<?xml version="1.0" encoding="utf-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TRB Publications Index</title><link>http://pubsindex.trb.org/</link><atom:link href="http://pubsindex.trb.org/common/TRIS Suite/feeds/rss.aspx?cdatein=1year" rel="self" type="application/rss+xml" /><description></description><language>en-us</language><copyright>Copyright © 2015. 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>TRB Publications Index</title><url>http://pubsindex.trb.org/Images/PageHeader-wTitle.png</url><link>http://pubsindex.trb.org/</link></image><item><title>Assessing Flooding Effect on Flexible Pavement Serviceability Using AASHTO 1993 Method and FWD Testing: Case Study in Florida</title><link>http://pubsindex.trb.org/view/2742200</link><description><![CDATA[This study aims to evaluate the effect of flooding on flexible pavement serviceability utilizing the American Association of State Highway and Transportation Officials 1993 design method and falling weight deflectometer (FWD) testing based on a case study in Florida. The modulus of pavement layers was back-calculated from FWD deflections and used to calculate the changes in pavement serviceability (ΔPSI) because of flooding. The results showed that the post-flooding pavement conditions can be categorized into three distinct periods. The first period represents an initial weakening phase in which the base, subgrade, and asphalt layers were all compromised, with the ΔPSI increasing by nearly six times. The second period corresponds to a partial recovery phase, during which the base layer recovered, while the subgrade and asphalt layers remained weakened. Therefore, the ΔPSI increase was reduced to 2.8 times, underscoring the critical role of base recovery. The third period is the post-recovery phase, during which both the base and subgrade layers fully recovered, but the asphalt layer continued to have permanent surface damage, with its modulus reduced by an average of 40%. During this phase, the ΔPSI increased by 2.6 times, exceeding the magnitude observed during the moisture recovery period, highlighting the long-term flooding effect. To mitigate flooding-induced pavement deterioration, traffic control can be an effective strategy to maintain acceptable ΔPSI levels in the short-term, while rehabilitation might be necessary to ensure long-term pavement performance. The proposed method provides a practical and efficient approach for quantifying flooding-induced pavement damage and informing transportation agencies of roadway resilience considerations.]]></description><pubDate>Mon, 03 Aug 2026 15:12:51 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742200</guid></item><item><title>Evaluation of Asphalt Mixture Production Sampling Frequency for Balanced Mix Design Acceptance using IDEAL-CT and IDEAL-RT</title><link>http://pubsindex.trb.org/view/2742337</link><description><![CDATA[Implementation of balanced mix design (BMD) tests during mixture production is crucial for assuring the quality and consistency of BMD mixtures. However, the BMD system lacks engineered testing frequency protocols and can require extensive sampling, labor, time, and equipment during quality control (QC) and quality assurance (QA). The main goal of this study is to determine appropriate production testing frequencies for IDEAL-CT and IDEAL-RT during BMD mixture production. In this study, eight asphalt mixtures with Superpave aggregate gradations, produced across 21 days and forty-nine sublots were evaluated to capture the variabilities occurring at sublot, day, and mixture-level production. IDEAL-CT and IDEAL-RT tests were performed on these reheated plant-produced and laboratory-compacted (RPMLC) mixtures. From the production variability analysis, the coefficient of variation (CoV) for the corresponding sublot, day, and mixture-level production was determined to be 21.1%, 27.7%, and 30.6% for CTindex, and 5.7%, 7.4%, and 9.6% for RTindex. The study also identified reduced sampling scenarios to capture daily production averages in CTindex and RTindex within 5%, 10%, 15%, and 20% deviation from the actual day average. To confidently determine CTindex and RTindex for a production day, 3S-2R (two replicates each from any three sublots) and 2S-2R (two replicates each from any two sublots) sampling scenarios can be adopted, respectively. Further, the study recommends multiple sublot sampling to determine approximate production day average over single sublot sampling. Overall, the study concludes that it is practically possible for consistent daily BMD mixture productions and incorporation of IDEAL-CT and IDEAL-RT tests during QC&amp;QA.]]