks. This TPF study will serve as a hands-on implementation network for State DOTs, ensuring they have the capacity, resources, and peer support to translate national AI strategies into operational deployments. 

OBJECTIVES: The study aims to achieve the following objectives: 1) AI meetings for State DOTs: Organize meetings and workshops to encourage dialogue and idea exchange among state DOTs. These convenings will serve as platforms for sharing experiences, discussing challenges, and collaborating on innovative solutions. 2) Strategies for AI adoption in transportation: Facilitate coordinated efforts among states to develop strategies for AI adoption in transportation. 3) Pilot Projects: Support DOTs for the implementation of pilot projects that address common use cases across the transportation sector. These projects will act as testbeds for new AI applications, providing valuable insights and best practices that can be scaled across states. 4) Create Shared Resources: Develop shared resources such as data repositories and workforce training materials. These resources will standardize data collection and analysis and equip the workforce with the skills needed to manage AI technologies effectively.]]></description>
      <pubDate>Wed, 04 Mar 2026 16:41:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2678092</guid>
    </item>
    <item>
      <title>Identifying Gaps in Transit Infrastructure and Potential Solutions</title>
      <link>https://rip.trb.org/View/2677556</link>
      <description><![CDATA[A lack of access to transit stops (due to safety concerns, poor first and last mile connections, a lack of shelter to protect from weather elements while waiting, etc.) often presents a significant barrier to using transit services, even when the service itself is well designed. However, for most bus transit projects, the feasibility study at the project planning stage only focuses on a buffer zone of 250 feet around any bus stop, as mandated and required by National Environmental Policy Act (NEPA). Such feasibility studies suffer from two drawbacks: (i) because of the limited spatial extent, they fail to capture the infrastructure gaps that may prevent people from utilizing the services; and (ii) because of limited interaction with current and potential users of the system, they fail to identify user-focused solutions to these gaps. Thus, such feasibility studies may overestimate the potential ridership while also lacking support from the local communities. As Colorado DOT (CDOT) starts implementing its planned bus rapid transit (BRT) services along some of the most heavily traveled corridors within the Denver Metro area, it is important to understand the infrastructure gaps and identify potential solutions to deliver the most benefit possible from transit infrastructure dollars.

The aim of the proposed project is to identify how and what infrastructure gaps need to be considered before evaluating the success of a transit-related investment. It also aims to create a set of potential solutions for those gaps, through user input of preferences and cost considerations. The research team uses one of the five proposed bus rapid transit projects within Denver Metro area as case study for this proposed project, complementing CDOT's ongoing work towards the BRT projects. Federal Boulevard BRT, the proposed case study BRT, is planned along one of the most heavily used travel corridors in Denver. The objectives of the project are: (i) to understand the current infrastructure needs to facilitate transit use, such as a lack of bus stop infrastructure, safety concerns, first and last-mile connectivity issues, etc.; and (ii) to identify solutions that best address the needs of the current and potential users. The proposed project will address these objectives through targeted data collection using surveys and app-based travel diary for the BRT catchment area larger than the required feasibility study (using a half-mile buffer around the bus stops instead of 250 feet as done in the NEPA study).]]></description>
      <pubDate>Wed, 04 Mar 2026 13:33:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2677556</guid>
    </item>
    <item>
      <title>Administration of Highway and Transportation Agencies. Practices for State Programming and Management of Federal Transportation Funding</title>
      <link>https://rip.trb.org/View/2666776</link>
      <description><![CDATA[State departments of transportation (DOTs) build and improve their transportation networks with federally and non-federally sourced funds. Federal funding sources have unique eligibility criteria and requirements. This means state DOTs and their metropolitan planning organization (MPO) and Tribal/local public agency (T/LPA) partners must carefully consider how to program the federal funds available to them. This includes strategic decisions for federalizing a project or not, aligning with national interests, and coordinating efforts among state DOTs and their partners.

Use of federal funds often translates into higher project delivery costs due to higher design standards and compliance requirements and a significant level of effort involved to manage those funds compared to the use of non-federal funds. How state DOTs navigate the challenges and opportunities associated with federal funds is not comprehensively documented. Research is needed to identify and analyze current practices among the state DOTs and situations when innovative practices have been adopted to address the complexities in programming and management of federal funds. This documentation of practice could highlight and improve strategies of state DOTs and their partners to maximize the impact of federal investment.

OBJECTIVE: The objective of this research is to comprehensively document existing and innovative practices of state DOTs to program, manage, and maximize federal transportation funds so that practitioners have a resource to understand opportunities to enhance their practices.  

