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    <title>Research in Progress (RIP)</title>
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    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJzdWJqZWN0aWQiIHZhbHVlPSIxNzg1IiAvPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSI3MzAiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMTYiIC8+PC9wYXJhbXM+PGZpbHRlcnMgLz48cmFuZ2VzIC8+PHNvcnRzPjxzb3J0IGZpZWxkPSJwdWJsaXNoZWQiIG9yZGVyPSJkZXNjIiAvPjwvc29ydHM+PHBlcnNpc3RzPjxwZXJzaXN0IG5hbWU9InJhbmdldHlwZSIgdmFsdWU9InB1Ymxpc2hlZGRhdGUiIC8+PC9wZXJzaXN0cz48L3NlYXJjaD4=" rel="self" type="application/rss+xml" />
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>Impact Study on Increasing Truck Permit Weight Limits: Infrastructure &amp; Economic Considerations</title>
      <link>https://rip.trb.org/View/2724819</link>
      <description><![CDATA[Oregon’s current weight restrictions (105,500 lbs.) for divisible loads are less than neighboring states like Idaho and Nevada, which permit up to 129,900 lbs. In response to industry requests for alignment with these states, Oregon Department of Transportation
(ODOT) needs a comprehensive impact assessment of what raising the weight limits will mean in terms of sustaining the current operational infrastructure its charged with maintaining. This study will evaluate infrastructure effects, highway safety, and maintenance costs, along with the implications for adaptation and community impacts. With neighboring states already designating heavier freight routes, increasing Oregon’s truck permit weight limits may support freight fleet electrification and promote regional integration of the shipping network while assessing the costs to maintain and manage this increased infrastructural burden that’s on ODOT’s horizon. This feasibility and impact study will assess selective extended weight designations in Oregon and survey existing programs nationwide while evaluating potential risks to structural integrity (pavement and bridges), traffic safety impacts, as well as community and environmental considerations. The findings will provide ODOT with data-driven insights to guide policy decisions. This study will also examine vehicle configurations and length factors necessary to maintain legal axle weights in Weight Tables 1 and 2 at a gross weight of 129,900 and determine if those lengths are consistent with the lengths allowed by the LCV (Longer Combination Vehicle) freeze in federal law.

(1) A comprehensive report containing recommendations to support an informed evaluation of increasing weight limits for divisible loads, including an infrastructure impact assessment detailing the effects of heavier loads on bridges, pavements, and highway safety, with a focus on high-frequency freight routes in Oregon. (2) An economic impact assessment will quantify the contributions of oversized freight to Oregon’s economy, balancing potential economic gains from increased freight capacity with the costs of infrastructure maintenance and safety considerations. (3) A strategic implementation plan will outline a phased approach to applying these findings, allowing ODOT to prioritize investments to engage communities and the public effectively.]]></description>
      <pubDate>Wed, 08 Jul 2026 13:35:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2724819</guid>
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    <item>
      <title>Cost-Benefit Analysis of Preemptive Weather-Related Road Closures</title>
      <link>https://rip.trb.org/View/2689390</link>
      <description><![CDATA[The decision to close a road and disrupt the flow of commerce and the traveling public results in significant costs. While maintaining roadway access is always the most preferred option, there may be scenarios, such as a multi-vehicle weather-related crashes, that induce a closure regardless of best efforts. Further, these crash scenarios place additional risk on the safety of transportation personnel, law enforcement, and emergency first responders. The resultant crash clean-up and recovery of damaged vehicles may further impede maintenance operations for a far longer duration than that of a proactive closure. The Nebraska Department of Transportation (NDOT) and the transportation community as a whole presently face unprecedented challenges with staffing shortages, financial uncertainty, and increasingly variable weather conditions. As such, the ability to determine when, where, and for how long to strategically close a road to maximize safety, minimize cost, and promote overall efficiency and reliability across the transportation network is paramount. The proposed project seeks to provide NDOT with quantitative metrics for meteorological trigger thresholds for road closures and a cost-benefit analysis of such decisions. This will allow NDOT to make consistent, justifiable decisions about when to close (and re-open) roads during extreme weather conditions.]]></description>
      <pubDate>Tue, 02 Jun 2026 12:24:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/2689390</guid>
    </item>
    <item>
      <title>Infrastructure Data System (IDS)</title>
      <link>https://rip.trb.org/View/2696940</link>
      <description><![CDATA[Transportation data have been growing in volume, velocity, and variety, especially since the introduction of connected vehicle data, crowd-sourced data, and other recent technological advancements. While this is an enormous opportunity for transportation advancement, the challenge lies in translating these data into actionable information for analysts and decision-makers. Therefore, it is crucial to make these datasets easily accessible to industry professionals and decision-makers.
