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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>
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      <title>Research in Progress (RIP)</title>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Leveraging Telematics Data for Enhanced Traffic Safety: Unveiling Crash-Prone Hotspots and Mitigating Incidents - Phase 2</title>
      <link>https://rip.trb.org/View/2727388</link>
      <description><![CDATA[Cutting-edge connected-vehicle (CV) telematics now stream billions of instantaneous speed, heading, and hard-maneuver records across Texas roadways—an untapped resource for proactive safety management. Phase I of Project 0-7200 capitalized on this opportunity by (1) surveying and vetting statewide CV data sources, (2) building rigorous preprocessing pipelines and a strategic data-archiving scheme with the Receiving Agency, (3) defining data-driven “near-crash” events, and (4) creating proof-of-concept analytics that locate and rank high-risk corridors. Two single-user prototype web tools—Performing Agency 1’s near-crash explorer and Performing Agency 2’s multi-criteria hotspot-ranking dashboard—proved the approach valid, with results aligning closely with the Crash Records Information System (CRIS). Phase II will transform those prototypes into a secure, cloud-based, multi-user platform capable of statewide, high-volume ingestion and real-time analytics—advancing the solution to TRL 8 (actual system completed and “Receiving Agency-pilot ready”). The Performing Agency shall, optimize the data-processing engine for scalability, integrate interactive visualizations with enterprise authentication, automate continuous data refresh and long-term archiving, and embed crash-prediction models that fuse telematics with CRIS and roadway inventory. The Performing Agencies shall develop a decision-support tool that lets the Receiving Agency’s districts quickly pinpoint emerging crash-prone hotspots and deploy targeted countermeasures.]]></description>
      <pubDate>Fri, 10 Jul 2026 17:07:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2727388</guid>
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    <item>
      <title>Empirical Modeling for Improved Ground Failure Analysis</title>
      <link>https://rip.trb.org/View/2726232</link>
      <description><![CDATA[Problem Statement: Numerous bridge approaches and substructures, highway and railway embankments, and particularly roads in low-lying areas adjacent to rivers and their corresponding traffic sign and signal poles are underlain by the silt soils of the Willamette and Columbia River Valleys and below Oregon's coastal communities. These soils are susceptible to liquefaction or cyclic softening during earthquakes and will produce varying degrees of severity in the consequences such as lateral spreading displacement, global instability, and settlement. Settlement of soils will produce drag loads to bridge and traffic sign and signal pole foundations. Such damage has the potential to severely impact our critical surface transportation lifelines and reduce the efficacy of emergency responders and reduce the rate of economic recovery. The risk of seismic ground failure is exacerbated by groundwater table rise, which occurs during short-term, acute events (flooding) and the long-term effects of potential rising sea levels. Application of ground failure models to silty soils that were developed based on the responses of sandy soils can result in over-conservative estimates of the effects seismic ground failure and lead to inefficient use of limited resources as Oregon strives to maintain and improve its current resilience.
This work aims to develop the types of empirical relationships that the geotechnical community are well-familiar with but geared towards transitional silty soils, which can exhibit differing behaviors from the soils which are presently represented in available models. The objectives of this research are to produce specific design guidance, models, and spreadsheet-based tools to: (1) account for the effects of sloping ground on the calculation of the factor of safety against liquefaction/cyclic softening during earthquakes, (2) compute lateral displacements of sloping ground, and (3) calculate vertical settlements of level and sloping ground and any foundations buried within, to (4) culminate in a decision matrix for Oregon Department of Transportation (ODOT) engineers and their consultants to guide the selection of a particular model when assessing the seismic vulnerabilities of existing surface transportation infrastructure. The decision matrix and specific guidelines for conducting cyclic failure analyses and simplified displacement estimates will guide cost-effective measures to assess and improve existing surface transportation infrastructure and improve community and infrastructure resilience to increasingly combined natural hazards.
]]></description>
      <pubDate>Wed, 08 Jul 2026 17:38:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2726232</guid>
    </item>
    <item>
      <title>Leveraging Existing Vegetated Roadside Areas for Efficient Stormwater Management</title>
      <link>https://rip.trb.org/View/2726138</link>
