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    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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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>Emergency Truck Parking Location Modeling</title>
      <link>https://rip.trb.org/View/2684216</link>
      <description><![CDATA[This research project will develop and apply optimization methods for the modeling of the emergency truck parking problem. This research is directly aligned with the Center for Freight Transportation for Efficient and Resilient Supply Chain (FERSC) goal of advancing research and practice for resilient and safe freight transportation. The results of this research can be used to inform policy and identify needed investments in truck parking facilities. The end goal is to inform the establishment of safe parking facilities to minimize risks for truck drivers and the public that are associated with commercial vehicles stopping at inadequate (sometimes illegal) locations due to the lack of appropriate short- and long-term parking in emergency situations.

A top concern for truck drivers is finding adequate parking. Truck drivers need a safe place to stop for compliance with hours-of-service (HOS) regulations and for other reasons related and unrelated to their jobs. Finding adequate truck parking is even more critical in emergency situations when regular truck parking facilities might not be accessible. This research project will apply optimization methods for the modeling of the emergency truck parking problem. A mathematical programming approach will be used to identify appropriate locations for emergency truck parking under different scenarios of disruptive emergency events. The mathematical model will be tested with an instance developed for Oregon. The results of this research have the potential to inform policy and identify needed investments in truck parking facilities.]]></description>
      <pubDate>Wed, 25 Mar 2026 16:59:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684216</guid>
    </item>
    <item>
      <title>Developing a Data Fusion Tool for Improved Traffic Crash Exposure
Analysis and Modeling</title>
      <link>https://rip.trb.org/View/2663603</link>
      <description><![CDATA[Accurate measurement of exposure is critical for understanding and preventing traffic crashes, as crash frequency is directly related to how much road users are exposed to risk. However, current exposure estimates rely on data sources with complementary but individually insufficient characteristics. Traditional traffic counts and Annual Average Daily Traffic (AADT) offer high accuracy but limited spatial and temporal coverage, while emerging Location-Based Services (LBS) data provide high-resolution mobility patterns but are often biased and less reliable. This fundamental mismatch between accuracy and coverage prevents agencies from developing the complete and reliable exposure estimates needed for effective safety analysis and planning.
This project develops a data fusion tool that integrates traffic counts and AADT, LBS data, and socio-demographically representative survey data from the National Household Travel Survey (NHTS) into a unified measure of exposure. Unlike previous efforts that focused on a single travel mode or low temporal resolution, the proposed framework generates exposure estimates for motor vehicles, pedestrians, bicyclists, and scooters at fine spatial scales (intersection and mid-block) and temporal scales (daily and monthly). The tool is evaluated in Washington, D.C., using three alternative fusion paradigms: Bayesian fusion through hierarchical or state-space modeling, Dempster–Shafer theory for explicit uncertainty representation and accommodation of LBS coverage gaps, and model-based fusion employing structured error modeling with NHTS socio-demographics to correct LBS data bias.
The fusion methods are compared through crash prediction models estimated with fused exposure measures against models using individual data sources, evaluated via pseudo-R², AIC, BIC, and out-of-sample prediction error, with a target improvement of at least 10% in predictive performance. Fused exposure patterns are further validated against Washington, D.C.’s High Injury Network and independent ground-truth count data where available. The final tool is delivered as an open-source Python package with documentation and secure coding practices. Agency outreach, including engagement with D.C. stakeholders managing the High Injury Network, informs tool refinement and supports preparation for future pilot deployment. This research supports USDOT’s Safety priority by generating more accurate and complete multimodal exposure measures that enable better identification of high-risk locations, improved crash prediction, and targeted safety interventions
]]></description>
      <pubDate>Tue, 03 Feb 2026 15:31:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2663603</guid>
    </item>
    <item>
      <title>Drone Network Design for Emergency Response in Rural Utah</title>
      <link>https://rip.trb.org/View/2655749</link>
      <description><![CDATA[Rural areas of Utah face significant challenges in providing timely and comprehensive emergency response. Long distances, limited road infrastructure, mountainous and desert terrain, and weather-related disruptions can significantly delay ambulances and rescue teams. These factors often increase response times for medical, disaster, and search-and-rescue emergencies, directly impacting outcomes and endangering lives.