></description><pubDate>Mon, 03 Aug 2026 15:12:51 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742337</guid></item><item><title>Commuting and the Spatial Mismatch: A Foregone Accessibility Approach</title><link>http://pubsindex.trb.org/view/2742332</link><description><![CDATA[The influence of urban structure on commuting efficiency has long been a central topic in urban and transportation research. Most traditional measures of commuting efficiency, such as excess commuting, rely primarily on distance and, occasionally, travel time. While useful, these proximity-based metrics fail to capture the spatial distribution of jobs and workers. Accessibility, defined as the ease of reaching destinations, offers a more comprehensive framework for addressing this limitation, as it considers the distribution of activities across space. We adopt the cumulative opportunities measure, which counts destinations reachable within a given time or distance threshold, replacing that threshold with the observed commuting distance. We call this “foregone accessibility,” defined as the share of citywide jobs located within a worker’s observed commuting distance that they do not take up or interact with. We compare observed commuting distance and foregone accessibility across different employment sectors for both workers and jobs in Greater Montreal, based on their levels of concentration and dispersion. Our findings reveal that foregone accessibility and observed commuting distance are not always positively correlated; in some cases, the relationship is negative. High commuting distances tend to be associated with low foregone accessibility, suggesting that some areas lack employment opportunities nearby, compelling residents to travel long distances. This highlights the limitations of relying solely on distance-based measures and underscores the need to adopt accessibility-based metrics. Such an approach is particularly relevant for urban planning, as it captures not only proximity but also the spatial distribution of employment opportunities across a city.]]></description><pubDate>Mon, 03 Aug 2026 15:12:51 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742332</guid></item><item><title>Evaluation of the Transportation Pooled Fund Program</title><link>http://pubsindex.trb.org/view/2742398</link><description><![CDATA[The Federal Highway Administration (FHWA) Research &amp; Technology (R&amp;T) evaluation program was initiated in 2013 to assess and communicate the value and effectiveness of investments made to advance innovation in the transportation industry. The objective of this program is to document the impact of the projects, demonstrate accountability to funders and policymakers, and identify lessons learned and best practices that can be applied to future projects/programs. As part of this program, the Transportation Pooled Fund (TPF) Program is being evaluated to better understand the program’s value and industry influence. The purpose of this project (TFPE 06) is to conduct a comprehensive evaluation of the TPF Program, identify its strengths and weaknesses, and provide strategies for optimizing the return on investment for administering this program. The fundamental evaluation metrics for the TPF program are efficiency, implementation, effectiveness, cost-effectiveness, and program participation. This Final Report begins with background information on the TPF Program to provide the foundation for the evaluation. Then, the report describes the evaluation approach and findings from the evaluation steps. Finally, findings are synthesized using quantitative and qualitative methods to provide responses to the evaluation questions.]]></description><pubDate>Mon, 03 Aug 2026 11:44:25 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742398</guid></item><item><title>Developing a Data-Driven Tool for Optimizing Maintenance Technician Staffing in Highway Fleet Operations</title><link>http://pubsindex.trb.org/view/2742136</link><description><![CDATA[With increasingly complex fleet technologies, technician shortages, financial strains, and changing workforce structures, state departments of transportation (DOTs) need a tool to help determine staffing allocations and assignments. NCHRP Project 23-40 developed a robust methodology and an interactive tool specifically designed to optimize staffing levels for highway maintenance fleets within state DOTs. The interactive tool provides a practical, data-driven solution that will help fleet managers make informed staffing decisions. The interactive tool is built in Microsoft Excel, chosen for its accessibility and familiarity to DOT personnel. The tool calculates technician staffing needs at the field, region/district, and statewide levels, making it adaptable to different organizational structures. The methodology underlying the tool incorporates a range of factors that impact maintenance staffing requirements: fleet size and makeup, equipment utilization levels, technician billable hours, the degree of equipment outsourcing, use of temporary staff, and reliance on overtime. For each equipment class, a Technician-Hour Standard (Tech-Hour Standard or Standard) is developed to determine the number of annual direct technician hours required to maintain a vehicle unit.]]></description><pubDate>Sat, 01 Aug 2026 13:34:47 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742136</guid></item><item><title>Review of Transit Station Design Guidelines</title><link>http://pubsindex.trb.org/view/2742133</link><description><![CDATA[As part of TCRP Project A-47, “Transit Capacity and Quality of Service Manual, Fourth Edition,” the research team conducted a series of small research tasks to develop new content for the manual. This TCRP research results digest (RRD) is one of 12 presenting the results of these research tasks. The Transit Capacity and Quality of Service Manual (TCQSM) provides guidance on transit station design and capacity analysis, but it does not recommend minimum or desirable station element dimensions or other design choices. This RRD compiles guidance from multiple transit agency design guides that agencies and projects may use to identify dimensions appropriate to their circumstances.]]