<?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" 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>Scalable Traffic Volume Estimation Using Probe Vehicle Data and Penetration Rate Modeling: Large-Scale Implementation</title><link>http://pubsindex.trb.org/view/2719397</link><description><![CDATA[Accurate, network-wide traffic volume data is essential for effective transportation planning and policy development. While traditional count stations offer reliable measurements, the high cost of their installation and maintenance limits full network coverage. Existing estimation methods often rely on sparse or outdated data, constraining their scalability and accuracy. This study introduces a novel framework that integrates probe vehicle data, stationary counts, and machine learning to estimate traffic volumes via modeled penetration rates. Penetration rates are first computed at locations with observed data and filtered using the interquartile range method to remove outliers. These rates are then used to train an XGBoost model, with Shapley additive explanations employed to assess feature importance and enhance model interpretability. The framework was validated on 675 road segments in Edmonton, Alberta, with 95.11% of observations retained as valid data. A network-wide mean absolute percentage error of 18.19% was achieved, with higher accuracy observed on high-volume roads. These results demonstrate the framework’s scalability and utility for large-scale traffic volume estimation in data-scarce environments, offering transportation agencies a cost-effective alternative to sensor-based monitoring for infrastructure planning and investment prioritization.]]></description><pubDate>Mon, 29 Jun 2026 09:20:07 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719397</guid></item><item><title>Evaluating the Reliability and Consistency of Statistical Models for Speed Distribution Analysis at Hazardous and Non-Hazardous Roadway Locations: Multifraction Data Set Approach</title><link>http://pubsindex.trb.org/view/2719396</link><description><![CDATA[Understanding the statistical dynamics of traffic speeds at hazardous and non-hazardous locations is essential for effective roadway safety interventions. This study investigates the distinct characteristics of spot speed distributions across six Indian highway segments, including National and State Highways. It uses continuous probability distributions and hypothesis testing to assess the statistical significance of speed differences between hazardous and non-hazardous locations. The analysis is based on observed spot speed measurements, stratified into four data fractions (25%, 50%, 75%, and 100%), obtained using a simple random sampling with replacement approach. Seven continuous probability distributions, including normal, lognormal, gamma, logistic, Weibull, Burr, and generalized extreme value (GEV), have been fitted independently for each location type and data fraction to capture their distributional characteristics. The location, scale, and shape parameters of the models have been estimated using maximum likelihood estimation. However, model adequacy has been confirmed using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values. Furthermore, a two-sample Kolmogorov–Smirnov test has been conducted to assess the statistical difference in speed profiles between hazardous and non-hazardous locations. The results reveal that the GEV distribution consistently outperforms other models across all locations and data fractions, demonstrating strong parameter stability and model adequacy. Larger data fractions improved model performance and hypothesis testing power, indicating greater distributional robustness. To address the potential effect of vehicle interactions and transient congestion during the observation periods, a modified Kaplan–Meier (KM) framework is used to estimate congestion-adjusted desired speed distributions. The KM-based findings show that hazardous roadway locations exhibit higher desired speed potential and greater upper-tail speed characteristics compared with non-hazardous locations. Interestingly, statistically significant speed differences have been found in nearly all settings, confirming the notion that crash-prone zones exhibit distinct speed dynamics. These findings have significant implications for road safety policy and infrastructure design, as well as the need for location-specific speed management strategies.]]