Traditional emergency services remain essential, but they are insufficient in covering all rural needs quickly. Unmanned Aircraft Systems (UAS), or drones, present a transformative opportunity to bypass geographic and infrastructure barriers. Drones can rapidly deliver critical supplies, e.g. medical kits, blood units, communication devices, food, water, or specialized equipment, within minutes rather than hours. However, to make such a system viable, Utah requires a data-driven framework to determine where drone bases should be located, what fleet capabilities are needed, and how to integrate these operations with regulatory and local constraints. This project addresses the need to design an optimized drone network for comprehensive emergency response in rural Utah.

The primary objective of this research project is to develop an optimized drone network design to significantly reduce emergency response times in rural Utah by identifying strategic drone base locations, fleet requirements, and deployment strategies. Secondary objectives of this research project are to evaluate the technological, regulatory, and operational feasibility of drone-based emergency response, ensuring alignment with community needs and positioning Utah Department of Transportation (UDOT) as a leader in innovative public safety solutions.]]></description>
      <pubDate>Mon, 19 Jan 2026 16:43:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2655749</guid>
    </item>
    <item>
      <title>Optimizing Signal Timing Through New Technologies</title>
      <link>https://rip.trb.org/View/2640688</link>
      <description><![CDATA[Traditional signal timing optimization is time consuming and requires engineering expertise, often resulting in long delays between optimization cycles. New technologies could provide an opportunity to make the process more efficient by early identification of locations where reoccurring congestion is occurring.  The objectives of this research project are to do a detailed feasibility study of technologies that can aid in identifying locations where current signal timing is causing delays and a process document for implementation of the technology.]]></description>
      <pubDate>Tue, 16 Dec 2025 09:06:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2640688</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Highway Practices. Topic 57-08. Siting Electric Transmission Lines in Rights-of-Way</title>
      <link>https://rip.trb.org/View/2630486</link>
      <description><![CDATA[A growing population increases electricity demand and requires reliability. However, expanding the electric grid’s capacity to meet additional energy demand requires installation of new transmission lines to deliver electricity to end-users. Key steps in this expansion include land permitting to host the electric transmission lines and right-of-way (ROW) acquisition for energy stakeholders to address additional ROW needs. Federal agencies have encouraged state departments of transportation (DOTs) to consider accommodating energy transmission lines within highway ROWs through utility accommodation policies or as alternative use provisions under 23 CFR 710.

The objective of this synthesis is to document practices for siting electric transmission lines in the state DOT–owned ROW. This synthesis will encompass emerging practices and policies for co-locating electric transmission lines in the highway ROW.
]]></description>
      <pubDate>Wed, 26 Nov 2025 17:21:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/2630486</guid>
    </item>
    <item>
      <title>Location-Based Technology for Construction Project Record and Activity Efficiency</title>
      <link>https://rip.trb.org/View/2607968</link>
      <description><![CDATA[This project will fund a pilot project using the collaborative digital stationing program, OnStation, to complement existing New Mexico Department of Transportation (NMDOT) e-Construction technologies. The digital stationing software will be deployed in two districts for use on multiple construction projects for two years. The software will be deployed on mobile electronic devices for use by field inspectors, supervisors, and project managers. Software users will receive training before usage. Users will have the ability to access digital stationing and software features in the field and the project offices. The software deployment and usage will be a complete project. By piloting this software in two of the six Districts in New Mexico, the NMDOT can ensure that the software will be fully functional and a good fit for use in the state of New Mexico. In the future, if the deployment is successful, the software will be used in all six NMDOT Districts. ]]></description>
      <pubDate>Thu, 09 Oct 2025 13:31:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2607968</guid>
    </item>
    <item>
      <title>Integrating Weight-in-Motion (WIM) with Vehicle and Land-Use Data Sources to Characterize Freight Truck Patterns and Optimize WIM Site Placement</title>
      <link>https://rip.trb.org/View/2589064</link>
      <description><![CDATA[The objective of this research is to: support Georgia Department of Transportation (GDOT) in enhancing its freight monitoring capabilities by evaluating the effectiveness of its existing weigh-in-motion (WIM) network and assessing the potential of integrating multiple data sources to inform future WIM site placement.

