<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
    </image>
    <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>
    </item>
    <item>
      <title>Evaluation of Large Truck Parameter Requirements For Crash Testing</title>
      <link>https://rip.trb.org/View/2712181</link>
      <description><![CDATA[Research is needed to examine test-vehicle physical properties, vehicle pre-test preparation, and relevant evaluation criteria for Manual for Assessing Safety Hardware (MASH) Test Levels 4, 5, and 6, considering the current large-vehicle fleet and contemporary freight operations.

 Research needs include: Reviewing and updating the physical properties of single-unit trucks (Test Level 4), tractor-vans (Test Level 5), and tractor-tank vehicles (Test Level 6), including vehicle dimensions, mass, center-of-mass height, and other critical features, to better reflect the current large-vehicle fleet. The research should also review MASH documentation requirements for large test vehicles. Determining whether MASH test-vehicle pre-test preparation for large vehicles reflects critical and contemporary operating practices. For example, this may include determining whether rigidly anchored or translatable ballast freight distributions contribute to more severe impact conditions or vehicle instability following impact. Assessing MASH evaluation criteria, including rollover potential, occupant risk, and effects on adjacent traffic flow, in relation to the system’s intended purpose and primary function. For example, a barrier designed primarily to capture an impacting vehicle and prevent secondary collisions with roadside obstacles may be considered successful if it effectively contains and redirects the vehicle. However, research is needed to explore whether there is value in refining the evaluation criteria to include a “preferred” performance designation for systems that also minimize occupant risk, limit occupant compartment damage, and improve vehicle stability by reducing rollover potential for large vehicles.

 Potential research tasks include: Review existing physical characteristics of large vehicles in the current vehicle fleet; Review existing crash tests, including: identifying causes of testing failures and determining whether failures are associated with particular vehicle design features.Identify issues with existing acceptance criteria; Analyze large-vehicle crashes to determine the consequences of modifying acceptance criteria; Identify potential modifications to crash test procedures.
]]></description>
      <pubDate>Tue, 09 Jun 2026 15:16:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712181</guid>
    </item>
    <item>
      <title>Public-Private Partnerships for Truck Parking Capacity Expansion and Development</title>
      <link>https://rip.trb.org/View/2712179</link>
      <description><![CDATA[Truck drivers need safe, secure, and accessible truck parking to obtain the rest required under federal hours-of-service regulations for their own safety and the safety of other road users. States face challenges in constructing and maintaining public truck parking facilities with sufficient capacity and amenities to meet demand. In addition, the prohibition on commercialization at public interstate rest areas limits states’ ability to generate revenue from amenity services for commercial motor vehicle operators.

The rise in paid truck parking in the private sector has further affected drivers since many are not reimbursed for parking their vehicles, making parking fees an out-of-pocket expense. As a result, truck drivers increasingly seek unauthorized and potentially unsafe parking locations, such as freeway shoulders, exposing themselves and the motoring public to crash risks, as well as increased risk of cargo thefts.

Public–private partnerships (P3s) have been identified as a potential strategy for truck parking capacity expansion off the interstate system. Through collaboration between public agencies and private entities, additional safe truck parking options could increase parking capacity, reduce unauthorized parking in unsafe areas, minimize cargo theft risks, reduce supply chain disruptions, and improve safety outcomes.