]]></description>
      <pubDate>Mon, 09 Feb 2026 20:44:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2666776</guid>
    </item>
    <item>
      <title>Vulnerability assessment and durability of coastal freight networks (UPRM)</title>
      <link>https://rip.trb.org/View/2663230</link>
      <description><![CDATA[Project Description: Freight networks, including ports, coastal highways, bridges, and distribution hubs, are critical lifelines that sustain regional economies, enable everyday commerce, and support emergency response after catastrophic events. The coastal location of this essential transportation infrastructure makes these assets uniquely vulnerable to extreme natural events such as flooding, storm surge, coastal erosion, and compound hazards. The Puerto Rico’s 2050 Long Range Transportation Plan explicitly calls for reducing transportation vulnerabilities to extreme weather effects and improving connectivity. Puerto Rico could serve as a critical logistics hub for U.S. freight operations in the Caribbean, offering strategic access to regional markets and maritime routes. But recent storms Hurricane María (2017) and Hurricane Fiona (2021) have highlighted the freight network’s fragility and the urgent need for targeted resilience measures. 
The assessment of Puerto Rico’s freight network, one that relies solely on the performance of the highway system, can be a case study to evaluate the system vulnerabilities derived from natural flood hazards, aging infrastructure, urbanization in coastal areas, and congestion in strategic corridors. A rigorous vulnerability assessment combines data from hydrologic and coastal flood modeling with traffic flows, asset condition inventories, and safety records to identify critical and single-point-of-failure links. This integrated analysis can provide a method to reveal which corridors and nodes are most likely to fail under different flood scenarios, how congestion and limited redundancy amplify delays, and which assets require immediate reinforcement or operational changes. It can also uncover system-level interdependencies among ports, road networks, and distribution hubs that are not visible from isolated asset inspections. This project can assist local transportation agencies, freight operators, and decision-makers in identifying risks to the freight network, improving the assessment of infrastructure assets by including the interdependence between ports, road networks, and distribution hubs, and prioritize improvements in strategic planning and project development. This project is envisioned as a two-year program. Year 1 will define Puerto Rico’s primary freight network anchored at the ports of San Juan and Ponce, map major distribution points, and develop an interactive dashboard showing asset condition, corridor flows, crash hotspots, and flood-vulnerable links and nodes. Four analytical dimensions will be assessed: infrastructure condition, traffic flows, safety, and durability, using official data, operational reports, and geospatial analysis to identify hotspots and critical vulnerabilities. Year 2 will focus on network optimization and investment prioritization, applying stochastic and optimization models to produce a prioritized, implementable resilience strategy. A Texas State University team will collaborate in the review of stochastic and optimization approaches, the evaluation of data requirements and computational complexity, and provide recommendations about the best model(s) for optimizing freight flows and prioritizing investments from ports to distributors.

]]></description>
      <pubDate>Sat, 31 Jan 2026 11:32:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/2663230</guid>
    </item>
    <item>
      <title>Strategic Approaches to Managing Emerging Transportation Infrastructure Assets Through Public-Private Partnership</title>
      <link>https://rip.trb.org/View/2658058</link>
      <description><![CDATA[Oklahoma is currently undergoing major transportation infrastructure network expansions statewide yet faces unique challenges especially in low population regions with insufficient travel demand and questions of economic viability. This project aims to develop a business case for the management of emerging transportation infrastructure assets for different regions in Oklahoma by analyzing best practices from other states, assessing the interdependence between infrastructure assets and travel demand, and evaluating innovative funding and partnership models. The project will focus on charging infrastructure for alternative fuel vehicles as the use case. The research will identify strategies to reduce long-term maintenance cost, increase technology adoption, and prioritize locations for infrastructure expansions based on short-range and long-term community needs and economic impacts. Key tasks include a (1) comprehensive literature review and policy benchmarking, (2) vulnerability, interdependency, and accessibility analysis, (3) key stakeholder engagement, (4) economic and technical feasibility analysis, (5) development of asset management strategies and implementable guidelines for Oklahoma DOT and its partners. The anticipated outcomes include actionable recommendations to support the long-term financial viability of transportation infrastructure asset management, promote access, and foster economic growth in different communities. Overall, the proposed research will analyze the economic feasibility of emerging transportation infrastructure asset management strategies through cost-benefit assessments and investment justifications, strengthening the case for federal and private funding. Its alignment with national priorities and ODOT’s goals ensures the findings are both timely and impactful. Based on the results, ODOT may need to revise Oklahoma’s Transportation Asset Management (2022-2031) and Long Range Transportation (2022-2031) plans to incorporate updated guidelines on financial viability, location priorities, and infrastructure life cycle management. Implementing these changes before future expansions will improve efficiency and ensure smoother project delivery. The results will directly contribute to the state’s mission of building a safer, more reliable, and efficient transportation system.  ]]></description>
      <pubDate>Fri, 23 Jan 2026 13:43:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/2658058</guid>
    </item>
    <item>
      <title>Research Strategic Plan</title>
      <link>https://rip.trb.org/View/2640692</link>
      <description><![CDATA[Missouri Department of Transportation (MoDOT) Research wants to develop a Strategic Research and Process Improvement Plan. The plan will support MoDOT’s mission, values, and tangible results and improve the effectiveness of the program. ]]></description>
      <pubDate>Tue, 16 Dec 2025 09:23:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/2640692</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Highway Practices. Topic 57-10. Strategic Planning Practices</title>
      <link>https://rip.trb.org/View/2630490</link>
      <description><![CDATA[Final Scope
Many state departments of transportation (DOT) develop strategic plans. These strategic plans range from brief statements of mission, vision, and values to detailed documents that link those statements to operational and budgetary decisions across the agency. Unlike long-range transportation plans and other federally required planning documents, there are no formal requirements or guidance for state DOT strategic plans. The national transportation vision framework, adopted by the American Association of State Highway and Transportation Officials (AASHTO), from NCHRP Research Results Digest 404: Collective and Individual Actions to Envision and Realize the Next Era of America's Transportation Infrastructure: Phase 1, highlighted the importance of strategic planning to effect organizational change.
The objective of this synthesis is to document state DOT practice for agency-wide strategic plan development, adoption, and implementation. 
Information to be Gathered Includes (but is not limited to):