]]></description>
      <pubDate>Thu, 14 Aug 2025 14:09:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2589064</guid>
    </item>
    <item>
      <title>Bioswale sizing calculator to optimize placement</title>
      <link>https://rip.trb.org/View/2566925</link>
      <description><![CDATA[The design of bioswales faces ongoing challenges due to the absence of formal guidance, particularly regarding the optimal number and placement of bioswales on a given street. This lack of clarity hampers effective stormwater management strategies in urban areas. Current literature fails to provide sufficient direction on how to optimize bioswale sizing and placement based on watershed size and soil moisture levels, leading to suboptimal performance and maintenance issues. Addressing this gap, the proposed research aims to leverage the correlation between watershed size and soil moisture levels to develop a comprehensive understanding of optimal bioswale sizing and placement. By instrumenting 70 bioswales in New Haven with soil moisture sensors, this study seeks to answer critical questions that have long plagued city planners and land managers. Specifically, it aims to determine how many bioswales should be constructed in a given area to maximize stormwater management efficiency while minimizing maintenance requirements.]]></description>
      <pubDate>Wed, 18 Jun 2025 16:02:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/2566925</guid>
    </item>
    <item>
      <title>Evaluating the Effectiveness of Dynamic Speed Feedback Sign (DSFS) at Safety Critical Locations in Connecticut </title>
      <link>https://rip.trb.org/View/2566902</link>
      <description><![CDATA[This research study will use the field data collected at horizontal curves and speed transition zones to evaluate the effectiveness of dynamic speed feedback sign (DSFS) in improving speed compliance at these locations. The research team will extensively collect speed data at numerous horizontal curves and speed transition zones to obtain a meaningful sample size; and estimate the ideal range of longitudinal position of DSFS that produces maximum impact on speed.]]></description>
      <pubDate>Wed, 18 Jun 2025 13:29:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/2566902</guid>
    </item>
    <item>
      <title>Accurate Collection and Reporting of Worker Presence in Work Zones </title>
      <link>https://rip.trb.org/View/2548660</link>
      <description><![CDATA[Accurately knowing and sharing the location of highway construction workers within a large work zone offers several benefits. First, it can enhance worker safety by informing motorists of the presence of workers on foot, thereby increasing their alertness and reducing the risk of crashes. Worker presence information is an important feature of the work zone data exchange feeds that DOTs are increasingly sharing with the public, including commercial motor vehicle drivers. Second, in the event of a crash, knowing the location of a worker also allows faster response time for incident management. Third, tracking worker locations helps improve efficiency and project management, as the information can help optimize resource allocation and streamline workflow coordination through better personnel and task tracking.]]></description>
      <pubDate>Wed, 30 Apr 2025 09:34:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2548660</guid>
    </item>
    <item>
      <title>Effects of Tunnel Location on Slope Stability (UTI-UTC 11)
</title>
      <link>https://rip.trb.org/View/2543320</link>
      <description><![CDATA[This project investigates how the placement and alignment of tunnels influence the stability of surrounding slopes, with a focus on mountainous regions such as those near the Eisenhower-Johnson Memorial Tunnel (EJMT). The research integrates geotechnical data, historical slope movement records, and numerical modeling to assess the interaction between tunnel excavation and existing slope conditions. By simulating various tunnel alignments and depths, the study identifies critical scenarios that may exacerbate slope instability or trigger landslides. Tools such as slope stability analysis software and custom Excel-based calculators are used to evaluate factor of safety and deformation responses. The goal is to provide transportation agencies with reliable, data-driven insights for selecting tunnel routes that minimize geotechnical risks and support long-term infrastructure resilience.