The objectives of this research are to (1) develop guidelines for state departments of transportation and local governments to use P3 for truck parking and (2) identify best practices that could replicate proven models to advance collaboration and partnerships with the private sector for the purpose of truck parking capacity development and expansion.]]></description>
      <pubDate>Tue, 09 Jun 2026 15:04:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712179</guid>
    </item>
    <item>
      <title>SPR-5042: Performance and Safety Evaluation of Truck Mounted Debris Clearing Systems</title>
      <link>https://rip.trb.org/View/2709430</link>
      <description><![CDATA[The principal investigators will help the Indiana Department of Transportation (INDOT) evaluate truck-mounted debris clearing systems by achieving the following three main objectives: 1) Development of an event-triggered, multi-sensor data collection framework integrating multi-camera video and Global Positioning System (GPS) to enable automated, machine vision-based performance assessment. 2) Quantitative evaluation of system performance through field testing to measure debris removal effectiveness, roadway interaction, and operational efficiency across real-world conditions. 3) Assessment of safety and traffic impacts by analyzing worker exposure, operational risks, and vehicle interactions to quantify how these systems influence roadway safety and deployment practices.]]></description>
      <pubDate>Wed, 03 Jun 2026 13:31:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2709430</guid>
    </item>
    <item>
      <title>Damage Progression of Highway Bridges and Operational Vibration-Waveforms-Phase-2</title>
      <link>https://rip.trb.org/View/2706038</link>
      <description><![CDATA[Aging highway bridges are increasingly subjected to heavy truck traffic that can exceed design load expectations and accelerate structural deterioration. Undetected overload events may contribute to localized stress concentrations, fatigue damage, and reduced service life. Current bridge monitoring approaches typically rely on periodic inspection rather than continuous operational detection of extreme loading events.
This project advances a vibration-based monitoring methodology to detect, identify, and predict the weight of heavy vehicles causing extreme loading on highway bridges. Building on Phase 1 results, the research integrates multi-sensor data—including accelerometers, six-dimensional inertial sensors, strain sensors, gyroscopes, and radar-video systems—to identify overload events and correlate them with structural response and potential damage hot spots. Finite element modeling and moving-load simulations will be used to support weight estimation and validate field measurements. The methodology will be tested on single- and multi-span steel and concrete girder bridges in Iowa. The resulting system is designed to provide a practical, portable, and cost-effective approach for bridge overload detection and condition-informed decision-making.

]]></description>
      <pubDate>Sat, 23 May 2026 18:06:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/2706038</guid>
    </item>
    <item>
      <title>A Robust Optimization-Based Approach for an Integrated Truck-Drone Emergency Resource Distribution System</title>
      <link>https://rip.trb.org/View/2684212</link>
      <description><![CDATA[The primary objective of this project is to develop and validate an integrated truck-drone coordination system that enhances emergency resource distribution through advanced optimization modeling and simulation. This system aims to improve delivery speed, service coverage, and operational efficiency during crisis situations. This project seeks to
address the challenges of disrupted transportation networks, uncertainty in demand locations, and inefficiencies in last-mile delivery during natural disasters. The primary stakeholders in this study include disaster relief agencies, emergency response teams, local government bodies, and logistics companies involved in post-disaster supply distribution. Efficient and adaptive delivery systems are crucial for these stakeholders, as traditional transportation methods often become inoperable due to damaged infrastructure limiting accessibility.

This proposal is about formulating multi-objective optimization models to coordinate multiple trucks and drones for emergence resource allocation. In such a coordination system, trucks can be used as depots, and drones can be used as delivery tools. To use drones beyond the last mile delivery, coordination points will be added between truck and customer locations. At such coordination points, drones may charge or exchange packages with other drones for longer delivery trips. Therefore, the research involves planning coordination points; coordinating delivery schedules; managing hand-offs between trucks and drones and between drones; and coordinating routes, altitudes, and timing for all active drones. The proposed model will improve emergency response efficiency and resilience during adverse conditions. The research team involves faculty members and students working in collaboration with North Carolina Department of Transportation (NCDOT) stakeholders.]]></description>
      <pubDate>Wed, 25 Mar 2026 17:23:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684212</guid>
    </item>
    <item>
      <title>A Data-driven Approach in Improving Truck Parking Efficiency</title>
      <link>https://rip.trb.org/View/2684213</link>
      <description><![CDATA[Freight transportation systems are a critical component of the United States' economy, underscoring the importance of adequate truck parking to ensure safe and efficient operations. However, a significant disparity between truck parking demand and supply has resulted in numerous challenges, including increased road safety risks, regulatory non-compliance, and operational inefficiencies. This study aims to address this knowledge gap by conducting a comprehensive review of current truck parking management approaches, with a focus on data-driven prediction models, and truck parking pattern analysis. In collaboration with the North Carolina Department of Transportation (NCDOT), the study will analyze truck parking patterns along key freight corridors and develop data-driven solutions to enhance parking efficiency and address these pressing challenges.