></description><pubDate>Mon, 29 Jun 2026 09:20:07 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719396</guid></item><item><title>Pedestrian Signing at Uncontrolled Crosswalks</title><link>http://pubsindex.trb.org/view/2719395</link><description><![CDATA[Currently, the Manual on Uniform Traffic Control Devices for Streets and Highways recommends that the type of sign used at a pedestrian crosswalk be a warning sign instead of a regulatory sign. The same sign—a pedestrian crossing (W11-2) warning sign—can be used in advance of a pedestrian crosswalk. This article describes an FHWA project that aimed to develop and evaluate alternatives to the W11-2 sign for use at crosswalks. The research team investigated regulatory sign alternatives through human factors testing using a computer-based test (CBT) and in-field evaluations by observing driver yielding. The CBT showed that regulatory sign alternatives that included explicit commands (e.g., “Yield To”) were preferred and understood better than warning sign versions. Based on the CBT results and discussions with the project stakeholders, two signs were selected for the field test to compare with a base condition of the typical W11-2 sign. The field test signs included either the stop symbol or the stop word along with the word “for” and a walking pedestrian symbol within crosswalk lines. The sign shape was rectangular with a white background. The findings from field studies revealed similar driver yielding for the three signs tested. Stated in another manner, the test signs (regulatory with black text on a white background with a rectangular shape) developed in this research and the sign currently used at pedestrian crossings (warning with black text on a yellow background with a diamond shape) had a similar impact on a driver’s decision to yield or not yield to a crossing pedestrian.]]></description><pubDate>Mon, 29 Jun 2026 09:20:07 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719395</guid></item><item><title>Successful Approaches to Protecting Electrical and Communications Infrastructure Within Highway Rights-of-Way</title><link>http://pubsindex.trb.org/view/2714466</link><description><![CDATA[Copper theft and vandalism of critical and sensitive highway electrical and communications infrastructure poses a serious issue for the Departments of Transportation (DOTs) across the nation, their partner emergency services, utilities, and the public. This NCHRP U.S. Domestic Scan sought practices, emerging technologies, and organizational arrangements highly successful in protecting assets and deterring illicit activities. The scan team reviewed existing literature and held workshops with select state DOTs, urban local agencies, utilities, law enforcement, and the private industry to identify promising actions, cooperative efforts, and case studies that can be replicated for successful outcomes elsewhere. This scan finds that multidisciplinary public-private sector task forces, consistent statutes, and enhanced resources for real-time detection and enforcement capabilities are important elements to addressing the issue. It also finds that more efforts are needed to ascertain the true costs of copper theft and communications vandalism. If successful, these approaches will better ensure public safety, critical services, and societal resilience.]]></description><pubDate>Sat, 27 Jun 2026 15:38:38 GMT</pubDate><guid>http://pubsindex.trb.org/view/2714466</guid></item><item><title>Best Practices In Regional, Multiagency Traffic Signal Operations Management</title><link>http://pubsindex.trb.org/view/2714407</link><description><![CDATA[This report summarizes the findings from a scan workshop of domestic regional traffic signal operations programs in the United States. The scan’s purpose was to examine the different types of organizational structures, institutional agreements and arrangements, and operational policies that organizations throughout the United States use to manage and operate traffic signal systems from a regional perspective. Representatives from 17 different agencies met with the scan team in a peer exchange format over a three-day period to discuss how their agencies developed and sustain their regional traffic signal programs.]]></description><pubDate>Sat, 27 Jun 2026 15:38:38 GMT</pubDate><guid>http://pubsindex.trb.org/view/2714407</guid></item><item><title>Leading Practices for Cost-Effective Vegetation Management Within Highway Rights-of-Way</title><link>http://pubsindex.trb.org/view/2714462</link><description><![CDATA[From the simple idea of planting tall native wildflowers to control weeds, to detailed analysis – and large plantings – of native plant communities on highway rights-of-way, state departments of transportation (state DOTs) are increasing the use of native vegetation in their operations. This scan report summarizes practitioner observations and provides the following: 1. It offers definitions of the terms “native vegetation” and “locally native vegetation.” Just as the saying “Beauty is in the eye of the beholder” means beauty looks different to different people, so, too, do the terms “native” and “locally native” look different to different people. Standard definitions for these terms will make it easier for state DOTs to use more native vegetation. 