      <description><![CDATA[Stormwater runoff from transportation infrastructure presents a persistent challenge for Oregon’s transportation system due to the requirement to treat highway stormwater runoff and protect downstream water quality. Current regulatory requirements compel project teams to demonstrate adequate stormwater treatment and infiltration performance during planning and design. However, limited understanding of how hydrologic data and roadside soil properties influence geochemical treatment capacity often prevents reliable evaluation of whether the natural roadside environment itself can meet objectives, providing an unrealized opportunity for potential savings on unnecessary facility installation and maintenance costs.
OBJECTIVES: The overall objective of this project is to develop and validate an integrated hydrologic-geochemical decision-support tool that enables early-stage screening of existing roadside stormwater infiltration potential and treatment performance. The tool will provide Oregon Department of Transportation (ODOT) with simulation capabilities to predict and quantify surface runoff routing, infiltration capacity, and subsurface geochemical dynamics. The coupled hydrologic-geochemical framework will support quantitative evaluation of whether already existing roadside environments can meet stormwater performance metrics and identify locations where built treatment facilities are actually necessary. 
The project will provide ODOT with quantitative decision-support framework for early-stage screening of roadside stormwater infiltration and treatment feasibility. The framework directly addresses the current uncertainty in determining when existing roadside soils and vegetative cover can meet stormwater performance requirements and when engineered treatment facilities are necessary. By enabling systematic identification of locations where existing soils provide sufficient infiltration and contaminant attenuation, this project may assist with (1) reducing unnecessary engineered stormwater treatment facilities that require construction costs, operational costs and long-term maintenance commitments, and (2) reducing the need to acquire additional ROW to install engineered facilities, minimizing both project delivery and O&M costs. Even if additional ROW may be needed to fit the natural areas for treatment, long-term operation and maintenance costs will likely be reduced.]]></description>
      <pubDate>Wed, 08 Jul 2026 17:25:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/2726138</guid>
    </item>
    <item>
      <title>Utilizing Public Perceptions to Inform Successful Roadside Vegetation Planning and Management</title>
      <link>https://rip.trb.org/View/2725587</link>
      <description><![CDATA[Current roadside vegetation planning and management is informed by a robust set of technical guidelines and principles rooted in engineering and natural sciences. However, public-facing roadside landscapes are part of critical infrastructure networks experienced by millions of people daily, and those experiences may vary based on traffic intensity and roadway speeds. Existing research on public perception offers limited practical guidance, as studies are often fragmented, focusing on isolated variables (like a single plant type or driver behavior). These isolated studies do not directly address the needs of engineers, vegetation managers, and transportation planners as they lack the operations and logistics needs of managing roadside vegetation in the context of local site conditions
This project aims to address these deficits through three objectives. Objective 1 will assess the current state of public perceptions as it relates to roadside vegetation management practices and regulations with the academic and grey literature. The results from this objective will then be used to inform a statewide online survey of Minnesota residents (Objective 2) focused on key attributes of the vegetation itself (e.g. height, color), vegetation composition, broader ecological factors, and perceptions of aesthetics, psychological restoration, and safety. Finally, driven by the results of the two previous objectives, in Objective 3, Roadside Vegetation Profiles (RVPs) will be created as a decision support tool for engineers, vegetation managers, and transportation planners to select for and optimize various attributes that they wish to prioritize for a specific roadside context.]]></description>
      <pubDate>Wed, 08 Jul 2026 16:47:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/2725587</guid>
    </item>
    <item>
      <title>A Decision Support System for Operational Forecasting of New Snow Natural Avalanches</title>
      <link>https://rip.trb.org/View/2717332</link>
      <description><![CDATA[Predicting new-snow or storm-snow avalanches to a high degree of accuracy (location, timing, and size) is important for state departments of transportation (DOTs) for minimizing highway closure times and ensuring safe transport in the avalanche terrain. New-snow avalanches arise because of instabilities in freshly fallen snow layers or at the interface of new and old snow. While in situ observations are critical to understanding the current state of the snowpack and making important decisions, spatial and temporal variabilities in mountainous terrain make it difficult to extrapolate the few observations that are typically available. Furthermore, highway avalanche forecasters do not have a way of remotely observing snow strength in different layers of new snow and forecasting snow stability based on this information. Previously, this information could be obtained only by human sampling in the field, which can be hazardous.