This project would establish the Infrastructure Data System (IDS), a robust data hub and information portal centered around various aspects of infrastructure and NCIT. IDS shall provide a one-stop shop solution for data and ad hoc- analysis needs by leveraging skills in building data systems, web-based tools, visualizations, and geographic information systems. This system could ultimately serve as a hub to host research results under NCIT and as a repository of data and information for researchers, analysts, and policymakers.
The IDS will ensure consistency by having one centralized location and will seamlessly integrate two key NCIT topical pillars: policy and technology. By leveraging advanced technology, the IDS will provide the tools and infrastructure needed to harness the power of data, driving innovation and enabling informed decision-making in the field of transportation. While the intent is to create an active data system, the lifespan of the application will be constrained due to limited funds. However, the results of this project will serve as a proof of concept, i.e. a stepping stone, for establishing a truly effective national-level system for NCIT.
]]></description>
      <pubDate>Sat, 30 May 2026 12:16:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/2696940</guid>
    </item>
    <item>
      <title>Capital Investment, Financing, Flood Risk, and Transportation Safety in the MidAmerica Region
</title>
      <link>https://rip.trb.org/View/2706033</link>
      <description><![CDATA[Transportation agencies in the MidAmerica region face increasing pressure to manage aging infrastructure under fiscal constraints while improving transportation safety. Rural highways, freight-intensive corridors, and aging bridges experience elevated crash severity, yet capital investment timing and financing decisions are rarely evaluated through a safety-risk lens.
This project develops an integrated empirical and probabilistic framework to quantify how capital investment timing, financing mechanisms, and flood-related hazards influence lifecycle transportation safety outcomes. The study constructs project- and asset-level datasets linking capital programming records, delivery timelines, financing mechanisms, infrastructure characteristics, crash outcomes, and flood risk indicators. Econometric models estimate statistical relationships between investment timing and safety performance. Monte Carlo simulation propagates uncertainty in delivery delays, cost escalation, traffic growth, and flood exposure to produce distributions of lifecycle safety risk and cost. Results will support safety-oriented capital planning and risk-informed decision-making for transportation agencies in the MidAmerica region.

]]></description>
      <pubDate>Sat, 23 May 2026 17:36:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2706033</guid>
    </item>
    <item>
      <title>A Performance- and Cost-Based Framework to Evaluate the Value of Multimodal Logistics Infrastructure</title>
      <link>https://rip.trb.org/View/2703796</link>
      <description><![CDATA[This project develops a practical, data-driven framework to evaluate the value of logistics infrastructure in a multimodal freight region. Focusing on the St. Louis metropolitan area, the framework integrates freight performance measurement with generalized logistics cost modeling to translate travel time, reliability, and terminal access improvements into economic outcomes. Methods include assembling a regional freight network representation, computing corridor-level travel time and variability metrics, and applying scenario-based valuation to estimate marginal benefits of targeted investments. The project also includes a private-sector truck–rail–barge use case to quantify multimodal tradeoffs and assess the competitiveness of inland waterway transportation under alternative infrastructure scenarios. The resulting workflow provides agencies and regional partners with transparent, repeatable methods to support freight investment prioritization and decision-making.]]></description>
      <pubDate>Sat, 16 May 2026 11:52:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703796</guid>
    </item>
    <item>
      <title>Smart Drop-Shipping and Stocking Decision Support System</title>
      <link>https://rip.trb.org/View/2703794</link>
      <description><![CDATA[Drop-shipping is an increasingly important order fulfillment strategy in modern supply chains, allowing firms to reduce inventory holding costs by shipping products directly from suppliers to customers. However, because inventory is not directly controlled by the firm, drop-shipping can introduce uncertainty in product availability, delivery lead times, and service reliability. To compensate, firms often rely on expedited transportation, which increases costs and may negatively affect safety and efficiency in freight operations. These trade-offs create a challenging decision problem: determining which products should be stocked internally, fulfilled through drop-shipping, or managed under a mixed fulfillment strategy.
