Document Library

Aggressive driving is a prevalent traffic safety concern that contributes to crash risk and undermines traffic safety culture. Building on Phase 1 work that defined aggressive driving and identified promising intervention points, this Phase 2 study examined two complementary strategies to reduce aggressive driving: supporting bystanders (i.e., spouses/partners, family members, and close friends) to intervene with drivers who engage in aggressive driving, and developing and testing media messages to encourage safer driving among drivers themselves. Key informant interviews were conducted with bystanders. Findings informed the development of a three-step bystander intervention that included expressing concern and connecting to shared values. The intervention was tested with a national sample of 102 bystanders. Results demonstrated increased bystander confidence, greater use of constructive strategies, and perceived reductions in aggressive driving frequency. Participants reported that the strategies were feasible, acceptable, and helpful. Media messages were developed in three main themes: cognitive reappraisal, adaptive response, and prosocial driving. Messages were tested with 864 drivers who reported recent engagement in aggressive driving. Findings indicated that, across message themes, messages were well received, prompted reflection on driving behavior, and supported changes in perceptions related to safety and responsibility. Together, these findings suggest that engaging bystanders and deploying supportive, nonjudgmental messaging are promising, complementary approaches to reducing aggressive driving and strengthening traffic safety culture. Resources were developed: a bystander conversation guide, a community dissemination toolkit, and a messaging development resource.

Pedestrian crosswalks, bike lanes, and medians are key safety devices in a multi-modal highway network. However, there is no statewide map of these assets' locations and types. Such a map would benefit planning, maintenance, safety assessments, and network analyses for ODOT and its partners. Currently, ODOT collects asset information through site visits and surveys, which are labor-intensive and costly across the state's vast road network. GIS databases are created ad-hoc and inconsistently, often by interns. Fortunately, ODOT Engineering Automation regularly collects 3D mobile lidar data, providing geometric and radiometric information. This research reviewed state-of-the-art approaches for detecting and classifying pedestrian crosswalks, bike lanes, and medians, and developed a methodology to extract these features from LiDAR datasets for updating ODOT’s GIS platform. The approach was tested on several datasets and showed good extraction performance, requiring minimal manual cleanup. Lastly, a plan is provided for ODOT to implement this research.

This study investigated the use of co-simulation for evaluating cooperative driving automation (CDA) applications within a work zone environment. The examined use case focused on the merging maneuvers of a single CDA-equipped vehicle into either a CDA platoon or a traffic stream consisting of human-driven vehicles near a work zone with a one-lane blockage. The findings demonstrate that co-simulation can serve as an effective component of automated vehicle and CDA testing, particularly in complex and challenging environments such as work zones. The study further demonstrated that cooperative lane-changing behavior near work zones can be systematically assessed within a controlled simulation environment, and that the resulting performance measures can help identify limitations and guide improvements to existing automated and cooperative driving algorithms and control logic.

Providing safe and secure parking for the more than three million heavy trucks that move over 70% of the nation’s freight is both a local and national issue. This is especially true for a major freight hub such as Louisiana, with its freight-intensive corridors, including I-10 and I-12. Currently, there is only one parking spot for every 11 trucks in the state, and these shortages lead to illegal parking, creating safety, operational, and economic challenges that ripple through Louisiana's freight system. These include non-compliance with Hours-of-Service regulations, economic and freight inefficiencies, and quality-of-life issues for impacted communities. This report presents the results of research that evaluated truck parking conditions in Louisiana and proposes short- and long-term solutions to address these problems. This study employed a mixed-methods approach to data collection and analysis, combining a literature review that synthesized state and national policies and local zoning laws, stakeholder surveys and interviews, GIS and spatial analyses, qualitative thematic analysis, and economic modeling using IMPLAN to assess the impacts of developing truck parking facilities in Louisiana. The cost of not investing in truck parking in the state was also calculated. Data were collected from a wide range of stakeholders, including truck drivers, trucking companies, communities, local government officials, truck parking companies, and law enforcement personnel, providing the necessary input for analyzing issues related to truck parking in Louisiana. Conclusions and recommendations were developed from a rigorous analysis and interpretation of the data. Recommendations focused on identifying priority corridors and locations where optimal benefits from parking investments could be achieved, developing model language for local zoning ordinances to support increased truck parking development in the state, and identifying potential funding avenues and management matrices to help policymakers determine the best approach to financing parking investments. Findings from this study will enable decision-makers to comprehensively address the challenges of providing adequate truck parking in Louisiana, a key to improved freight efficiency, enhanced safety, and more livable communities.