 

For NCHRP 20-30/IDEA 263, the research team will develop an avalanche forecasting system that combines numerical weather prediction; machine learning, advanced real-time weather observations; and a simple-to-interpret, physics-based, snowpack stability tool. The proposed system will provide early warning information on storm-snow instability that is too dangerous to obtain by sampling snow manually during storms. A device developed by the research team, the Differential Emissivity Imaging Disdrometer will be used to characterize individual falling snowflakes (e.g., crystal type, mass, density, precipitation rate) in real-time along with other systems. Individual snowflake data from the device will be integrated into a computationally lightweight, real-time, snow-stability model (SNOSS-ANT) that accounts for both shear and anti-crack modes of failure in new snow. This lightweight model will be combined with a simple machine-learning routine developed for the National Oceanic and Atmospheric Administration’s High-Resolution Rapid Refresh weather forecasting model to forecast the timing of natural new-snow avalanches. Utah DOT will help the research team evaluate and demonstrate the developed system at its Atwater field site on State Route 210. 

The proposed innovation addresses highway operations by (1) deploying improved or advanced technologies for systems operations, (2) incorporating reliability estimation into planning and operations modeling tools, and (3) real-time data fusion to support traveler information systems. In addition, the proposed tool will improve highway and worker safety through (1) new automated identification and warning of hazardous conditions, (2) advanced technology to reduce highway workers’ exposure to hazardous conditions, and (3) warning of impending hazards.]]></description>
      <pubDate>Tue, 23 Jun 2026 13:47:40 GMT</pubDate>
      <guid>https://rip.trb.org/View/2717332</guid>
    </item>
    <item>
      <title>Developing Guidelines for Right-Turn Lane Pockets for Intersections in Nevada</title>
      <link>https://rip.trb.org/View/2713605</link>
      <description><![CDATA[Nevada is overrepresented in intersection-related crashes and has been designated as an Intersection-Focused state by the Federal Highway Administration (FHWA).  Further research exploring how dedicated right-turn lane pockets could mitigate fatal and serious injury crashes is needed.  Currently, the criteria used to determine when an exclusive right-turn lane is required may be inconsistently applied given today’s traffic volumes, vehicle mix, pedestrian activity, and safety expectations. In some cases, right-turn lanes are omitted even when they could improve operations or safety, while in others, they are added despite limited benefits and significant cost or right-of-way impacts.
The main objective of this research is to produce an updated, data-driven, and context-sensitive framework for determining when and where exclusive right-turn lane pockets should be required or clearly not required at access points in Nevada.  In particular, a tool will be provided that will improve the Nevada Department of Transportation’s (NDOT’s) ability to consistently evaluate access points to the state highway system and will maximize the safety and operational benefits of exclusive right-turn lanes. Additionally, the research results will provide NDOT with a process model that supports consistent, transparent, and technically-sound decision making for new developments and access modifications.
The University of Nevada, Reno team plans to reach the research objective by: (1) Synthesizing the current state of knowledge and practice for right-turn lane warrants nationally and among peer agencies. (2) Collecting high-resolution field data and developing calibrated VISSIM microsimulation models.  (3) Conducting systematic scenario-based simulations using the calibrated VISSIM models and crash data analyses.  (4) Developing guidelines, using the empirical findings from the aforementioned tasks, for determining when an exclusive right-turn lane pocket is warranted. (5) Developing a user-friendly, implementation-ready decision-support tool for use by NDOT reviewers, local agency staff, developers, and consulting engineers. (6) Compiling all research findings, guidelines, and tools into a comprehensive final report and conducting a training workshop to facilitate implementation.
The final deliverables will be designed from the outset for direct integration into NDOT’s policies, procedures, and operations. 
Additionally, the implementation plan will be structured as a phased approach that transitions from research completion through pilot application, full deployment, and sustained use.]]></description>
      <pubDate>Thu, 11 Jun 2026 14:33:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2713605</guid>
    </item>
    <item>
      <title>Develop a Risk-Based Framework for Selecting Hydrologic, Hydraulic, and Scour Criteria for Temporary Hydraulic Structures and Encroachments</title>
      <link>https://rip.trb.org/View/2712198</link>
      <description><![CDATA[Temporary hydraulic structures, such as bridges, culverts, and temporary access fills, are widely used during construction and emergency response to maintain transportation access and restore mobility following infrastructure damage. Unlike permanent structures, these installations are often designed for shorter service lives and may not meet the same hydrologic and hydraulic criteria. However, current design practices vary significantly across state departments of transportation, with no consistent national guidance for determining appropriate risk levels or design storm frequencies.