Industry interviews with a major U.S. wholesaler indicate that firms tend to rely on drop-shipping for slow-moving products due to limited warehouse space and capital constraints, yet lack systematic, data-driven methods to guide these decisions Existing research largely focuses on single-product settings or coordination issues between retailers and suppliers and does not address multi-product decisions under warehouse capacity constraints.
This project aims to fill this gap by developing an optimization-based decision support framework for drop-shipping and inventory planning across multiple stock-keeping units (SKUs). The proposed approach integrates mixed-integer programming with meta-heuristic methods to support large-scale, real-world applications. The model incorporates demand patterns, inventory holding costs, transportation costs, service level requirements, and cash flow constraints. A complementary simulation framework will be developed to evaluate system performance under uncertainty in demand, supplier inventory availability, and delivery times.
The project supports Mid-America Transportation Center (MATC) themes of Safety and Transportation Systems of the Future by enabling more predictable and efficient freight movements, reducing reliance on expedited shipping, and promoting data-driven planning in distributed fulfillment networks. Expected outcomes include an implementable decision support tool, analytical insights for industry stakeholders, and dissemination through publications and conference presentations.]]></description>
      <pubDate>Sat, 16 May 2026 11:49:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703794</guid>
    </item>
    <item>
      <title>Decision Support for Dynamic Risks: Determinants of Model Adoption</title>
      <link>https://rip.trb.org/View/2703696</link>
      <description><![CDATA[Since the COVID-19 pandemic, significant supply chain disruptions continue to impact the U.S. economy and have negative impact on transportation networks. Sudden changes in demand or freight availability contribute to increased volatility in freight prices. In turn, volatile freight rates impact the management of transportation networks and increase the difficulty of decision making. This research addresses this problem through the development of decision support tools to proactively respond to initial indicators that predict changes in driver availability and freight cost with the goal of supporting enhanced, early actions to mitigate the risk of disruptions and promote safer transportation network operations.
Work on related prior projects has underscored the importance of forecasting sources of risk to improve the management of transportation systems and the need to understand the key decision components to maximize the value of information to the decision maker. The proposed research will rely on this prior work and make advancements towards the design of an implementable system by examining the end-user perception of decision support recommendations for transportation contracting decisions. 
The research will interview transportation professionals to identify factors that influence their current decision-making and factors that would affect their adoption of a decision support tool. The results of these interviews, in conjunction with prior findings in related research, will inform the design of features for a decision support tool. Design features will be identified for an initial prototype that is suitable for conducting future usability testing of the interactive features. This research continues progress towards the development of a dynamic decision support tool that can ultimately improve the quality of transportation management decisions and continue the legacy of leadership in America’s transportation networks. ]]></description>
      <pubDate>Fri, 15 May 2026 14:13:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703696</guid>
    </item>
    <item>
      <title>Zero- and Reduced-Fare Transit Policy and Post-Pandemic Recovery: A Multi-Agency Analysis of Ridership, Service Supply, and Access</title>
      <link>https://rip.trb.org/View/2697838</link>
      <description><![CDATA[Despite growing interest in fare reduction as a policy lever, rigorous comparative evidence on its effects, particularly in the post-pandemic context, remains limited. In Virginia some 40 transit agencies eliminated fares for some period of time during the COVID pandemic, leading the Department of Rail and Public Transportation to ask how fare reduction or fare elimination have affected ridership, operations, and access for system users. This research addresses that question by developing a structured analytical framework and applying it to a sample of transit agencies in which Virginia properties are heavily represented. Using longitudinal data spanning years before and after the pandemic “lockdown”, the research compares agencies that adopted zero- and reduced-fare policies or means-tested fare-free programs against matched fare-collecting agencies. The analysis addresses three interrelated outcomes: ridership recovery trajectories, changes in service supply and scheduled speeds and headways, and shifts in access to employment and key destinations. For a representative subset of agencies, the study also conducts a network-level analysis of access to employment using Remix, a transit planning and scheduling software tool, for a selected set of agencies that represent a range of system sizes. Findings are intended to provide evidence-based guidance for Virginia transit agencies and other stakeholders considering fare policy as a tool for ridership recovery and service quality and performance.]]></description>
