Institute for Transportation

About the research

As utility infrastructure increasingly occupies public roadway rights of way (ROWs), Iowa faces growing challenges in coordinating utility installations and managing space efficiently. The lack of standardized oversight across cities, counties, and the Iowa Department of Transportation (DOT) has led to inconsistent practices, disorganized utility placement, and costly delays in highway construction. This research aimed to develop a comprehensive utility management approach by identifying best practices for planning, documenting, and managing utility installations within public ROWs. Through surveys of current practices, gap analysis, and stakeholder engagement, the study produced a framework for improved utility coordination. Key recommendations include statewide standardization of policies, mandatory digital as-built documentation, designated utility corridors, enhanced permitting and oversight, and clear protocols for managing abandoned utilities. The research also resulted in the development of training programs and outreach efforts to support implementation. By adopting these strategies, Iowa can achieve more efficient, coordinated, and sustainable utility management, ultimately reducing project costs and preserving ROW integrity for future infrastructure needs.

About the research

Although young drivers log fewer miles than any age group except the elderly, the number of crashes and fatalities they experience is disproportionately high. Driver education is an important part of helping young drivers learn the basic skills of driving, but current requirements for driver education in Iowa do not take a comprehensive or data-driven approach to identifying and addressing novice needs.

The main goal of this research was to enhance Iowa’s driver education curriculum and ensure that it addresses both Iowa-specific and general safety issues to prepare novice drivers for a rapidly changing driving environment. Best practices in driver education and teaching trends in Iowa, in other states, and nationally were identified; a crash analysis was carried out; and driver education instructors and parents were surveyed to determine problem areas that could be addressed by the driver education curriculum. A series of informational videos was then developed to supplement driver education curriculums, and the research team drafted recommendations for changes to the Iowa driver education curriculum, the Iowa Code, and Iowa Administrative Rules.

About the research

Effective and timely bridge inspections are crucial for extending bridge lifespans and preventing catastrophic failures. Traditional inspection methods often involve manual visual assessments and can be time-consuming, labor-intensive, and prone to human error. Recent technological advancements in unmanned aerial vehicles (UAVs), artificial intelligence (AI), and machine learning (ML) offer promising solutions to these challenges. When high-quality images captured by UAVs are analyzed using AI and ML algorithms, structural defects can be detected and quantified with greater precision and efficiency than manual inspections.

The primary objective of this research was to enhance the accuracy and efficiency of structural inspections by integrating UAV technology for image capture and AI-based detection models for analysis. High-resolution images of bridge components were collected using UAVs operating at various distances and angles and were then processed through a custom-developed convolutional neural network (CNN) to detect critical defects such as cracking and spalling. The model’s performance was assessed through multiple case studies, and its ability to detect and quantify defects under different conditions was validated against field data. This approach yielded significant improvements over traditional bridge inspection methods in terms of the precision with which structural vulnerabilities were identified and accurately quantified defect dimensions.

Furthermore, the research incorporated the development of three-dimensional (3D) models of bridge structures using commercially available software to enable detailed structural assessments. High-resolution UAV imagery was successfully integrated into 3D modeling software to generate detailed models of bridge structures enabling comprehensive structural assessments and allowing for the quantification of detected defects. The results demonstrate the potential of UAV-based inspections combined with AI-powered detection models to revolutionize bridge inspection practices by offering a more reliable, efficient, and cost-effective approach to infrastructure maintenance and supporting more informed decision-making for infrastructure safety and longevity.

About the research

This project is a task order under the main Federal Highway Administration (FHWA)-sponsored project, “Infrastructure Research and Technology Deployment Program.”

The final report reviews state department of transportation (DOT) practices related to bridge load rating, posting, and permitting procedures, analyzing publicly available documents. It examines previous versions of the National Bridge Inspection Standards (NBIS) and the most recent 2022 update, alongside the American Association of State Highway and Transportation Officials (AASHTO) Manual for Bridge Evaluation (MBE) and its interim revisions. The review highlights both common and unique practices across states in assessing bridge load-carrying capacity, which is essential for preservation and public safety. Routine load ratings are typically based on design plans, field measurements, and inspection reports, while more advanced methods incorporate sophisticated analytical techniques like two-dimensional (2D) and three-dimensional (3D) finite element models.

In 2024, peer exchange meetings were held in Salt Lake City, UT, and Pittsburgh, PA, where participating transportation agencies discussed five key topics: state truck size and weight limits, consideration of deterioration in bridge load rating, timely re-rating and posting, structural analysis for permit loads, and research and technology. The final report summarizes the meetings and their contributions to advancing bridge load rating practices across the U.S.

About the research

The traditional method of tracking material deliveries to roadway and bridge construction sites has been for inspectors to collect paper tickets from haul truck operators. The Iowa Department of Transportation (DOT), however, is a national leader in the innovative alternative to this method: e-ticketing.

As defined by the Federal Highway Administration’s (FHWA’s) Every Day Counts, Round 6 (EDC-6) initiative, e-ticketing is the provision of “an electronic means to produce, transmit, and share materials data and track and verify materials deliveries.”

