Watch the video to learn more about NJ STIC Incentive Grants.
The Federal Highway Administration (FHWA) offers STIC Incentive Funding, as well as technical assistance, to support the standardization and advancement of innovative practices. The NJ STIC receives $125,000 each year and state and local public agencies in transportation are eligible to apply.
To be eligible, a project or activity must have a statewide impact in fostering a culture for innovation or in standardizing an innovative practice, and must align with FHWA’s Technology Innovation Deployment Program goals. The NJ STIC will prioritize funding projects and activities that advance innovations such as the Every Day Counts (EDC) innovations that are being promoted by FHWA.
NJ STIC solicits ideas for funding of proposed innovation projects each federal fiscal year. Selected projects are then submitted to the Federal Highway Administration (FHWA) for approval. The request submittal does not guarantee funding nor award of funding.
The NJDOT Bureau of Research, Innovation and Information Transfer (BRIIT) is ready to answer your questions and assist applicants. For more information on eligibility, proposal requirements, past funded projects, and more, please visit: the New Jersey STIC Incentive Fund Requests webpage.
At the NJ STIC 2024 3rd Triannual Meeting on December 2024, the Infrastructure Preservation CIA Team announced the publication of an FHWA TechNotes reports, which drew lessons from NJDOT, among other transportation agencies and stakeholders. The report, Experiences from Early Implementation of UHPC Overlays, summarized the experiences of five different entities with their recent installations of UHPC overlays.
FHWA interviewed Samer Rabie and Jess Mendenhall from NJDOT, as well as individuals from the Delaware River & Bay Authority, Federal Lands Highway, the Iowa Department of Transportation, and Buchanan County in Iowa, to discuss the lessons learned and future recommendations from their previous experiences.
According to the report, ultra-high performance concrete (UHPC), part of the sixth round of the Every Day Counts (EDC-6) initiative, offers many qualities beneficial to overlay applications, including very low permeability, good freeze-thaw resistance, good abrasion resistance, high strength and stiffness, and good bond strength. Despite higher initial costs during the construction process, UHPC factors such as superior durability and improved life-cycle cost can also reduce costs over time compared to traditional methods.
UHPC Overlay surface after grinding and grooving.
The implementation of UHPC overlays differs from traditional overlays, requiring additional planning, expertise, and methods, especially for larger projects. The feedback provided by the transportation agencies on UHPC overlays in the FHWA report includes information on project selection, project planning, surface preparation, UHPC mixture design, UHPC mixing, UHPC placement, constructions joints, UHPC finishing, and UHPC removal and repair.
In addition to the FHWA TechNotes report, NJDOT has previously highlighted UHPC research projects from New Jersey’s Institutes of Higher Education partners, and the agency’s own experiences with implementing UHPC. Some examples include presentations at the annual NJDOT Research Showcase, Q&A interviews with NJDOT’s SMEs focused on the innovation’s implementation, and previous projects with FHWA. Most recently, NJDOT has been a participating funding agency for the Structural Behavior of Ultra High Performance Concrete project, led by FHWA, as part of the Transportation Pooled Fund (TPF) program. To learn more about UHPC research and implementation in New Jersey, read through the resources section below.
Resources:
FHWA. Experiences from Early Implementation of UHPC Overlays. (2025). [Report]
NJDOT’s Involvement with Transportation Pooled Fund Program. (2025). [Article]
Ultra High-Performance Concrete (UHPC) Applications in New Jersey – An Update. (2024). [Article].
Advanced Reinforced Concrete Materials for Transportation Infrastructure. (2023). [Webinar].
Bandelt, M., Adams, M., Wang, H., Najm, H., and Bechtel A., Shirkorshidi, S., Jin, F. (2023). Advanced Reinforced Concrete Materials for Transportation Infrastructure. (2023). [Final Report].
Bandelt, M., Adams, M., Wang, H., Najm, H., and Bechtel A., Shirkorshidi, S., Jin, F. Advanced Reinforced Concrete Materials for Transportation Infrastructure. (2023). [Technical Brief].