Florida-produced fine aggregates are generally of suitable quality, and deleterious effects associated with organic matter are uncommon. However, naturally occurring organic constituents can affect cement hydration and early-age strength development depending on their concentration, composition, and interaction with cementitious phases. The sands evaluated in this study contained relatively low organic contents, making establishment of a universal organic-content threshold impractical. FDOT currently uses AASHTO T 21 as the primary screening method for potentially deleterious organic impurities and requires AASHTO T 71 testing when screening results indicate concern. This framework should be maintained. AASHTO T 21 provides effective statewide screening, while AASHTO T 71 provides performance-based confirmation. However, AASHTO T 21 is qualitative, and AASHTO T 71 requires extended testing that can delay aggregate acceptance decisions. Neither elemental analysis nor the Modified Walkley-Black method demonstrated sufficient precision, consistency, or correlation with AASHTO T 21 to support statewide acceptance criteria. However, MWB may be used to establish minespecific organic-carbon baselines, and isothermal calorimetry may be used to establish mine-specific hydration-response baselines. Deviations from these baselines may indicate the need for additional evaluation, including AASHTO T 71 testing. Organic-carbon contents below approximately 0.015% did not measurably affect hydration or compressive strength. Alkaline washing reduced measured organic content and increased pH but did not consistently improve strength. The ASTM C109 hand-tamped consolidation procedure is recommended for AASHTO T 71 mortar cube fabrication. Trace inorganic constituents, including phosphorus, did not produce measurable strength effects.

The Federal Railroad Administration contracted ENSCO to investigate the application of model-assisted probability of detection (MAPOD) to handheld ultrasonic rail flaw inspection. This research was conducted as part of a project that began in 2019 to investigate methods for evaluating the performance of track inspection technologies. The demonstration of MAPOD presented in this study points to several opportunities for further research. For example, hit-miss POD analysis could be extended to accurately show the probability of sizing flaws, and MAPOD simulations could include additional physical and human factors. Most importantly, the MAPOD approach developed in this study could also be adapted and applied to other track inspection technologies, such as track geometry measurement

Truck platooning, a technology where connected and automated trucks travel in closely linked convoys, promises significant reductions in fuel consumption and emissions. However, these long convoys present a major safety hazard on existing roadways, particularly on rural two-lane undivided highways. On these roads, human drivers must use the oncoming traffic lane to overtake, and a long truck platoon acts as a dangerous and extended barrier. To address this problem, we established a comprehensive framework to safely integrate platoons into mixed traffic. The research progressed through four steps. First, we modeled the precise time and distance required for a human driver to safely pass a platoon. Second, we developed a dynamic algorithm that determines safe platooning limits, such as the maximum number of trucks allowed, based on real-time road geometry and oncoming traffic. Third, we tested these rules using advanced traffic simulations. Finally, we designed an active gap opening control system, allowing automated trucks to proactively split apart and provide a safe harbor for passing vehicles. Our findings demonstrate that while long platoons operate safely on multilane highways, they require strict, dynamic limitations on two-lane roads. This research provides transportation policymakers with a clear, data-driven blueprint. By shifting from rigid rules to context-aware operational rules and utilizing cooperative gap opening technologies, agencies can preserve the economic benefits of truck platooning while rigorously protecting the safety of everyday drivers.

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.