The digitization of this data collection and processing procedure has numerous benefits:

• Increased safety for job site construction inspectors through a reduction in their exposure to work zone vehicles
• Time savings through real-time access to data and reduced processing times
• Higher-quality project paperwork through more consistent and efficient project documentation
• Standardization of the data collected, allowing for easier access and analysis that might define future improvements and/or quantification of program impacts

About the research

The design of drilled shafts in Iowa currently relies on the American Association of State Highway and Transportation Officials (AASHTO) LRFD Bridge Design Specifications. To improve design efficiency at the state level, a series of research projects was conducted to develop the Drilled SHAft Foundation Testing (DSHAFT) database, a regional database facilitating the collection, storage, and efficient access of load test data from Iowa and other states, and to utilize the collected data to establish regional resistance factors that are reflective of the uncertainties associated with predicting drilled shaft capacity under Iowa’s specific geological conditions and construction practices. Resistance factors established in a 2019 study for various resistance prediction methods generally showed improvements over those recommended by AASHTO.

The present research aimed to validate the proposed resistance factors and formulate design recommendations for implementation. To this end, the DSHAFT database was further expanded with additional test data. Additionally, regression analyses were conducted on test data from Iowa to develop local resistance predictions that may provide more accurate estimates of drilled shaft capacity locally. Results from the analysis indicated that a linear correlation between soil parameters and measured unit side resistance was the best fit for most soil types. Moreover, settlement data were collected at several production shafts that were part of a few Iowa DOT bridge replacement projects to evaluate the field performance of drilled shafts designed under the current Iowa DOT guidelines. Various challenges were encountered during the data collection process. Some of the data indicated unexpected negative settlements, and further investigation is needed to develop appropriate conclusions. Design recommendations were formulated based on all findings, and design examples were developed to illustrate the application of the design recommendations.

About the research

The United States has approximately 600,000 bridges and 47,000 miles of interstate highways. More than 75% of bridges and 60% of highways are made of concrete. Concrete production consumes massive amounts of raw materials and energy, and US cement production emits about 67 million tons of carbon dioxide. A key to concrete decarbonization is using low-carbon cement. We propose to formulate, characterize, optimize, evaluate, and implement a new generation, low-carbon, energy-saving, and cost-effective cement made with calcined clay (CC)/natural pozzolan, Type I portland cement (I), and limestone powder (L), called CC·I·L cement. Implementation challenges will be addressed by (1) streamlining the testing process for characterizing raw materials and their blends, (2) using machine-learning techniques to optimize cement composition and predict performance, (3) developing prediction models for hydration and adiabatic temperature rise via software modification, and (4) conducting both laboratory and field investigations to comprehend performance. A roadmap will be developed defining goals, outcomes, and milestones for implementing CC·I·L in future transportation infrastructure.

About the research

This project is a task order under the main Federal Highway Administration (FHWA)-sponsored project, “Infrastructure Research and Technology Deployment Program.”

Past regional bridge load rating peer exchanges conducted by the FHWA from 2014 to 2019 proved effective to gain an understanding of the load rating practices used by state departments of transportation (DOTs). The exchanges helped make known the best practices and technologies being used for load rating bridges, posting bridges, and issuing permits. The success of these exchanges and the continual evolution of practices and technology coupled with newly imposed requirements provide reason for additional peer exchanges, which are intended to include representatives from all DOTs.

About the research

Traffic signal controllers use yellow change and red clearance intervals at signalized intersections to alert drivers to impending changes in the right-of-way assignment between conflicting traffic movements. Determining appropriate change and clearance intervals (CCIs) is important at signalized intersections to ensure safe transfer of the right-of-way while minimizing lost time and therefore reducing intersection delay.

To improve documentation and consistent implementation of CCI calculation methods in State and local agencies, the Federal Highway Administration is leading the Traffic Signal Change and Clearance Interval Pooled Fund Study. The pooled fund study sponsored a phase I study to develop a synthesis of knowledge on CCIs. The phase I study included a literature review and an agency benchmarking plan to synthesize existing research and agency practices and identify research gaps. Based on the review findings, this synthesis report presents eight research studies and the data needs to execute the research. The eight research studies include proposed methods for determining the CCIs and the CCI performance assessment.

This project is a task order under the main FHWA-sponsored project DTFH61-16-D-00053, in which LEIDOS, Inc. is the Lead.

About the research

The Process Document was developed to help agencies manage and evaluate work zone activities and document the lessons learned. Its objective is to outline a structured post-construction evaluation process that uses a feedback loop to help evaluate and improve performance during the construction phase and generate lessons learned for future use.

The scope for the work was as follows:

• Define a structured review process that includes evaluation
• Define a feedback loop to document and mitigate project issues and generate lessons learned
• Develop a structure for lessons learned documentation
• Demonstrate the implementation of lessons learned in example projects

The four appendices (A through D) at the end of the Process Document were designed to be easily accessed at a later date. Appendix C provides a sample Lessons Learned form that readers can adapt and use on their projects.

The Discussion Facilitation Guide is a companion document to the Process Document, and the purpose is to provide resources to facilitate discussion during training. This document provides a training discussion outline with recommended steps for facilitation. Everything mentioned in this companion document is a suggestion and can be adjusted accordingly.