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Factsheet presenting crash statistics from the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS) focusing on children (persons aged 14 and under).

Precast/prestressed concrete girders with cast-in-place decks are commonly used for bridge construction throughout the United States. However, girder lifespans exceed the lifespans of concrete decks, resulting in the need for deck replacement. This study surveyed United States Department of Transportation (DOT) engineers to determine common deck removal practices. Survey results showed that, although most states have a need to replace bridge decks, few states have comprehensive plans for assessing the long-term effects of deck replacement on girder behavior. This study developed a Python model to estimate girder behavior over its lifespan that accounts for the effects of deck replacement, changes in loading conditions, changes in restraint conditions, and concrete deformations. Time-step analysis was used to calculate incremental changes in girder behavior throughout time, considering several lifespan stages delineated by changes in loading or boundary conditions. The B4 model (Wendner et al., 2013) was used to estimate the creep and shrinkage strain in the concrete. The model was validated against examples in the literature and applied to an example bridge to illustrate function. Modeling results suggest that deck replacement had minimal effect on long-term girder behavior for the bridge considered. A parametric study was also conducted to evaluate the influence of input parameter variations on long-term prestress loss, deflections, and stresses and strains for the example bridge. Parametric study results showed that girder behavior varies widely based on input parameters, suggesting that more research is needed to determine whether other bridge configurations would also be insensitive to deck replacement.

This research focused on the utilization of Light Detection and Ranging (LiDAR) technology within the Louisiana Department of Transportation and Development (DOTD) for various geotechnical applications. The study addressed several key practices, including site investigation and reconnaissance for drilling operations, geotechnical asset management inventory data collection, change detection for forensic evaluations and monitoring, and cross-section data collection for stability analysis. The primary objective of the research was to leverage LiDAR technology to enhance geotechnical infrastructure management within DOTD. The investigation involved a comprehensive analysis of available data within DOTD and other relevant Louisiana agencies. Additionally, the study explored the integration of LiDAR with other data sources and collection technologies, such as drones for local scanning. The research findings contribute to the identification and implementation of LiDAR technology in geotechnical infrastructure, providing valuable insights into its efficacy and potential benefits. By harnessing LiDAR for site investigation and reconnaissance during drilling operations, the study aims to improve the accuracy and efficiency of data collection in challenging terrains. Further, the research explored the role of LiDAR in geotechnical asset management, emphasizing the importance of inventory data collection. Through change detection techniques, LiDAR proves to be a valuable tool for forensic evaluations and continuous monitoring of geotechnical assets, facilitating proactive maintenance and risk mitigation. The study also explores the application of LiDAR in cross-section data collection for stability analysis. By assessing terrain morphology and structural integrity, LiDAR contributes to a more thorough understanding of geotechnical conditions, enabling better informed decision-making for infrastructure stability and resilience. In conclusion, the research underscores the potential of LiDAR implementation in geotechnical applications within DOTD, offering a sustainable and resilient approach to infrastructure management. The insights gained from this study have the potential to enhance DOTD’s capabilities in site investigation, asset management, and stability analysis, ultimately contributing to the longterm sustainability of geotechnical assets.

Ultra-high performance concrete (UHPC) has been used in different applications and was explored to be
used for precast elements; however, there was limited research and guidance on the connection between UHPC
elements. General test methods to evaluate interface strength (e.g., direct tension pulloff, shear pushoff) can be
used with the Mohr-Coulomb Friction Approach to determine the cohesion coefficient and coefficient of friction
typically used to estimate interface shear strength. The test program here sought to explore the bond behavior of
matchcast UHPC with various interface surface conditions, such as surface roughness (including smooth faces
cast on plywood formwork, roughened surfaces created by casting on form liners) and exposed steel fibers at the
interface (created by the use of paste retarders) in order to inform design provisions for matchcast UHPC. The
effect of pre-corroded steel fibers and the surface wetting conditions were considered as well. Trends in interface
shear behavior associated with surface conditions were identified. The most evident outcome from testing was
that the presence of exposed steel fibers provided improved performance relative to only roughened surfaces.
Roughened interfaces can improve the friction of the interface, but the presence of the exposed fibers improved
both cohesive strength and provided improvement to the post-crack tensile strength. Additionally, there was
improved cohesive bonding when prolonged wetting by burlap was made. Extended term ponding had reduced
performance. Cohesion coefficient and friction factors for the various test conditions were assessed. Modification
to interface shear strength provisions to include the effect of wetting conditions on cohesion was presented. The
experimental work provided practical experiences that were translated into considerations for construction.