 Recent studies indicate that many agencies rely on case-by-case assessments, qualitative risk evaluations, or inconsistent application of evaluation criteria for temporary structures. Additionally, there is limited use of quantitative risk models and little integration of factors such as traffic impacts, environmental considerations, and failure consequences. The lack of standardized guidance can result in designs potentially contributing to increased conservatism and lifecycle costs, or to reduced system resilience and increased risk in some scenarios. Research is needed to identify and incorporate factors such as costs, structure lifespan, traffic, scour conditions, environmental impacts, failure risks, and regional variability to help determine how to select hydrologic, hydraulic, and scour criterion for temporary structures and to measure performance.

The objectives of this research are to develop (1) a practitioner’s guide and a data-driven risk-based decision-making framework for selecting hydrologic, hydraulic, and scour design criteria for temporary hydraulic structures and encroachments; and (2) a standalone memorandum with language suitable for AASHTO’s consideration in evaluating potential updates to the AASHTO Drainage Manual.]]></description>
      <pubDate>Tue, 09 Jun 2026 17:42:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712198</guid>
    </item>
    <item>
      <title>Elevate the Prioritization of Fleets and Equipment Within an Overall Asset Management Strategy</title>
      <link>https://rip.trb.org/View/2712185</link>
      <description><![CDATA[State department of transportation (DOT) fleets support highway maintenance, emergency response, and agency operations. However, fleet funding and prioritization can vary across agencies and may differ from approaches used for infrastructure assets such as roads and bridges. Funding constraints may contribute to increased lifecycle costs, additional maintenance requirements, and challenges related to fleet expansion and replacement planning. In some cases, fleet-related needs compete with other agency priorities during funding and resource allocation decisions.

Transportation Asset Management Plans (TAMPs), established under the Moving Ahead for Progress in the 21st Century Act (MAP-21), provide a framework for managing infrastructure assets using lifecycle-based approaches. Although these plans have traditionally focused on roads and bridges, some agencies are exploring ways to incorporate fleet assets into asset management practices. Current approaches vary across agencies, and practices for integrating fleet management into TAMPs are still evolving. In addition, fleet performance and utilization data may not always be fully integrated into planning and budgeting processes. Research is needed to identify critical equipment, performance measures, funding strategies, and data management methods to assist state DOTs with assessing fleet investment needs and managing fleet resources effectively.

