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Vertical split rims (VSRs) are one of the leading causes for wheel removals in North American freight rail service. The Federal Railroad Administration funded a research effort in which a group of researchers and subject matter experts explored a better understanding of VSRs using finite element analysis. The analysis was intended to identify the relative contributions of factors that can lead to VSR failures with a goal of establishing approaches to minimizing derailments associated with these wheel failures. In February 2016, researchers established a multi-phase research program to comprehensively understand various wheel failure mechanisms, identify major contributing factors, arrive at potential strategies to mitigate the failures, and consequently improve the safety of rail network operations. Since the beginning of this effort, research has been conducted under the guidance of a stakeholder working group made up of members of the Association of American Railroads, North American wheel manufacturers, and researchers.

State departments of transportation (DOTs) face a critical and growing gap in their bridge inspection workforce. Traditional on-the-job (OTJ) and instructor-led training models, while essential, are becoming increasingly difficult to scale because the experts who deliver them are leaving the workforce. In addition, classroom training alone cannot capture the tacit, context-dependent judgment that experienced inspectors rely on every day.

TRB’s NCHRP IDEA Final Report for Project 260, Bridges to the Future: Training Inspectors with Simulation-Based Interactive Storytelling, describes a simulation-based training platform that uses interactive storytelling to accelerate the development of entry-level bridge construction inspectors by immersing them in realistic, branching scenarios built from the tacit knowledge of senior inspectors. The platform addresses reinforcing steel placement, bearing pile driving, and post-construction inspection.

The platform supports dual-platform deployment, delivering training as both a desktop video game for standard PCs and an augmented reality experience using the Microsoft HoloLens 2 head-mounted display. It also includes a replicable methodology and open-source toolkit, including the interview protocol, narrative construction template, assessment instruments, and complete Unity codebase, that state DOTs can use to develop their own training scenarios tailored to their inspection priorities, enabling them to reuse and expand the platform without rebuilding it from scratch.

Truck travel time reliability (TTTR) is one of the most important performance measures for assessing freight movement on the interstates. The Virginia Department of Transportation (VDOT) and the Virginia Office of Intermodal Planning and Investment have been reporting TTTR and setting performance targets as required by the Federal Highway Administration, as well as using TTTR in various project planning and performance measurement processes. This study aims to identify the locations and potential influencing factors of unreliable truck travel time, evaluate the effect of influencing factors, and develop models to predict the TTTR index for interstate highways in Virginia.

Using 7 years of probe speed and travel time data from the National Performance Management Research Data Set together with traffic volume, roadway, incident, and weather data maintained by VDOT, this study conducted descriptive and regression analyses to characterize the trends of TTTR and developed a hierarchical Bayesian model and random forest models to analyze and predict TTTR.

Hierarchical Bayesian models and random forest models achieved similar prediction performance, but the Bayesian model provides credible intervals for segment-level and network-level predictions to help VDOT planners better account for uncertainty in performance target setting and project planning. Traffic volume, crash frequency, the number of through lanes, and posted speed limit are the most significant factors in the Bayesian models and random forest models.

The study recommends that VDOT use the hierarchical Bayesian model to supplement the current method for setting freight reliability targets. Researchers developed an implementation plan that includes stakeholder engagement and technical assistance for the 2026–2029 performance cycle.

The U.S. transit bus market is heavily strained by extensive vehicle customization, where individual transit agencies frequently order small, highly bespoke batches of buses to fit local climates or legacy fleet inventories. While locally logical, this fragmentation destroys economies of scale in an already small market (fewer than 5,000 heavy-duty buses sold annually), resulting in inflated prices—such as a $995,000 median cost for battery-electric buses—and prolonged delivery times that far exceed more standardized, lower-cost international peers like Europe and India. To stabilize this fragile industry as vehicles grow more technologically complex, the report outlines six coordinated recommendations for Congress, the Federal Transit Administration (FTA), and transit agencies. These strategies aim to build procurement capacity, increase price transparency, require agencies to formally justify non-standard designs, and introduce federal financial incentives to reward standardized purchasing without forcing a rigid, one-size-fits-all manufacturing mandate.

Dwell time is the time a bus spends serving passenger movements, including the time required to open and close doors and boarding lost time. Passenger service time is the largest component of dwell time and is influenced by several factors, including passenger demand, fare payment method, vehicle configuration, passenger load, door and door channel usage, and platform configuration.

TCRP Research Results Digest 116: Recent Research on Bus Dwell Time Factors, produced by TRB's Transit Cooperative Research Program, explores recent research on dwell time factors developed since the Transit Capacity and Quality of Service Manual (TCQSM), 3rd Edition was published. This research informed updates to Chapter 6 of the TCQSM, 4th Edition. The digest describes one of 12 small research tasks conducted to support the development of new content for the 4th Edition.

To combat expensive bridge deterioration caused by corrosion, this project investigated the feasibility of using dissimilar metal welds (DMWs) to protect highly corrosive locations while minimizing initial fabrication costs. The research evaluated welding corrosion-resistant steels—specifically ASTM A709 Grade 50CR and a potential alternative, ATI 412—to standard structural bridge steels (ASTM A36 and ASTM A709 Grade 50W). Initial weldability evaluations indicated that these DMWs are highly susceptible to solidification and cold cracking. However, researchers determined that utilizing lower heat input and a single-V with backgouge weld joint successfully eliminated these defects, allowing the crack-free DMWs to ultimately meet the mechanical property requirements of the AASHTO/AWS D1.5 Bridge Welding Code.