2. It identifies findings and recommendations to help state DOTs better protect existing native vegetation on rights-of-way and aid in using more native vegetation in revegetation work. Although nearly all the research and practice, which this domestic scan identified with native vegetation and rights-of-way, is based on highway roadsides, the best practices identified in this domestic scan could be adapted to railroad or dedicated bicycle/pedestrian rights-of-way.]]></description><pubDate>Sat, 27 Jun 2026 15:38:38 GMT</pubDate><guid>http://pubsindex.trb.org/view/2714462</guid></item><item><title>Sustainable Mobility Readiness Index: Evaluating Global Metropolitan Areas’ Passenger Mobility and Logistics Performance</title><link>http://pubsindex.trb.org/view/2717791</link><description><![CDATA[Metropolitan areas are nowadays facing rapid growth and technological transformation, thereby creating complex challenges concerning the adoption of sustainable passenger and freight mobility technologies. Current evaluation frameworks typically address attributes of urban transport separately, focusing narrowly on specific modes, technologies, or sustainability dimensions. This study establishes the Sustainable Mobility Readiness Index (SMRI), an innovative and comprehensive framework that is designed to evaluate the preparedness of metropolitan areas concerning the adoption of sustainable, inclusive, and innovation-driven mobility systems. The SMRI integrates six key dimensions (transport supply, transport demand, innovation, policy, finance, and environment and energy) captured through 64 indicators, while also emphasizing the dual importance of passenger and freight transport readiness. Further, it applies a structured, multistage methodology incorporating expert-informed weighting, normalized scoring, and sensitivity analysis to assess 26 global metropolitan areas. Therefore, the SMRI addresses notable gaps in current literature by showcasing a geographically adaptable, interdisciplinary, and data-driven benchmarking tool. Results indicate a significant variance in readiness levels across cities and underline opportunities for peer learning and targeted investment. In addition, the study portrays a typology of metropolitan areas (mature, emerging, and developing) based on context-specific characteristics and performance patterns. While the SMRI offers a robust basis for evidence-based policymaking, it also acknowledges data limitations and identifies opportunities for future development of new mobility technologies, including spatial analysis and the incorporation of equity and accessibility metrics. As metropolitan mobility systems continue to evolve, the SMRI provides a timely contribution to the planning and policy analysis of sustainable transport transitions worldwide.]]></description><pubDate>Fri, 26 Jun 2026 14:00:16 GMT</pubDate><guid>http://pubsindex.trb.org/view/2717791</guid></item><item><title>Energy-Efficient Control of Connected Autonomous Electric Vehicles in Mixed Traffic with Human-Driven Vehicles</title><link>http://pubsindex.trb.org/view/2719394</link><description><![CDATA[Signalized intersections are recognized as traffic bottlenecks that increase vehicle stops, leading to frequent acceleration events on urban roads and potentially elevating overall fuel consumption when red signals are encountered. With advances in emerging technologies, connected autonomous vehicles (CAVs) can be optimally controlled to improve energy efficiency while accounting for future traffic constraints. In mixed traffic environments, a controlled CAV can directly influence the energy efficiency of following human-driven vehicles (HVs) because of car-following behavior. This paper considers the CAV and its following HV simultaneously in the design of energy-efficient vehicle control strategies. By leveraging traffic prediction results, the speed trajectory and powertrain operation of a connected autonomous electric vehicle (CAEV) is co-optimized, explicitly accounting for multiple HVs behind it. Simulation results show that the total energy savings of a vehicle platoon increased from 7.47% to 10.05% as the number of HVs considered in the optimization rises from zero to five. Furthermore, the effect of multiple CAEVs on platoon-level energy efficiency is comprehensively analyzed, with improvements from 8.1% to 15.2% when multiple HVs follow each CAEV.]]