      <pubDate>Thu, 30 Apr 2026 08:37:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/2697838</guid>
    </item>
    <item>
      <title>The Effects of Complete Streets Policies and Projects on Local Business Development and Growth in California</title>
      <link>https://rip.trb.org/View/2696848</link>
      <description><![CDATA[This project aims to explore the effects of Complete Streets policies and projects on local business development in California. The project uses a mixed-methods research design and micro-level business databases to explore how Complete Streets influences job accessibility, business attraction, business survival rates, and the broader transformation of mixed land use surrounding Complete Streets project sites. It investigates the interplay between Complete Streets projects and local business dynamics, particularly focusing on the clustering or dispersion of businesses for the agglomeration economy. By comparing the range of Complete Streets policies adopted by different entities, such as state agencies, counties, Metropolitan Planning Organizations, and cities, within varying sociodemographic, environmental, economic, and physical contexts, the research assesses their influence on transportation improvement plans and economic development strategies. The primary objectives of the research comprise three major research tasks. First, it aims to evaluate how Complete Streets policies impact changes in travel demand and behavioral patterns, considering the allocation of various transport modes. Second, the research examines the effects of proximity to Complete Streets project sites on the growth and development of local businesses. Finally, the project seeks to understand the perspectives of transportation agencies and local governments regarding the urban environment modifications driven by Complete Streets initiatives, particularly their implications for local business growth and broader land use changes. By employing mixed methods, the research aims to provide comprehensive insights that inform policymakers, urban planners, and business owners of strategies to refine Complete Streets policies for better local business development.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:07:56 GMT</pubDate>
      <guid>https://rip.trb.org/View/2696848</guid>
    </item>
    <item>
      <title>Rural Vehicle Markets and Consumer Affordability</title>
      <link>https://rip.trb.org/View/2691725</link>
      <description><![CDATA[There is a need to better understand rural vehicle consumer choice and transportation affordability to inform efforts to support economic vitality in rural communities. Access to adequate vehicle choices at affordable price points may be limited in rural contexts due to the spatial location of vehicle purchase options. At the same time, access to affordable vehicle options has important implications for transportation affordability, mobility, and economic opportunity in rural areas. Prior research suggests that people living in rural areas are more vehicle dependent, and that vehicle affordability and access is related to mobility and economic opportunity. Recent research indicates that rural vehicle consumers face more limited options and higher prices for a small subset of vehicle options, however, little is known about the implications for consumer choice and vehicle affordability for the overall vehicle market. This project uses detailed vehicle data and vehicle dealership listings in Colorado, Maine, and Vermont to evaluate the relationship between vehicle options, distances people travel to purchase a vehicle, and the price paid for the vehicle in both urban and rural contexts. Findings from this research can inform policies that seek to expand access to affordable transportation options in rural communities.]]></description>
      <pubDate>Sun, 12 Apr 2026 23:55:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2691725</guid>
    </item>
    <item>
      <title>Container-on-Barge Market Demand </title>
      <link>https://rip.trb.org/View/2673252</link>
      <description><![CDATA[This project will assess the market demand and policy levers that could expand container-on-barge (COB) services along the Missouri and Mississippi Rivers. The study will identify key shippers, high-potential commodities, infrastructure needs, and incentive mechanisms to make COB competitive with trucking and rail. This work directly supports the Missouri Department of Transportation's (MoDOT’s) freight, sustainability, and economic development goals, and aligns with the Missouri State Freight Plan and the U.S. Maritime Administration's (MARAD’s) America’s Marine Highway Program.]]></description>
      <pubDate>Tue, 24 Feb 2026 15:27:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2673252</guid>
    </item>
    <item>
      <title>Center for Efficient Mobility (CEM) Innovation Accelerator</title>
      <link>https://rip.trb.org/View/2636170</link>