Despite satisfying basic mechanical standards, the DMWs exhibited severe vulnerabilities during corrosion and non-destructive evaluation (NDE) testing. The material combinations suffered from accelerated galvanic, pitting, and intergranular corrosion, particularly within the heat-affected zones of the weld interfaces. Furthermore, standard NDE inspection methods proved highly unreliable; radiographic testing produced artifacts that could mask flaws, while ultrasonic and phased array testing suffered from anisotropic behavior and wave refraction that caused defects to be mislocated or missed entirely. Consequently, because of these persistent corrosion and inspection challenges—compounded by long lead times and recent quality issues with 50CR steel—the Virginia Transportation Research Council recommends that VDOT avoid utilizing 50CR/412 steel in DMWs and continue to exercise caution when specifying 50CR steel to manage project risk.

This research evaluated the effectiveness of nighttime construction lighting systems in improving worker visibility and safety while minimizing glare impacts on motorists in Nebraska work zones. The study combined an industry survey with controlled field testing to assess current lighting practices and quantify lighting performance. Survey responses from construction professionals documented commonly used lighting systems, perceived adequacy, safety impacts, and public concerns related to glare. Field experiments were conducted at the Midwest Roadside Safety Facility using LED, halogen, and balloon light towers. Lighting configurations were systematically varied by mounting height, aiming angle, and rotation angle. Worker visibility was evaluated using horizontal illuminance based on Federal Highway Administration recommendations, and driver glare was assessed using veiling luminance ratios in accordance with Illuminating Engineering Society RP-8-22 standards. Results indicate that lighting performance depends primarily on configuration rather than lighting type alone, and only a limited number of configurations satisfied both illuminance and glare criteria. The findings can be used to guide safer nighttime work zone lighting setup and support the development of NDOT-specific lighting recommendations.

This study highlights that Inductive Loop Detectors (ILDs), sensors embedded into the pavement for traffic control, are concerningly vulnerable to novel cyber and physical attacks.

Probe data are increasingly being adopted by transportation professionals in the United States as a means to better measure the mobility of Americans across and within the national transportation system. Centered on new, rapidly changing forms of technology that allow mobile devices to actively determine and share their locations with analysts as a novel form of big data, probe data offer exciting advantages for measuring mobility, but they rely on technologies and methods that are not transparent to their users or members of the public. This report offers a statistics-centered definition of probe data, contrasts them with non-probe data, notes common data subtypes, discusses their advantages and limitations, summarizes their history, and proposes ways to differentiate noted subtypes. This report accompanies a set of six user guides on specific probe data types.

Federal agencies increasingly use cloud computing to perform their missions. Cloud services provide benefits, including on-demand access to shared resources such as networks, servers, and data storage, and can enable agencies to deliver IT services more efficiently. Additionally, cloud services can provide agencies with opportunities to obtain IT capabilities more quickly and potentially at a lower cost than building and maintaining their own computing infrastructure. In pursuing these benefits, agencies may also encounter various risks and challenges, such as managing shared cybersecurity responsibilities with the provider.

This review determined the extent to which selected agencies are ensuring contractor compliance with key cloud computing security practices. To address the objective, researchers identified a non-generalizable sample of four Chief Financial Officers Act agencies based on the number of cloud authorizations issued, excluding agencies selected in recent GAO reports. Using the median number of authorizations, agencies were randomly selected with two at or above, and two below the median: Departments of State, Transportation, Veterans Affairs (VA), and the Small Business Administration (SBA).

Several state departments of transportation have integrated mobile road weather information sensors (RWIS) and maintenance decision support systems (MDSS) to improve the performance of their winter maintenance operations. The main goal of this research project is to conduct a multi-year field study to evaluate the effectiveness of integrating mobile RWIS and MDSS into existing Illinois Department of Transportation (IDOT) winter maintenance operations. The project focused on eight research tasks. Tasks 1 through 3 comprised identifying IDOT study participants for the deployment of mobile RWIS units and MDSS; selecting, acquiring, installing, calibrating, and providing training on 12 mobile RWIS units acquired from three manufacturers; and conducting a multi-year field evaluation of mobile RWIS units and MDSS during three consecutive winter seasons to assess their operational performance and effectiveness. Salt usage data were collected and analyzed in Task 4 through pairwise comparisons of snowplows with and without mobile RWIS units and MDSS to evaluate their effectiveness in reducing salt usage and improving roadway conditions. Surveys and follow-up interviews with winter maintenance personnel were conducted in Task 5 to gather and analyze feedback on the use, benefits, and operational challenges of mobile RWIS units and MDSS. Tasks 6 through 8 comprised evaluating the cost-effectiveness of the three mobile RWIS models and MDSS, identifying additional uses for mobile RWIS units, and developing recommendations for future deployment and use of mobile RWIS units and MDSS across Illinois.