State DOTs with formal agency-wide strategic plans and the type of plan they adopted, 

Source requirements for a strategic plan (e.g., historical experience with strategic planning, state statute requirement, or executive initiative),

Business unit tasked with leading the development of the plan and/or implementation and if developed with internal staff or consultant support,

Process for developing the strategic plan, including communication strategies used with business units and agency staff; degree of leadership involvement; employee, partner, and public engagement; and level of review by state DOT executive board, commission, or other governing bodies, if applicable,

Content of the state DOT strategic plans (e.g., mission statement, values, vision statement, strategic goals and/or objectives, strategies, actions, performance and/or progress measures),

Alignment/integration practices to ensure strategic plan complements or guides other agency long-range planning documents, capital plans, and operational/business plans (means to cross siloes),

Implementation practices to operationalize strategic plans (e.g., such as communication strategies internally and with external stakeholders, change management, identifying roles and responsibilities, etc.),

Examples of how strategic planning processes support effective agency decision making and if plan framework or content is sustained between administrations, and

Measures to evaluate success of the strategic plan (e.g., dashboards, scorecards, and if publicly communicated) and when to know it is time to update (or is update cycle dictated to the state DOT).

Information will be gathered through a literature review, a survey of state DOTs, and follow-up interviews with selected DOTs for the development of case examples. Information gaps and suggestions for research to address those gaps will be identified.]]></description>
      <pubDate>Wed, 26 Nov 2025 15:51:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2630490</guid>
    </item>
    <item>
      <title>Quantum Computing and Quantum-Inspired Algorithms for Transportation Network Design</title>
      <link>https://rip.trb.org/View/2625857</link>
      <description><![CDATA[Quantum computing has the potential to transform the classical computing paradigm with improved efficiency for solving NP-hard combinatorial optimization problems modeled as a quadratic unconstrained binary optimization (QUBO) model, including those in transportation and supply chains. Although the quantum annealing (QA) algorithm is theoretically attractive, there is a lack of computational experience showing its superior performance over the traditional algorithms. The purpose of this project is to explore quantum computing and quantum-inspired algorithms on a class of transportation network design problems. We will develop and implement custom-designed algorithms to solve large-scale QUBO models for transportation network design, and evaluate their performance compared to that of QA. The model and algorithms are expected to provide optimal large-scale network design solutions efficiently. This project aligns with the DOT’s strategic goal of economic strength and global competitiveness, and supports MATC-TSE’s theme on transportation systems of the future.
]]></description>
      <pubDate>Tue, 18 Nov 2025 13:58:10 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625857</guid>
    </item>
    <item>
      <title>AI-Driven Infrastructure Prioritization: Vision-Language Model Framework for Capital Planning</title>
      <link>https://rip.trb.org/View/2620732</link>
      <description><![CDATA[This project develops a scalable, artificial intelligence (AI)-powered framework for automated condition assessment and capital investment prioritization of road and bridge infrastructure across Colorado. Current manual inspection methods are costly, slow, and limited in coverage, often missing early signs of degradation. Leveraging recent advances in Vision-Language Models (VLMs), the project proposes a novel approach that extracts Pavement Condition Index (PCI) and bridge deck ratings from satellite and street-level imagery using VLMs guided by prompt engineering and in-context learning, requiring no retraining, and will be validated against Colorado Department of Transportation (CDOT) inspection records using machine learning model accuracy metrics.

The framework integrates three components: (1) Infrastructure condition (2) network criticality, computed via graph-theoretic metrics and traffic data, and (3) hazard exposure, based on geospatial data for landslides, wildfires, and floods. These layers will be synthesized into a weighted prioritization model to rank road segments for capital upgrades, refined through CDOT expert review.

A web-based geographic information system (GIS) tool will visualize prioritization results, supporting interactive exploration and decision-making. The tool will be pilot-tested with CDOT districts, and outcomes will be disseminated through a final report, peer-reviewed publication, Transportation Learning Network (TLN) webinar, and Colorado LTAP training.

By integrating AI, geospatial analytics, and network modeling, this project addresses data-driven infrastructure planning needs—enhancing efficiency, reliability, and resilience—while offering a replicable model nationwide.]]></description>
      <pubDate>Mon, 10 Nov 2025 16:24:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2620732</guid>
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