Presentation: Design, Construction, and Evaluation of UHPC Bridge Deck Overlays for NJDOT. (2022). [STIC Presentation]
Stronger, More Resilient Bridges: Ultra High-Performance Concrete (UHPC) Applications in New Jersey. (2021). [Article]
Ultra-High Performance Concrete for Bridge Preservation and Repair: NJDOT Example Featured. (2021). [Article]
NJDOT Research Showcase Posters and Presentations
Ghahsareh, F. Life-Cycle Assessment of Ultra-High Performance Concrete (UHPC) Beams Using Advanced Monitoring Technologies. (2024). [Presentation].{Video}
Gucunski, N. Evaluation of Performance of Bridge Deck with UHPC and LMC Overlays through Accelerated Structural Testing. (2024). [Presentation]. {Video}
Shirkhorshidi, S., Bandelt, M., Adams, M., and Reif J. Corrosion Performance of Ultra-High Performance Concrete in Uncracked and Cracked Beams. (2022). [Presentation]. {Video}
Meng, W. Design and Performance of Cost-Effective Ultra-High Performance Concrete (UHPC) for Transportation Infrastructure. (2018). [Presentation]
We had the opportunity to speak with Swathi Malluru, a PhD candidate at Rowan University and recipient of the 2024 NJDOT Research Showcase Best Poster Award. Her research focuses on sustainable pavement rehabilitation, including the Full-Depth Reclamation (FDR) and Cold In-Place Recycling (CIR) processes that were the subject of the performance evaluation recognized with the Best Poster Award. In this interview, Ms. Malluru discusses her journey in transportation engineering, from her background in sustainable materials to her work optimizing stabilizers for FDR and CIR. She hopes that her research can provide economic and environmental benefits and shares how it could shape future NJDOT policies.
Q. Congratulations on receiving the Best Poster Award at the 2024 NJDOT Research Showcase. Could you tell us about your prior educational and research experience, and how you came to be a PhD student at Rowan University?
A. First of all, I would like to thank you for your time. I pursued my master’s in Transportation Engineering from the Indian Institute of Technology. At the university, I learned about pavement materials, specifically pavement rehabilitation techniques and pavement design analysis. Then, I worked on a steel slag aggregates project. In this project, I completely replaced the conventional natural aggregates with steel slag aggregates in hot mix asphalt mixture and evaluated the performance to understand if slag could function as an alternative to the conventional natural aggregates. This motivated me to do further work in sustainability and that’s how my research journey started.
What drew me to Rowan University was the Center for Research and Education in Advanced Transportation Engineering Systems (CREATES), which deals with diverse research projects, and has a lot of facilities for conducting research on pavement materials. CREATES provides facilities where we can conduct our laboratory tests and evaluate the performance of various mixes. In the laboratory, we do everything in controlled conditions that may not exactly simulate field conditions but provide a good opportunity for a researcher to understand the behavior of a particular material and mix under different circumstances. CREATES also facilitates test sections and conducts Accelerated Pavement Testing (APT) using the Heavy Vehicle Simulator (HVS) to evaluate the field performance of the asphalt mixtures.
Q. What sparked your interest in sustainability related to pavement materials and rehabilitation?
A. I come from an industry background. After my master’s, I worked in construction for Larsen & Toubro and later as a highway designer for Jacobs. I worked on the geometric design of Texas Department of Transportation (TxDOT) projects. Based on my experience, I found that, especially in developed countries, roads have mostly been constructed. The future is in widening, rehabilitation, and maintenance of the existing roads. Additionally, we see that transportation is the largest global contributor to carbon emissions. These factors convinced me to focus on researching environmentally friendly and cost-effective pavement materials for sustainable development.
Q. The research in your poster focused on Full Depth Reclamation (FDR) and Cold In-Place Recycling (CIR). Can you describe some of the environmental or economic benefits that these processes provide?
Asphalt Milling Machine.
A. This project was funded by NJDOT Pavement Support Program (PSP) and led by Dr. Ahmed Saidi from CREATES, Rowan University. Cold In Place Recycling and Full Depth Reclamation are two rehabilitation techniques of deteriorated asphalt pavements. In the conventional process, whenever the pavement is highly distressed, we completely remove the materials and lay a new pavement stretch in that particular location. This process utilizes a Hot Mix Asphalt (HMA) mixture that requires asphalt, high mixing temperatures and large amounts of energy consumption, producing emissions. Production of HMA also involves a lot of volatile organic compounds, which can significantly impact the environment.
By replacing the process with a FDR or CIR, we can conserve the materials and reduce emissions. In FDR, the existing pavement is milled up to the unbound soil layers (at a depth up to 14 inches) and then laid into a single layer through pulverization and stabilization with additives. CIR involves reclamation of asphalt layer (at a depth up to 4 inches) and stabilization with additives. In this scenario, we see very little emissions, and it is also very quick. In our few trial stretches, which included some NJDOT projects, we observed that we could save $10,000 to $50,000 per mile. This is a huge achievement in cost savings and time savings, and is environmentally friendly. These are the benefits we get from implementing FDR and CIR.