></description><pubDate>Fri, 26 Jun 2026 08:40:59 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719394</guid></item><item><title>Factors Influencing Road User Behaviors and Motivations Around Pedestrian Hybrid Beacons and Rectangular Rapid Flashing Beacons in North Carolina</title><link>http://pubsindex.trb.org/view/2719393</link><description><![CDATA[The safety and operational effectiveness of pedestrian hybrid beacons (PHBs) and rectangular rapid flashing beacons (RRFBs) are well established. However, their performance depends on pedestrians actuating these traffic control devices before crossing. Past research has mostly evaluated drivers yielding to these devices using staged crossing protocols. Further research studying how real-world pedestrians and drivers use these devices is needed. We use field video footage data to investigate factors linked to road user behaviors at pedestrian crossings and a survey of pedestrian attitudes and motivations at urban locations in North Carolina. Among other findings, we found evidence of a link between pedestrian refuges and increased actuation and yield rates, whereas pedestrian and driver behaviors worsen at crossings where a sidewalk is absent on one side. We found higher odds of yielding for PHBs, while pedestrians were less likely to actuate those devices compared with RRFBs. In general, factors such as increased traffic and longer crossing distances were associated with more actuations. Survey responses indicated that conditions and roadway elements that increase friction or safety risk during the crossing (heavy traffic, fast cars, and longer crossing distances) motivate pedestrians to actuate the devices more frequently. A comparison of pedestrian waiting times showed that pedestrians experienced 52.0% shorter wait times at actuated RRFBs compared with actuated PHBs, a finding that might help explain the higher rates of actuation at RRFB sites.]]></description><pubDate>Fri, 26 Jun 2026 08:40:59 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719393</guid></item><item><title>Mandatory Construction Temperature as a Specification for Integral Abutment Bridges</title><link>http://pubsindex.trb.org/view/2719392</link><description><![CDATA[Integral abutment bridges (IABs) experience significant cyclic thermal movements induced by fluctuating temperatures. The pattern and maximum value of these movements depend on bridge properties, specific locality of bridge, and the initial temperature when the bridge starts behaving integrally, called the installation temperature or construction temperature (CT). Current practices mostly focus on design temperatures and lack standardized requirements for initial CT. Potential discrepancies may arise because specifications for design temperatures have a tacit assumption that CT is grossly near the middle of the extreme bridge temperatures. However, actual CT can significantly deviate from this tacit assumption during the construction phase because it is mostly not mandated. Consequently, bridge movements may become significantly asymmetrical and unwanted. This study addresses this gap by proposing a practical and easily applicable methodology for setting and mandating CT as a specification to be jointly implemented during in both design and construction of IABs. The output of the proposed method is a tight range for CT, applicable to most days without significant adverse effects in construction scheduling. Attaching the CT as a criterion into design protocols may result in enhanced predictions of thermal displacements and internal forces within IABs. Ultimately, theoretical assumptions can be connected to their practical implementation. As a result, valuable insights and actionable recommendations may be achieved to enhance the reliability, longevity, and efficiency of IABs through overall performance improvements. The methodology presented can also be used for other structures where thermal displacements are of concern.]]></description><pubDate>Fri, 26 Jun 2026 08:40:59 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719392</guid></item><item><title>Automated Bridge Deck Health Evaluation Aligned with National Bridge Inventory Ratings via Unmanned Aerial Vehicle Imaging and Label-Free Sparse Autoencoder-Based Anomaly Mapping</title><link>http://pubsindex.trb.org/view/2719391</link><description><![CDATA[Bridge deck deterioration poses a critical threat to structural safety and public transportation systems, necessitating scalable and objective inspection methods. This study presents a lightweight, unsupervised anomaly detection framework that leverages unmanned aerial vehicle (UAV)-acquired imagery and sparse autoencoders to evaluate bridge deck surface conditions without requiring labeled training data. High-resolution images captured using a UAV were divided into 64 × 64 patches and processed through a sparse autoencoder trained solely on healthy concrete patches to learn a compact representation of normal surface texture. During testing, reconstruction error was computed for each patch, with elevated errors indicating potential anomalies such as