As the Virginia Department of Transportation (VDOT) transitions from traditional in-pavement sensors to non-intrusive traffic
monitoring technologies, a standardized and mathematically defensible verification process is required to ensure data integrity.
This research establishes a comprehensive Device Acceptance Framework designed to evaluate the volumetric and classification
accuracy of emerging traffic count devices.

The framework was developed through a multi-stage methodology. First, a user needs survey involving VDOT stakeholders
established a 5% error threshold as the primary accuracy target for engineering and planning applications. Second, a robust
operational baseline was established by calibrating existing continuous count stations against absolute, human-verified video
ground truth data.

Third, the established baseline and parameters were integrated into a formal eight-step “fail-fast” protocol. This protocol subjects
candidate devices to progressive evaluations, ranging from simple 24-hour volumetric screenings to rigorous classification tests
under adverse environmental conditions (e.g., heavy rain, dense fog, and snow). A field demonstration of the framework on a
candidate video-based detector illustrated its practical application and the effectiveness of the pass-fail criteria.

The implementation of this framework provides significant operational and financial benefits. By utilizing the pre-calibrated
continuous count station baseline instead of manual video processing, VDOT can achieve a direct cost avoidance of
approximately $321,300 per device certification request. Furthermore, the framework establishes a transparent roadmap for both
the agency and technology vendors, ensuring that only resilient, high-accuracy tools are deployed across Virginia’s traffic
monitoring network. The study recommends developing a standardized traffic count device acceptance procedure, particularly the
“fail-fast” framework to establish a consistent, resource-efficient vetting process for emerging non-intrusive traffic count devices
for VDOT approval.

The American Association of State Highway and Transportation Officials (AASHTO) publishes the Transportation Operations Manual (TOM), which provides a holistic view of transportation systems management and operations (TSMO) and encompasses a broad range of topics and tactics within the discipline.

NCHRP Web-Only Document 472: Transportation Systems Management and Operations: Implementation Guide, produced by TRB’s National Cooperative Highway Research Program, complements the TOM by providing effective practices and other resources that illustrate the practical application of operations topics, concepts, and strategies presented in the manual. The Guide presents more than 160 effective TSMO practices from transportation agencies, highlighting tangible benefits and implementation approaches. It is designed to help agencies learn from these practices and apply them within their own contexts to support the implementation of TSMO programs and strategies.

Transportation research and government agencies often operate in separate disciplines, creating organizational silos that hinder the development of coordinated, multidisciplinary strategies to eliminate traffic fatalities. The Safe System Approach seeks to overcome these barriers by integrating countermeasures across disciplines and introducing redundancy to improve transportation safety.

NCHRP Web-Only Document 470: Strategic Decision Making to Improve Traffic Safety, produced by TRB’s National Cooperative Highway Research Program, presents updated versions of the predictive models developed in earlier research and describes the Safety Countermeasure Benefits Estimator (SCBE), a web-based tool developed as part of the research, and its accompanying user guide. The tool is designed to help practitioners estimate the potential effects of safety programs and projects. By combining these estimates with the anticipated impacts of vehicle safety improvements, the updated models can help states establish realistic targets for reducing traffic fatalities and assess the investments needed to achieve those goals.

Currently, regional planning processes and tools are limited in their ability to quickly and easily compare alternatives and their multidimensional impacts and interrelationships. MPOs often rely on single-use models, each with its own data dependencies and implementation schedules. This inefficient approach increases costs, extends timeframes, and reduces the reliability of complex planning efforts and investments.

With support from the USDOT SMART Grant Stage 1 Prototyping Grant, BMPO is developing SMART METRO, an innovative regional application of systems integration to create and implement an efficient foundational digital twin platform. Accelerating threats to infrastructure, housing costs, congestion impacts, and population growth pose significant risks to Broward County, Florida. SMART METRO will integrate data science, geospatial analytics, and simulation tools and models for efficient transportation, infrastructure hardening, economic development, and land-use analysis.