This project aims to address this gap by conducting a comprehensive review of existing literature and offering a nuanced exploration of potential truck parking solutions. Using NC as a case study, the project will provide data-driven recommendations to improve the efficiency and utilization of existing parking facilities along key freight corridors. By enhancing the safety and efficiency of truck parking, this study will directly benefit truck operators, supply chain stakeholders, regulatory agencies, and local communities. The findings will serve as a foundation for informed policymaking and infrastructure planning, ensuring that North Carolina’s freight transportation network remains resilient, sustainable, and operationally efficient in the face of growing demands.]]></description>
      <pubDate>Wed, 25 Mar 2026 17:16:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684213</guid>
    </item>
    <item>
      <title>Enhancing Freight Safety and Efficiency for California’s Logging Industry: A Data-Driven Approach</title>
      <link>https://rip.trb.org/View/2684215</link>
      <description><![CDATA[The logging industry plays a vital role in the U.S. economy, particularly in California’s northern regions, where timber production supports local supply chains. However, the safe and efficient movement of logging trucks is increasingly challenged by road curvature, steep grades, aging infrastructure, and seasonal fluctuations in freight demand. These factors create high-risk conditions, exacerbated by overlapping tourist activity and inadequate roadway data. This research aims to develop a comprehensive, data-driven framework to identify and mitigate freight safety risks for logging trucks. By leveraging open-source tools, data collection efforts, 3D road profiling, and advanced statistical and machine-learning models, this study will identify and predict high-risk freight routes for California’s logging industry.

Problem: The terrain, road curvature, seasonal harvest demands, and aging infrastructure pose significant challenges to both roadway safety and freight efficiency. Certain high-risk locations - such as roads with sharp curves, steep grades, or deteriorating bridges - may be especially hazardous for large vehicles like logging trucks. Furthermore, the seasonal nature of logging, combined with heightened tourism activity, creates fluctuating traffic patterns and additional stress on key corridors.

Objectives/Goals: This proposal seeks to develop a comprehensive, data-driven framework to identify, analyze, and recommend improvements for critical freight corridors used by logging trucks.]]></description>
      <pubDate>Wed, 25 Mar 2026 17:03:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684215</guid>
    </item>
    <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>Enhancing Rural Freight Resilience in the Southeastern U.S.: Data-Driven Modeling and Decision Support for Supply Chain Efficiency.