cracks, delamination, or staining. These error values were visualized through heatmaps and aggregated across all patches to derive three condition quantification metrics: average reconstruction error, anomalous area percentage, and normalized severity score. A novel classification scheme empirically mapped these metrics to National Bridge Inventory (NBI) deck condition ratings, offering an interpretable, standardized evaluation of bridge decks. To analyze the model’s robustness and threshold sensitivity, experiments were conducted on eight bridges, showing high agreement with NBI deck condition ratings, achieving up to 87.5% rating classification accuracy. Moreover, threshold sensitivity analysis revealed how rating transitions occur across scoring levels, further highlighting the model’s adaptability. Overall, the proposed approach enables efficient, interpretable, and defect-annotation-free bridge condition assessments, aligning with federal standards while significantly reducing the labor requirements, subjectivity, and data annotation burdens of traditional inspections. It represents a promising step toward scalable, automated infrastructure health monitoring using autonomous aerial systems.]]></description><pubDate>Fri, 26 Jun 2026 08:40:59 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719391</guid></item><item><title>Factors Influencing Rural Freight Transport in Bangladesh: Insights from Generalized Linear and Additive Models</title><link>http://pubsindex.trb.org/view/2719390</link><description><![CDATA[Freight transportation is an important research topic in the transportation domain of high-income countries, but middle-income and low-income countries lack quality research on this, especially for heterogeneous roadway freight movement on narrower rural roads. This study addresses this issue in northern Bangladesh, analyzing the volume of five dedicated freight vehicle types across 1,162 roadway segments. A negative binomial generalized linear model (NB-GLM), along with a supporting negative binomial generalized additive model (NB-GAM), was found suitable to better explain the interrelation between freight volume and different predictors like area, population, household size, solvency rate, crest width, embankment height, and international roughness index. Freight movement was notably higher on market days. The NB-GLM highlighted significant linear effects of socioeconomic attributes, whereas the NB-GAM revealed strong nonlinear influences of roadway and spatial characteristics. Distinct variations were observed for predictor significance in statistical terms across different vehicle classes. These findings serve as a decision-support tool for policy makers wanting to implement targeted interventions, including temporal zoning, last-mile surface funds, and village freight consolidation hubs. The results provide a robust framework for predicting freight movements in regions with similar economic conditions, aiding in sustainable road network development and maintenance planning.]]></description><pubDate>Fri, 26 Jun 2026 08:40:59 GMT</pubDate><guid>http://pubsindex.trb.org/view/2719390</guid></item><item><title>Enhancing Wind Field Prediction and Reconstruction around Windbreak Walls along High-Speed Railway by Advanced Neural Network Architectures: Accuracy and Stability Assessment</title><link>http://pubsindex.trb.org/view/2717202</link><description><![CDATA[Accurate prediction of wind fields around high-speed railway (HSR) infrastructure is critical for operational safety and energy efficiency. This study evaluates neural network approaches for predicting wind fields around HSR windbreak walls, focusing on transformer models. Field measurements were conducted using 15 anemometer masts arranged inside and outside windbreak walls on the Lanzhou–Xinjiang railway. We compared multiple deep learning architectures (multilayer perceptron, long-short-term memory, temporal convolutional network and transformer) for predicting interior wind conditions based on exterior measurements. The key findings are summarized as follows: (1) prediction accuracy improved substantially with longer historical contexts (10–60 timesteps); (2) significant spatial variability exists in wind predictability across measurement locations; (3) feature importance analysis identified critical measurement points, enabling cost-effective maintenance strategies and optimized sensor deployment; and (4) sequence mean filling performed best among the three tested strategies for handling missing data, maintaining positive predictive power even with substantial sensor loss. Among these models, the transformer model achieved the best overall performance (𝘙² = 0.9665 at 𝘛 = 60), with its advantage becoming most pronounced at longer historical contexts. These findings have important implications for railway safety and wind energy applications, enabling more efficient monitoring networks and robust forecasting systems. The demonstrated effectiveness of transformer models represent a significant advancement in applying attention-based architectures to infrastructure monitoring challenges.]]