></description><pubDate>Sat, 01 Aug 2026 13:34:47 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742133</guid></item><item><title>Estimating Bus Speed: Update of the TCQSM Method</title><link>http://pubsindex.trb.org/view/2742134</link><description><![CDATA[As part of TCRP Project A-47, “Transit Capacity and Quality of Service Manual Fourth Edition,” the research team conducted a series of small research tasks to support development of new content for the manual. This TCRP research results digest (RRD) is one of 12 presenting the results of these research tasks. Practitioners use the bus speed estimation method of the TCQSM 3rd edition to quickly forecast the effects of proposed operational changes, such as developing bus lanes or increasing bus stop spacing. This RRD describes the use of archived bus travel time data to validate and update the method using more bus facilities and many more bus travel time observations than were feasible when the research underlying the method was conducted in the late 1990s.]]></description><pubDate>Sat, 01 Aug 2026 13:34:47 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742134</guid></item><item><title>A Data-Driven Tool for Optimizing Maintenance Technician Staffing in Highway Fleet Operations</title><link>http://pubsindex.trb.org/view/2742137</link><description><![CDATA[This report presents the Predictive Insights for Technician Staffing and Operational Planning (PITSTOP) tool, developed under NCHRP Project 23-40 to support data-driven optimization of maintenance technician staffing for highway fleets. It uses vehicle inventory, maintenance history, and operational assumptions to estimate technician-hour standards and convert them into staffing requirements measured in full-time equivalent hours (FTEs). The tool integrates multiple datasets and provides a structured workflow for data preparation, validation, and analysis. Results are delivered through dashboards that identify staffing gaps or surpluses across state, regional, and shop levels. The tool enables transportation agencies to make transparent, consistent, and defensible workforce planning decisions.]]></description><pubDate>Sat, 01 Aug 2026 13:34:47 GMT</pubDate><guid>http://pubsindex.trb.org/view/2742137</guid></item><item><title>Developing a Guide to Manage Out-of-Service Utility Facilities</title><link>http://pubsindex.trb.org/view/2737280</link><description><![CDATA[Utilities are essential services that often occupy the public right-of-way along roads. While utility access benefits both service providers and the public, utility facilities can complicate highway construction, especially roadway expansion projects. Transportation agencies identify utilities requiring relocation through coordination with utility owners during project planning and design. However, no process or technology can guarantee the detection of all buried utilities. Abandoned or out-of-service (OOS) utilities are particularly difficult to identify because ownership records may be missing, inaccurate, or unavailable. When previously unknown utilities are discovered during construction, they can cause significant project delays, increased costs, and contractor claims.  This document, produced by the Transportation Research Board's (TRB’s) National Cooperative Highway Research Program (NCHRP), describes the research conducted to develop holistic guidance to locate, track, and manage OOS facilities throughout the life cycle of highway facilities, including strategies to address long-term, short-term, and urgent or emergency OOS facility issues. The research resulted in development of guidance published as NCHRP Research Report 1185: Out-of-Service Utility Facilities: Management Throughout the Highway Life Cycle.]]></description><pubDate>Fri, 31 Jul 2026 09:02:42 GMT</pubDate><guid>http://pubsindex.trb.org/view/2737280</guid></item><item><title>Out-of-Service Utility Facilities: Management Throughout the Highway Life Cycle</title><link>http://pubsindex.trb.org/view/2737269</link><description><![CDATA[Utilities are essential services that often occupy the public right-of-way along roads. While utility access benefits both service providers and the public, utility facilities can complicate highway construction, especially roadway expansion projects. Transportation agencies identify utilities requiring relocation through coordination with utility owners during project planning and design. However, no process or technology can guarantee the detection of all buried utilities. Abandoned or out-of-service (OOS) utilities are particularly difficult to identify because ownership records may be missing, inaccurate, or unavailable. When previously unknown utilities are discovered during construction, they can cause significant project delays, increased costs, and contractor claims. This report produced by the Transportation Research Board's (TRB’s) National Cooperative Highway Research Program (NCHRP), provides guidance on practices for locating, identifying, tracking, and managing OOS utility facilities throughout the highway life cycle. The guide is designed to help transportation officials understand the risks associated with OOS utility facilities and implement strategies to reduce project delays, costs, and construction impacts. It also supports contractors, consultants, utility owners, and other stakeholders by increasing awareness of OOS utility issues and promoting practices that improve coordination, decision-making, and project outcomes. A report documenting the research conducted to develop NCHRP Research Report 1185 was published as NCHRP Web-Only Document 454: Developing a Guide to Manage Out-of-Service Utility Facilities.]]