</title>
      <link>https://rip.trb.org/View/2643108</link>
      <description><![CDATA[This research aims to address the issue of limited alternative routes in rural freight systems by modeling rural freight networks to identify critical vulnerabilities and evaluate potential recovery strategies. The study also proposes new methods for addressing truck parking shortages using models such as reservation and automated allocation for predicting demand and optimizing supply. The project leverages network science, emerging data sources, and simulation tools to develop methodologies for assessing the resilience of rural freight networks. Additionally, the study will explore the potential of connected and autonomous vehicles (CAVs) for improving operational efficiency and reducing parking demand, particularly for middle-mile delivery and short-range freight operations. This research directly addresses these issues by (1) Developing network-based modeling techniques to analyze rural freight resilience, (2) Identifying critical corridors and evaluating alternative routing strategies, and (3) Proposing innovative truck parking solutions to improve operational efficiency. This includes broader operational strategies such as parking reservations, staging areas near hubs or ports, route reservations, and quicker incident resolution for truckers.  ]]></description>
      <pubDate>Sat, 20 Dec 2025 17:04:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2643108</guid>
    </item>
    <item>
      <title>Development of In-Pavement LFBG Sensors for Vehicle WIM System Measurement and Monitoring in Rural Low-Volume Road Conditions Phase One: Theoretical Research</title>
      <link>https://rip.trb.org/View/2596477</link>
      <description><![CDATA[The research aims to address the growing challenge of accurately monitoring overweight truck loads on low-volume roads, which present unique issues for both infrastructure durability and road safety. Low-volume roads, defined as those carrying fewer than 2000 vehicle per day (and often fewer than 400 vehicles per day in rural areas), account for over 80% of the roads in North Dakota. Given the state’s reliance on agriculture and natural resources transport, overload trucks frequently travel these roads, which are not designed to withstand the repeated stress of excessively heavy loads. While special permits are issued for trucks carrying heavy loads under specific conditions, enforcing weight limits on numerous low-volume roads remains a significant challenge. This issue compromises the longevity of the road infrastructure and poses safety risks for all road users. Therefore, accurate monitoring and enforcement of weight limits on low-volume roads is crucial for maintaining infrastructure and enhancing road safety.]]></description>
      <pubDate>Mon, 08 Sep 2025 16:01:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/2596477</guid>
    </item>
    <item>
      <title>SPR-5021: Traffic Signal Freight Prioritization via Vehicle to Infrastructure (V2I) Communications</title>
      <link>https://rip.trb.org/View/2576723</link>
      <description><![CDATA[This project will development and evaluate traffic signal freight prioritization utilizing third party in-cab alerts provider. This V2I application will communicate with the signal controller to extend green time for slower moving freight entering the decision zone with the objective of reducing hard braking and slower start-ups at intersections along the corridor. The communication latency (and needs) will be evaluated. This project will use and evaluate, commercial cellular infrastructure for both the communication to the trucks (in cab devices provided by Drivewyze) and communication to the traffic signal cabinets (INDOT cellular modems).]]></description>
      <pubDate>Tue, 15 Jul 2025 15:48:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2576723</guid>
    </item>
    <item>
      <title>Analysis and Implications of the Vehicle Inventory and Use Survey (VIUS)</title>
      <link>https://rip.trb.org/View/2549196</link>
      <description><![CDATA[To better understand the future of travel behavior and demand this research effort will explore the National Vehicle Inventory and Use Survey (VIUS).  There is a keen interest in this survey as a result of the fact that a growing share of all travel is non-household-based travel for freight commercial and service functions. These functions account for an estimated 40% of all vehicle miles of travel and, due to the fact that they are larger vehicles, their energy use and emissions are disproportionate to their vehicle miles traveled (VMT) share and represent a majority of all energy use and emissions for transportation. In addition, these vehicles, many owned by businesses and commercial entities, are different than household-owned vehicles in several respects including how decisions are made regarding their purchase and use. Many of these activities do not have travel alternatives such as bike and public transit that may be available for person trips. Thus, having a richer understanding of these vehicles and their utilization is important to modeling and understanding travel demand as well as influencing transportation policy strategies and investments.

Findings from the exploration of this survey will be contrasted with other sources of information regarding travel by these classifications of vehicles. It is anticipated that a comprehensive descriptive understanding of the use of these vehicles will facilitate understanding their role in things like transportation safety, transportation electrification, and future travel demand.  ]]></description>
      <pubDate>Mon, 05 May 2025 15:14:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2549196</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>Update of Traffic Factor Equations for IDOT Mechanistic-Empirical Pavement Design</title>
      <link>https://rip.trb.org/View/2486928</link>
      <description><![CDATA[Transportation agencies must adapt pavement design procedures to meet changes in traffic and advances in new technologies such as electric vehicles and trucks, which are expected to accelerate pavement damage due to increased weight from batteries. Researchers will update the equations used by IDOT pavement designers to convert mixed-traffic axle loadings into traffic factors for asphalt and concrete pavements while accounting for current traffic conditions and axle configurations. Traffic factor represents the total number of 18-kip equivalent single-axle loads, expressed in millions, that a given pavement may be expected to carry. They will also incorporate the impact of e-trucks and platoons — a group or convoy of closely spaced vehicles — on pavement design. Updating the traffic factor equations to meet current and future demands will allow the agency to properly design pavements to carry the anticipated loadings.]]></description>
      <pubDate>Mon, 06 Jan 2025 12:32:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/2486928</guid>
    </item>
  </channel>
</rss>