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    <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" />
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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>
    <image>
      <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>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>
    <item>
      <title>Truck Permits: Managing Increasing Loads and Mitigating Infrastructure Damage to Balance Freight Mobility</title>
      <link>https://rip.trb.org/View/2472700</link>
      <description><![CDATA[Non-reducible truck permits, essential for freight mobility, pose significant challenges to infrastructure integrity, contributing to accelerated fatigue, increased maintenance costs, and safety hazards. This study quantifies the scope and distribution of permit loads across Massachusetts, evaluates their impact on bridges and highways, and verifies their alignment with current regulations and industry standards. The research will integrate data on truck permits, freight volumes, and infrastructure conditions to develop data-informed recommendations for mitigating adverse effects. Outcomes include optimized permit management strategies, improved infrastructure durability, and expanded access to reliable transportation, aligning with US DOT priorities in safety and system performance.
]]></description>
      <pubDate>Mon, 09 Dec 2024 10:27:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/2472700</guid>
    </item>
    <item>
      <title>Assessment of Infrastructure Damage Cost and Compliance of Truck Weight Limit</title>
      <link>https://rip.trb.org/View/2459071</link>
      <description><![CDATA[This proposal will synthesize a comparison between estimated damage infrastructure costs and violation fines associated with overweight trucks on the Brooklyn-Queens Expresswy (BQE) corridor post-implementation of weigh-in-motion (WIM)-based direct enforcement. Even with a reduction in the number and weight of overweight trucks, some structural damage may still occur. The team will evaluate the total damage caused by overweight trucks before and after direct enforcement to assess whether current fines are sufficient to cover the repair costs. The results will help guide legislative updates and support the creation of policies for setting appropriate violation fees through the use of WIM systems for direct overweight enforcement.]]></description>
      <pubDate>Thu, 21 Nov 2024 17:05:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2459071</guid>
    </item>
    <item>
      <title>Co-locating Electric Charging Stations and Parking Facilities for Agricultural Freight Trucks for Efficient and Resilient Agricultural Supply Chain in California</title>
      <link>https://rip.trb.org/View/2422985</link>
      <description><![CDATA[The objective of this proposed research is to study the potential of co-locating electric charging stations and parking facilities for freight trucks in California – a recommendation by the California Department of Transportation (Caltrans) in its recent report on California Truck Parking Study 2022. This proposed research will focus on identifying such locations (as shared infrastructure) for charging stations and parking that will specifically cater to agricultural freight trucks of California and supporting its vital agricultural supply chain. With the strategically identified points of electric charging stations (at truck parking facilities), the goal will be to minimize the distance traveled by agricultural freight trucks to recharge, thus reducing transportation costs. This cost reduction will positively impact on the entire supply chain by making agricultural products more affordable for consumers. With readily available charging and the parking infrastructure, agricultural freight trucks can maintain their schedules more efficiently. This would reduce downtime for recharging and would ensure timely delivery of perishable agricultural goods to markets, improving overall operational efficiency in the supply chain.]]></description>
      <pubDate>Thu, 29 Aug 2024 16:15:56 GMT</pubDate>
      <guid>https://rip.trb.org/View/2422985</guid>
    </item>
    <item>
      <title>Social Life Cycle Analysis of Zero Emission Heavy-duty Trucks</title>
      <link>https://rip.trb.org/View/2414311</link>
      <description><![CDATA[California has implemented ambitious policies to reduce greenhouse gases (GHGs) and air toxins from the transport sector for both passenger vehicles and trucks. Most recently, the Advanced Clean Fleet and Advanced Clean Truck rules mandate a transition to zero emission trucks by 2042 for the entire state. These regulations are based on tailpipe emissions. While reducing tailpipe emissions is critical for reducing the health impacts of emissions on local populations, the operation/use phase is only one phase of the truck life cycle that produces emissions. From a climate change perspective, the emissions generated over the entire life of the truck is a more appropriate measure for GHG reduction.

Life Cycle Assessment (LCA) has been developed for this purpose. There are two types of LCA: environmental LCA (E-LCA) and social LCA (S-LCA). E-LCA looks at inputs (water, electricity, energy) and outputs (GHGs, other emissions/toxins) to calculate a normalized environmental footprint over a product's life. S-LCA analyzes a product's social and socio-economic aspects to identify site-specific supply chain impacts (where the activities occur), both positive and negative, for each phase (material acquisition, transformation, distribution, etc.). Impact categories include health, safety, and working conditions for various stakeholder groups. Taken together, these tools can provide a comprehensive assessment of both environmental and social impacts.
 
Building on their previous research on E-LCA for heavy-duty trucks, the researchers will conduct a S-LCA analysis to assess the social impacts of battery-electric and fuel cell trucks. This S-LCA research will include all materials and life cycle phases for hypothetical battery-electric and hydrogen electric fuel cell trucks, focusing on the materials required for large batteries and fuel cells. S-LCA will pinpoint “hot spots” of harm across the supply chain. The combined LCA (environmental plus social) will provide a more comprehensive assessment of these alternative fuel trucks and a more informed basis for designing zero emission vehicle policies. ]]></description>
      <pubDate>Thu, 08 Aug 2024 19:32:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/2414311</guid>
    </item>
    <item>
      <title>Analyzing Truck Size and Weight Impacts on Vehicle Miles Traveled</title>
      <link>https://rip.trb.org/View/2398002</link>
      <description><![CDATA[Minnesota Department of Transportation (MnDOT) has a goal of reducing vehicle miles traveled (VMT) by 20% per capita by 2050. Additionally, Minnesota’s Next Generation Energy Act sets a greenhouse gas (GHG) emission reduction goal of 80% below 2005 levels by 2050. Trucking makes up a large proportion of VMT on the intercity highway network, and medium- and heavy-duty (classes 3-8) trucks account for 37% of the GHG emissions in the transportation sector. Currently, there are no tools or guidance for the freight community in Minnesota to move toward the VMT reduction goal. Changing the regulations on truck size and weight limits could affect VMT and the resulting GHG emissions. Currently, the allowed maximum truck weight for vehicles operating on Minnesota highways without an exemption or special permit is 80,000 lbs, while some provinces in Canada allow up to 137,788 lbs., depending on the vehicle configuration. There are federal studies that analyzed the potential impacts of changing truck size or weight limits, but no studies have analyzed the impacts on Minnesota highway network (including interstate freeways). This project will use vehicle telematics and freight movement data to develop a network analysis tool to project potential VMT changes under different regulatory scenarios. Moreover, the impacts of VMT changes on lifecycle cost of transportation infrastructure, such as bridges and pavements will be analyzed. Study results could inform policies and regulations and help MnDOT move toward its VMT reduction goal.]]></description>
      <pubDate>Wed, 26 Jun 2024 09:46:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2398002</guid>
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