      <description><![CDATA[This project will establish an “Innovation Accelerator” for the Center for Efficient Mobility (CEM)  to act as an incubator for commercializing technologies related to healthy and efficient mobility. The CEM consortium led by the Texas A&M Transportation Institute (TTI) has already laid the groundwork for this effort through the identification of stakeholders and partners and the establishment of an innovation ecosystem to accelerate the development, adoption, and commercialization of new transportation technologies, in partnership with the Texas Department of Transportation.  This project will formalize the innovation ecosystem within CEM, supported by commercialization support and stakeholder engagement. It will include commercialization support from technology commercialization and licensing offices at TTI and the A&M System, with support from facilities at our partner institutions, and input and advice from stakeholders. Through support, seed funding, commercialization grants, and the necessary legal and business support, CEM will champion students, faculty, and researchers in their efforts to commercialize any intellectual property developed as part of the grant. CEM will leverage the support of Texas A&M’s Innovation Office (https://innovation.tamus.edu/). CEM will also work with their counterparts at other consortium members such as Georgia Tech's CREATE-X and Quadrant-i initiatives (https://commercialization.gatech.edu/ ) and work with researchers, entrepreneurs, and investors to spin off new companies based on CEM research.   The key aspects of this project include:  Stakeholder Engagement – CEM will formalize a stakeholder engagement and advisory function to identify needs and problems that can be solved through research and technology developed by CEM; Innovation Ecosystem – Students, researchers, and faculty will be supported as they advance research outcomes. The innovation ecosystem will connect them to experts, entrepreneurs, and business communities. Testing facilities and seed funding will also be made available as needed to support technology development.  Commercialization Support -  Commercialization experts from within the consortium  will provide education,  technical support, legal and business support   to researchers who develop technologies with potential for commercialization.  ]]></description>
      <pubDate>Thu, 12 Feb 2026 15:56:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2636170</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>Impact of Noise Barriers on Residential Property Values</title>
      <link>https://rip.trb.org/View/2652033</link>
      <description><![CDATA[Highway noise barriers require substantial investment from the Commonwealth of Virginia, yet their effects on nearby residential property values remain uncertain. This study will evaluate the impact of highway noise barriers on residential property values in Virginia, addressing two gaps: (1) reliance on dated Virginia studies, and (2) unclear roles of confounding factors such as school redistricting, crime, interest rates, HOA (homeowner associations and associated amenities), and economic shocks.  The study will deliver Virginia-specific, quantitative evidence on the extent to which noise barriers affect property values.

The study will identify and analyze at least eight matched pairs of neighborhoods (one with a barrier and one without) for the years with available 2012-2024 sales data, with additional pairs included as data availability allows.  If those years are not available, the analysis will focus on the years for which verified sales and barrier data can be obtained.  A regression model will be developed that forecast the log of sales price based on barrier presence or absence plus confounding factors such as home size, type of neighborhood, and time (year and quarter) of sale.  Then, the regression model will be used in two study designs—a cross-sectional analysis and a pre-post analysis.

This study has been requested by Virginia Department of Transportation's (VDOT’s) Environmental Division to support litigation and to improve communication with citizens.
]]></description>
      <pubDate>Fri, 09 Jan 2026 09:12:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652033</guid>
    </item>
    <item>
      <title>Rural Infrastructure Earthquake Risk Planning for Public Safety and Economic Stability</title>
      <link>https://rip.trb.org/View/2652031</link>
      <description><![CDATA[Earthquakes pose a significant and growing threat to rural communities across the Western United States, where transportation networks are critical lifelines for public safety and economic stability. Ground shaking, surface rupture, and aftershocks can severely damage roadways, bridges, and utilities, disrupting mobility and delaying emergency response. Earthquakes can also trigger cascading hazards—including post-earthquake fires, debris flows, and utility failures—that further compromise evacuation routes and supply chains. These risks are particularly acute in rural areas, where road connectivity is sparse, detours are limited, and small businesses play a central role in community stability.

This project addresses two key gaps: (1) rural earthquake evacuation and transportation system management under cascading hazard conditions, and (2) business continuity for small enterprises dependent on vulnerable transportation infrastructure. First, a Community Advisory Board (CAB) will guide the research, ensuring that local knowledge, operational realities, and stakeholder priorities shape the study design. Second, we will develop a GeoAI-driven, agent-based model to simulate rural evacuations under earthquake and cascading hazard scenarios, integrating seismic hazard data (e.g., ShakeMap), transportation network characteristics, traffic data, and socio-demographic information. Third, we will build a multi-hazard business continuity model that predicts how rural businesses recover following earthquake-related disruptions, incorporating infrastructure damage, supply chain dependencies, workforce displacement, and access constraints.]]></description>
      <pubDate>Thu, 08 Jan 2026 16:12:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652031</guid>
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