The objectives of this research are to (1) develop a guide with reporting tools and successful practices for prioritizing fleet and equipment within state DOT asset management planning processes to improve lifecycle management, and (2) develop a framework for a Fleet Asset Management Plan (FAMP) to aid state DOT funding decisions.]]></description>
      <pubDate>Tue, 09 Jun 2026 16:07:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712185</guid>
    </item>
    <item>
      <title>Evaluation of Positive Protection in Work Zones</title>
      <link>https://rip.trb.org/View/2712242</link>
      <description><![CDATA[Positive protection enhances safety in work zones for both users of the transportation system and for workers by providing separation between the work space and motorized traffic. The decision on whether to use positive protection in a given work zone (and what types of measures and strategies to implement) depends on many factors. The objective of this research project is to develop a decision support tool for the use of positive protection in work zones. Attainment of the project objective will fill gaps in existing knowledge and help transportation practitioners to make data-driven decisions regarding the use of positive
protection in work zones. The research approach will include a literature review, the
gathering of information from various states regarding their best practices for providing
positive protection (through a survey and interviews), analysis of data from a series of freeway work zones, and tool development. The research will be implemented through a collaborative effort by a team comprised of work zone safety experts from the University of Missouri (MU) and Michigan State University (MSU). The benefits of this research project will include improved safety for construction work zones through the use of positive protection. The guidelines developed in this research project will be of great value to the practitioners who are responsible for the implementation of positive protection in work zones and will help to facilitate the increased use of positive protection in work zones.]]></description>
      <pubDate>Tue, 09 Jun 2026 12:18:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712242</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>Ensemble Radar Nowcasts for Probabilistic Road Disruption Prediction</title>
      <link>https://rip.trb.org/View/2706035</link>
      <description><![CDATA[Heavy precipitation and flash flooding can rapidly degrade roadway operating conditions, causing speed reductions, lane closures, detours, and secondary crashes. Current traffic management systems largely confirm disruptions after they have already developed, limiting the ability of transportation operators to act proactively. Deterministic weather products also provide limited information about forecast uncertainty, which is critical for risk-based operational decision-making.
This project develops a probabilistic road disruption nowcasting system that integrates ensemble radar precipitation forecasts with traffic observations and roadway attributes to produce segment-level disruption probabilities at lead times of 30 to 180 minutes. Using a multi-member ensemble framework applied to real-time radar precipitation data, the system will generate exceedance probabilities and persistence metrics that quantify near-term hazard likelihood. These probabilistic precipitation indicators will be fused with traffic state variables and roadway characteristics to estimate the likelihood of operational disruption. The result is a calibrated, segment-level decision-support tool that provides actionable lead time and quantified uncertainty to support safer and more reliable corridor operations.