></description><pubDate>Fri, 31 Jul 2026 09:02:42 GMT</pubDate><guid>http://pubsindex.trb.org/view/2737269</guid></item><item><title>Structural Redundancy Analysis for Continuous Steel Two-Girder Bridges: Evaluation of Capacity and Failure Modes</title><link>http://pubsindex.trb.org/view/2736658</link><description><![CDATA[This study presents structural redundancy evaluations of three two-girder steel bridge systems using finite element analysis to assess their capacity and behavior under fracture conditions. Following AASHTO System Redundant Members (SRM) Guide Specifications, detailed three-dimensional finite element analysis (FEA) models were developed in ABAQUS to simulate member fractures at critical locations and evaluate bridge responses under Redundancy I and II load combinations. The analysis includes two-girder bridges using geometries typical of real bridge applications. Multiple fracture scenarios across different spans were evaluated to identify controlling limit states and failure modes. Results demonstrate that two-girder systems may have redundancy challenges as a result of limited load sharing between intact and fractured girders. This limitation results from low torsional stiffness and relatively flexible lateral bracing and floor beams, which severely restrict load redistribution. When one girder fractures, the remaining intact girder carries substantially increased loads, causing the fractured girder to behave as a cantilever beam. The controlling failure mode was identified as buckling at section changes near piers on fractured girders, with high displacement differences between intact and fractured girders. These behaviors may reduce reserve capacity below Redundancy I and II thresholds. Analysis revealed that the evaluated two-girder bridges did not meet SRM qualification requirements because of inadequate load transfer mechanisms between the two main load-carrying members. This research provides bridge engineers with critical guidance on the need for careful evaluation when two-girder systems are evaluated for redundancy performance.]]></description><pubDate>Thu, 30 Jul 2026 09:59:20 GMT</pubDate><guid>http://pubsindex.trb.org/view/2736658</guid></item><item><title>Discrete Choice Model with Generalized Additive Utility Network for Interpretable Policy Evaluation</title><link>http://pubsindex.trb.org/view/2736657</link><description><![CDATA[Discrete choice models (DCMs) are widely used for prediction and policy analysis, but standard multinomial logit (MNL) models with linear utility may fail to capture nonlinear response patterns in travel behavior. Neural extensions, such as deep neural network with alternative-specific utility functions (ASU-DNN), improve predictive flexibility, but their learned utility representations can be difficult to interpret and may be less stable under counterfactual shifts. This study proposes the generalized additive utility network (GAUNet) and its interaction variant, generalized additive and interactive utility network (GAIUNet), which represent systematic utility as a low-dimensional additive decomposition of learned neural shape functions. The proposed models are evaluated using synthetic transport mode choice data and real-world probe-person data collected in Tokyo, Japan, from 2018 to 2021. In synthetic experiments, GAUNet achieves predictive performance comparable to ASU-DNN and better than linear MNL, while yielding more stable policy evaluation under counterfactual changes in travel cost and access time. In real-world data, GAUNet and GAIUNet outperform linear MNL and remain competitive with ASU-DNN, while producing utility shapes that are easier to inspect at the attribute level. The results suggest that the proposed framework can recover interpretable nonlinear utility patterns without requiring cutoff locations to be specified in advance, thereby providing a transparent and flexible alternative to more entangled neural DCMs.]]></description><pubDate>Thu, 30 Jul 2026 09:59:20 GMT</pubDate><guid>http://pubsindex.trb.org/view/2736657</guid></item><item><title>Data-Driven Bridge Deck Condition Rating Prediction Using Machine Learning Models</title><link>http://pubsindex.trb.org/view/2736652</link><description><![CDATA[Bridges are integral components of transportation networks, facilitating connections and supporting traffic loads across various obstacles. While bridges are important, they are costly to maintain because of high usage and strict inspection demands. With approximately 57,000 bridges in Texas, the state requires an accurate and computationally efficient deterioration model to support informed rehabilitation and reconstruction decisions by bridge management agencies. The deteriorating condition of bridges, along with escalating maintenance and rehabilitation costs, necessitate difficult budgeting choices to ensure that bridges remain safe with a prolonged operational lifespan. Machine learning (ML) techniques have become increasingly popular for developing predictive models and assisting