Through the Digital Right-of-Way (ROW) and Mobility Improvement Project, the City of Philadelphia developed and implemented a set of new technologies to test digital management of the right-of-way (ROW). Traditionally, as in other cities, Philadelphia issues regulations on how roadways and sidewalks may be used or blocked, and posts physical signs that users must read, interpret, and follow to use the street safely and legally. The Smart Cities team, in partnership with the Streets Department, Open Mobility Foundation, and several vendors, tested communicating these right-of-way regulations and closures digitally, such that a user’s phone or vehicle could receive them, parse out relevant information for specific location/day/time and turn it into guidance for the user - for instance, should the user park or not, and if a user is blocking a bike lane or not.

One of the most important deliverables for the project was the development of the Right-of-Way Data Specification (ROWDS), a formal way to standardize and structure City ROW rules for computers to use, and its implementation through Road Rules, a software product by the company INRIX. These technologies have helped increase the spatial resolution (the level of detail for mapping small areas) of the underlying basemap to match what the Streets Department needs to operate. The project also demonstrated that higher spatial resolution can help the city better manage street-closure permitting. As this project is operationalized through a citywide deployment, it will pave the way for an improved user experience for everyone who uses the roads and a more efficient permitting system for the City of Philadelphia.

This report investigates vulnerabilities in New Zealand’s strategic road network that could cause disruptions. The project identifies critical vulnerabilities that impact the national freight network and strategic supply chains, incurring significant costs to end users, and identifies mitigation activities to reduce these vulnerabilities. The analysis includes crucial nodes and linkages, predicting the impact of their unavailability on supply chains. The report highlights the importance of competition in the freight sector, noting that an oligopolistic structure often drives inefficiencies and increased costs. We identify short-term (up to 1 day), medium-term (up to 1 month) and long-term (3 months or longer) closure timeframes as defined by users, outlining their respective impacts and contingency plans. In short-term closures, contingency plans typically involve dynamic decisions, carrying safety stock and delaying shipments. Medium-term closures see a shift towards using rail and sea transport and offshore storage in containers for warehousing. Long-term closures emphasize sea transport and adaptive decision making even more, with significant variations in response based on the specific business and level of uncertainty involved. We use economic impact computable general equilibrium modelling and stakeholder engagement to inform the need to strengthen or build redundancy into the freight system, focusing on road transport. Findings indicate regional variations in freight cost impacts and suggest the importance of adaptive planning for deeply uncertain events. The report emphasizes economic impacts, not financial costs, and provides insights into contingency plans and their effectiveness in different scenarios.

Corrosion of buried steel, a critical component of American transportation infrastructure, remains one of the most insidious challenges due to the uncertainty associated with its estimates. Predicting when and how this corrosion happens is very difficult. This uncertainty grows exponentially with time, making corrosion estimation in the long term even more challenging, especially with buried steel and steel structures, which cannot even be monitored visually. While significant advancement has been made to understand the effect of the various corrosion parameters on soil corrosivity, there is a lack of a comprehensive understanding of how these factors collectively contribute to corrosion as they vary simultaneously and continuously with time. This project evaluates soil resistivity and corrosivity in controlled, constant conditions, considering the various key parameters that contribute to corrosion of buried steel. The project involved devising a new experimental protocol and developing and implementing a comprehensive experimental program by varying one testing parameter at a time. The results of the testing program showed the potential of the experimental approach to provide the necessary data to develop empirical prediction models for soil resistivity. Additionally, a new experimental method was piloted for this project to capture the variation in soil resistivity in a continuously varying environment. Finally, the researchers compiled a large digital database of real-world corrosion measurements and site information. Using advanced data analysis techniques, they created a model that can help predict corrosion in buried steel structures and estimate the level of uncertainty in those predictions. Better predictions of corrosion can help engineers and infrastructure managers identify risks earlier, plan maintenance more effectively, and extend the life of critical infrastructure such as pipelines, bridges, and transportation systems, therefore helping to reduce costly failures, improve safety, and support more reliable systems.