]]></description>
      <pubDate>Thu, 24 Apr 2025 15:58:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/2543320</guid>
    </item>
    <item>
      <title>Implementation of Multimodal Innovations: Crosswalk Lighting, Rectangular Rapid Flashing Beacons (RRFB), LED-embedded Advance Warning Signs, and Passive Automated Detection</title>
      <link>https://rip.trb.org/View/2519073</link>
      <description><![CDATA[To reduce vulnerable road user injuries and fatalities, the Federal Highway Administration (FHWA) has developed a collection of countermeasures under the umbrella of the Proven Safety Countermeasure initiative (PSCi).  Although the countermeasures are discrete elements (e.g., bicycle lanes or pedestrian refuge islands), they are only effective when applied as a system and tailored to local conditions.  For example, for uncontrolled pedestrian crossings along low- and moderate-speed roads, elements such as pedestrian-actuated nighttime illumination and flashing beacons might be appropriate at the crosswalk.  Additional measures such as LED-embedded advance warning signs might be appropriate at sites with higher speeds or sight distance challenges.  Many of these elements have been shown to be effective in other states and in Europe, but they have not been widely deployed in Virginia due to two obstacles.  First, there has not been a Virginia-specific comprehensive evaluation—e.g., to what extent do these systems influence motorist speeds or safety surrogates such as vehicle/pedestrian near-misses and changes in rates of motorist yielding to pedestrians—that considers measures of exposure such as traffic and pedestrian volumes.  Second, the mechanisms through which Virginia entities—notably cities, towns, and Virginia Department of Transportation (VDOT) Districts—should procure and install these systems is not clear.  Through two case studies, this research seeks to address both obstacles.  Although the numerical results will be specific to the case study locations, the lessons learned in terms of how to select sites, how to tailor PSCi systems and other multimodal elements to those sites, and how to conduct the evaluation are generalizable to other locations that could benefit from a PSCi system.]]></description>
      <pubDate>Thu, 06 Mar 2025 11:26:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2519073</guid>
    </item>
    <item>
      <title>Development of an Experimental Sampling Plan to Address Statistical Variability Associated with Sampling Asphalt Mixtures from the Roadway</title>
      <link>https://rip.trb.org/View/2518953</link>
      <description><![CDATA[The objective of this project is to develop a detailed plan and recommendations for a roadway sampling variability study. The plan should describe the optimal sampling location (paver hopper, paver auger box or behind the paver from the paved surface), as well as the number of samples, replicates, projects, testing locations, types of mixtures, and aggregate sources to be included.]]></description>
      <pubDate>Tue, 04 Mar 2025 10:31:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/2518953</guid>
    </item>
    <item>
      <title>Comprehensive assessment of alternative fueling system supply chains in the heavy duty trucking sector</title>
      <link>https://rip.trb.org/View/2495007</link>
      <description><![CDATA[This project examines production supply chains for fueling systems of heavy duty vehicles.  The project uses life cycle analysis (LCA) and extends the method to consider impacts beyond energy consumption and associated emissions, including wider societal impacts, such as air emissions generated in the production or operations process, or labor conditions for those engaged in raw materials extraction or component production.  The project builds on current research that is developing prototype supply chains and identifying “hot spots” for particular impacts.  The purpose of the research is to examine strategies for relocating resource extraction, production, and manufacturing activity to reduce overall impacts.  The case of electric batteries for trucks is used to estimate the effects of taking advantage of locations with cleaner energy mix or more robust labor standards, as for example onshoring manufacturing to the US.]]></description>
      <pubDate>Fri, 31 Jan 2025 18:42:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/2495007</guid>
    </item>
    <item>
      <title>Evaluating Housing Dissonance and the Potential for Smart Growth in Rural America</title>
      <link>https://rip.trb.org/View/2495006</link>
      <description><![CDATA[The potential to adopt more sustainable travel behavior and the ability to meet travel needs in small and rural communities is strongly linked with land use. Some evidence points to a large unmet demand in rural US areas for more compact and mixed-use development that could help create more livable and sustainable communities. This project involves a national study to evaluate the types of communities where people in rural areas currently live and how those align with their preferences. This project will focus on understanding neighborhood-level attributes and transportation factors that explain housing location preferences and provide insights into the potential for land-use strategies to address rural transportation needs while reducing emissions.]]></description>
      <pubDate>Fri, 31 Jan 2025 16:35:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2495006</guid>
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