></description><pubDate>Wed, 24 Jun 2026 10:29:07 GMT</pubDate><guid>http://pubsindex.trb.org/view/2717202</guid></item><item><title>Effects of Inert and Active Fillers and Their Physicochemical Properties on Asphalt Mixture Performance</title><link>http://pubsindex.trb.org/view/2717195</link><description><![CDATA[The primary objective of this study is to assess the impact of various inert and active fillers, along with their physicochemical properties, on the laboratory performance of asphalt mixtures. To achieve this objective, various fillers, including active fillers derived from industrial wastes, are sampled, processed, and evaluated. Two state-approved asphalt mixes, a stone matrix asphalt (SMA) and a surface mixture, were selected. For each selected filler, the study characterizes its physical and chemical properties and its influence on the mixture’s laboratory performance against major distresses, specifically, rutting, durability, moisture resistance, and cracking. Results indicate an acceptable correlation between the physical and chemical characteristics of the fillers and the performance of the mixes prepared with these different filler materials. Concerning laboratory-mixed performance, mixes containing industrial fillers, particularly fly ash and steel slag, exhibit better rutting and cracking performance than the control mixes for SMA and surface mixes. In relation to durability, the control mix and steel slag appear to enhance the durability of the surface mixtures. SMA, on the other hand, consistently demonstrates robust performance across filler types. For moisture-damage resistance, the tensile-strength ratio is higher for the different industrial filler materials, especially fly ash and steel slag, than for the control filler. In summary, this study recommends using fly ash and steel slag powder as replacements for mineral fillers in asphalt mixtures. These industrial waste-derived fillers are found to outperform conventional fillers while allowing the reuse of industrial waste in the road infrastructure.]]></description><pubDate>Wed, 24 Jun 2026 10:29:07 GMT</pubDate><guid>http://pubsindex.trb.org/view/2717195</guid></item><item><title>Agent-Based Urban Freight Modeling: Lessons Learned from the Literature and a Framework for Passenger–Freight Integration</title><link>http://pubsindex.trb.org/view/2717194</link><description><![CDATA[Freight transportation is an essential component of urban systems, as it supports economic activity and provides consumer services. However, current urban freight models are often disconnected from passenger transport simulations. This separation limits their ability to support integrated policy analysis, especially in the context of shared infrastructure and rising e-commerce demand. This study conducts a comprehensive review of agent-based urban freight modeling literature, focusing on behavioral realism, integration with passenger models, and representation of logistics processes. Key limitations are identified, including the absence of consistent agent structures, decision hierarchies, and insufficient alignment with land-use and emission models. Existing frameworks often treat freight activity in isolation, lack temporal depth, and fail to represent cross-sector interactions such as those driven by online shopping. To address these limitations, this study presents an integrated conceptual framework that embeds urban freight modeling within an existing agent-based urban system simulation platform. The extended framework introduces logistics actors such as shippers, carriers, receivers, and consumers. It incorporates them across long-term, medium-term, and short-term decision modules. Freight decisions, including firm transitions, fleet strategies, logistics planning, and delivery scheduling, are modeled in alignment with passenger systems. The integration occurs within a shared simulation environment, where freight and passenger activities interact through a common traffic flow simulator and virtual activity schedules. This framework enables behaviorally consistent and policy-sensitive simulation of urban mobility systems, particularly in the context of e-commerce-driven freight demand. Results of this study provide a foundation for future development of integrated models capable of supporting strategic planning, emission reduction, and multimodal transport policies.]]></description><pubDate>Wed, 24 Jun 2026 10:29:07 GMT</pubDate><guid>http://pubsindex.trb.org/view/2717194</guid></item></channel></rss>