infrastructure management decisions. Although these approaches show strong potential, their practical application is often limited by issues such as reliance on inspection-based ratings that may carry inherent biases (1, 2) or the use of simplified or narrow classification categories (3, 4). This study addresses these limitations by selecting exclusively inventory-based features without inspection biases, using a multi-class classification approach, and thoroughly optimizing multiple ML models. Seven different ML models, including Decision Tree (DT), K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Random Forest (RF), Adaboost (AB), CatBoost (CB), and Bagged Tree (BT), were applied to the bridges within Texas. The prediction accuracy of the best model was found to be above 90%. Among the selected input features, bridge age proved to be the most significant factor affecting deck Condition Rating (CR), followed by span type and number of spans. Climate zones also showed substantial correlation.]]></description><pubDate>Thu, 30 Jul 2026 09:59:20 GMT</pubDate><guid>http://pubsindex.trb.org/view/2736652</guid></item><item><title>Comprehensive Laboratory and Field Evaluation of a High-RAP Asphalt Mixture Containing a Soybean-Based Rejuvenator at the NCAT Test Track</title><link>http://pubsindex.trb.org/view/2736650</link><description><![CDATA[This study evaluates the laboratory and field performance of a high reclaimed asphalt pavement (RAP) mixture incorporating a soybean-oil-based rejuvenator. A dense-graded asphalt mixture containing 50% RAP was designed using a balanced mix design (BMD) approach, with the optimal rejuvenator dosage selected to satisfy both cracking and rutting thresholds. Two mixtures were produced at the plant: one with rejuvenator (R) and the other with no rejuvenator (NR). Only the R mixture was paved at the National Center for Asphalt Technology test track for field evaluation, while both were tested in the laboratory. BMD test results indicated that adding the rejuvenator significantly improved cracking resistance while maintaining rutting performance within acceptable limits. Results from the stress sweep rutting test also showed lower rutting resistance for the R mixture. Nonetheless, cyclic fatigue test results indicated only slight improvement in fatigue resistance, and FlexPAVE™ pavement modeling predicted no notable difference in damage between the R and NR mixtures. Testing of extracted binders showed that the use of rejuvenator enhanced rheological behavior by reducing stiffness, increasing phase angle, and lowering the binder Glover-Rowe parameter after extended aging, which suggests improved long-term durability. After 1 year of accelerated loading, the test section paved with the R mixture exhibited excellent field performance, with no cracking, minimal rutting, and stable ride quality. These findings support the potential of the bio-based rejuvenator to facilitate higher RAP usage while achieving both performance and sustainability objectives.]]></description><pubDate>Thu, 30 Jul 2026 09:59:20 GMT</pubDate><guid>http://pubsindex.trb.org/view/2736650</guid></item><item><title>Comparative Performance Analysis of Superpave4 and Superpave5 Asphalt Mixtures in Massachusetts: Cracking Resistance, Permeability, and Mechanistic-Emperical Evaluation</title><link>http://pubsindex.trb.org/view/2736665</link><description><![CDATA[This study presents Phase II of a research study for the Massachusetts Department of Transportation (MassDOT) comparing Superpave mix design (Superpave4) and Superpave5 through laboratory testing and performance modeling. Currently, MassDOT develops mix designs with the Superpave4 method, but targets 5% field air voids; however, Superpave4, when placed in the field, typically achieves 6%–8% air voids. As a result, MassDOT increased their effective binder content by raising minimum VMA specifications, yet there were issues achieving the target voids. Therefore, Superpave5, which targets 5% air voids in both laboratory and field applications, was explored as a potential solution. Four 12.5 mm nominal maximum aggregate size mixtures were evaluated: Superpave4 with 14% and 15% VMA, and Superpave5 with 15% and 16% VMA. Building on Phase I findings that revealed inconsistent cracking tolerance index (CTIndex) behaviors between mix types, Phase II focused on intermediate-temperature cracking using Texas Overlay Test, low temperature cracking using the Thermal Stress Restrained Specimen Test (TSRST), permeability with a falling head permeability test, and performance prediction using FlexPAVE™. The Texas Overlay Test results aligned with Phase I CTIndex results. TSRST results showed no significant differences between mixture types, indicating that binder rheological characteristics influence low temperature performance rather than mix design methods. Superpave5 mixtures exhibited higher permeability than Superpave4 at equivalent air void content but remained within acceptable thresholds. FlexPAVE™ modeling confirmed superior rutting resistance for Superpave5 mixtures, while cracking simulations aligned with the CTIndex and Texas Overlay results, suggesting mixture characteristics affect cracking susceptibility along with air void levels.]]></description><pubDate>Wed, 29 Jul 2026 09:15:26 GMT</pubDate><guid>http://pubsindex.trb.org/view/2736665</guid></item></channel></rss>