]]></description>
      <pubDate>Sat, 23 May 2026 18:00:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2706035</guid>
    </item>
    <item>
      <title>Maintenance Decision Support System Refinement</title>
      <link>https://rip.trb.org/View/2705945</link>
      <description><![CDATA[The objectives of the Maintenance Decision Support System are to: (1) Assess current road and weather conditions using observations and reasonable inferences based upon observations and physical laws. (2) Provide time- and location-specific weather forecasts along transportation routes. (3) Predict how road conditions would change due to the combined effects of the forecast weather and the application of several candidate road maintenance treatments. (4) Notify state agencies of approaching adverse conditions and suggest optimal maintenance treatments that can be achieved with resources available to the transportation agencies. (5) Evaluate the reliability of predictions and the effectiveness of applied maintenance treatments for specific road and weather conditions so that the decision support logic can be improved. Continuing the efforts of the previous phases of work, the member agencies voted on the future direction and tasks of the Maintenance Decision Support System (MDSS) pooled fund study (PFS). Some of these tasks represent continuation of previous phases of work and others are new endeavors for the project. The primary research areas selected by members of the MDSS project panel include: (1) Investigate methods to improve the MDSS model for better support of frost, freezing rain and other weather conditions; (2) Assess recommendations based on user feedback in real-time with post-recommendation analysis to improve MDSS modeling; (3) Analyze the use of Level of Service in DOT operations and understand how this functionality can be improved within MDSS; (4) Focus on Liquids as a priority treatment recommendation and develop processes that facilitate specialty liquids within MDSS; (5) Conduct a discovery process on Performance Measurement methods that would be applicable for MDSS with the goal of implementing these methods to demonstrate MDSS value; and (6) Improve the Route Configuration Process by implementing automated functionality, clear guidance for users, and preparing for the future of MDSS.]]></description>
      <pubDate>Thu, 21 May 2026 22:52:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/2705945</guid>
    </item>
    <item>
      <title>Pavement Marking Selection Process for State and Local Roads</title>
      <link>https://rip.trb.org/View/2704030</link>
      <description><![CDATA[Pavement markings are essential for guiding road users on both state and local paved roads during the day and night and under various weather conditions. The choice of pavement marking materials—such as wet retroreflective and retroreflective media—depends on several factors. These factors include the cost of materials, durability requirements of the roadway, presence of street lighting, presence of rumble strips, type of pavement, average daily traffic (ADT), contractor availability, snowplow operations, functional classification of the roadway, and its general location. Additional considerations may involve whether to recess the markings or provide contrast markings. Given these variables, the pavement marking type selection is inconsistent across the four Regions of the South Dakota Department of Transportation (SDDOT).

A research project is needed to identify which pavement markings are most effective for state and local roads. It is also important to consider autonomous vehicles (AVs), Automated Driving Systems (ADS), and Advanced Driver Assistance Systems (ADAS)—such as lane departure warning (LDW) and lane keeping assistance (LKA)—when choosing pavement markings. These technologies, which utilize cameras and sensors to detect pavement markings, have the potential to significantly reduce crashes caused by human error and distracted driving.

By establishing a standardized approach to selecting pavement markings, implementing maintenance strategies and asset management practices, and providing training across the state, we can enhance road safety by leveraging these advancements. A pavement marking selection tool, matrix, guide, and/or decision tree, along with asset management practices and training resources, are necessary to assist state and local government agencies in choosing and maintaining pavement markings based on various pavement types, traffic conditions, roadway characteristics, and functional classes, all while complying with the Manual on Uniform Traffic Control Devices (MUTCD) 11th Edition. 

This research will examine each type of pavement marking, new and emerging options, application rates, installation processes, maintenance schedules after initial placement, asset management practices, training practices, and life cycle cost analysis (LCCA).
]]></description>
      <pubDate>Wed, 20 May 2026 10:52:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2704030</guid>
    </item>
    <item>
      <title>Reliability-Aware Accessibility Measurement and Planning for Rural Transportation Systems</title>
      <link>https://rip.trb.org/View/2703797</link>
      <description><![CDATA[Reliable access to essential destinations is a persistent challenge in rural transportation systems, where long travel distances, limited infrastructure, and exposure to environmental disruptions can significantly affect mobility. Transportation accessibility is widely used in planning to evaluate how well transportation networks connect people to services and opportunities, yet most accessibility measures assume deterministic travel conditions and do not account for travel-time variability, weather disruptions, or infrastructure reliability. As a result, existing accessibility metrics may overestimate the practical ability of rural residents to reach essential destinations and provide limited guidance for transportation planning under uncertain conditions.
This project develops a reliability-aware accessibility measurement and planning framework for rural transportation systems. The research will extend traditional accessibility measures by incorporating transportation network uncertainty through scenario-based modeling of travel-time variability and disruption conditions. Reliability-aware accessibility metrics will be benchmarked against conventional accessibility measures and embedded within an optimization-based planning model that helps identify transportation interventions that improve reliable access under resource constraints. The framework will be demonstrated through a rural transportation case study using publicly available data and implemented as a prototype decision-support workflow for transportation planners.]]></description>
      <pubDate>Sat, 16 May 2026 11:55:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703797</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>
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