Q. For the first two tasks in the research project, you conducted a literature review and a survey of different state DOTs. What did you find through these two tasks, and how did it prepare you for the lab tests?
A. We went through the various guidelines of different state DOTs and other state agencies. From this literature review, we observed that early on, state guidelines mentioned only the usage of cement for the FDR. But some states like Pennsylvania and Illinois started implementing the use of bituminous stabilizers to improve the performance of FDR. Through the state DOT literature review and the survey questionnaire, we learned more about the properties of emulsions and cement, the properties of RAP gradation, the types of cement that we have to select, and also how to cure and compact samples. We learned all these aspects of FDR and CIR from the literature review and the survey questionnaires, and then we tried to incorporate all these elements.
Q. You concluded with the research that 5 percent cement, or 3 percent emulsion, 1 percent cement and 3 percent water worked best for FDR, and 2 percent emulsion, or 1.5 percent foamed bitumen for CIR. How many different combinations did you try and how significantly did these combinations outperform the alternatives?
A. Based on the performance criteria from the literature review, we tried to understand what the optimum dosage should be. We considered three different stabilizer material types for FDR: a section with only cement varying from 4 to 5 percent with a 0.5 increment; a mix consisting of emulsion varying from 3 to 5 percent; and foamed bitumen varying from 3 to 5 percent. We decided to utilize these dosages based on the literature review. From the laboratory test, we observed that the 3 percent emulsion gave less rut depth and better fatigue performance compared to alternatives. Similarly, when we added 5 percent cement or 3 percent emulsion, we found it gave an equal performance.
Q. Did you experience any challenges during the lab tests?
A. Based on what we learned in the literature review, we were able to match the results and confirm it. Emulsions, and the inclusion of bituminous additives, can improve the performance of these mixtures. The challenges were during the mixing and compaction, but we managed to rectify those challenges over time.
Q. What additional research do you think should be conducted based on your findings from this project?
A. We have to conduct further work on the impact and performance of FDR and CIR and also evaluate any other alternatives that can be used as stabilizers. Currently, we are proposing FDR and CIR guidelines for minor roads, but maybe, if we try to improve and enhance its performance, we can extend it to the interstate highways and roads of higher priority. That is a major area for future research.
Q. What kind of impact do you hope this research will have on NJDOT construction and design policy moving forward?
A. I hope it helps NJDOT optimize cost savings, reduce labor, and construction time and, especially, aid in NJDOT becoming more environmentally friendly. This will help reduce emissions compared to using the conventional overlay method and help NJDOT achieve its sustainability goals.
Q. Moving toward your personal research, is there any kind of research that you specifically want to focus on going forward, or would it be something similar to this as you progress through your doctoral path?
A. After this, I want to try to conduct a test trial to evaluate the performance of FDR and conduct a life cycle assessment. And try to test the impact of low temperatures on the performance of FDR. Will there be a low temperature cracking effect from freezing? I would also like to work on developing design guidelines for the implementation of FDR and CIR throughout NJDOT.
Q. What are your career goals and aspirations for after you complete your PhD?
A. After my PhD, I would like to work in the industry, so I can implement my research and work to find solutions for major problems.
NJ 2025 Build a Better Mousetrap Competition is underway!
The competition provides a great opportunity to share your ingenious and implemented solutions in transportation with others in New Jersey and across the country. These innovations can range from the development of tools and equipment modifications to the implementation of new processes that increase safety, reduce cost, and improve efficiency of our transportation system.
We are looking for submissions from employees of any local, county or state public agency, including the New Jersey Department of Transportation and NJ TRANSIT that have developed new solutions to problems or found better ways of doing things.
Winners will be chosen in two categories: Operations and Organizational Improvement. This competition is sponsored by the Federal Highway Administration’s Local Technical Assistance Program and Tribal Technical Assistance Program, and local public agency winners will be entered in the annual National LTAP/TTAP Conference.
A state winner in each category will also be selected and presented at the Annual NJDOT Research Showcase later this fall. The deadline for submissions is May 1st, 2025.
The New Jersey 2024 Build a Better Mousetrap Award was given to Bishoy Abdallah, a Senior Engineer in the Transportation Roadway Design (Group-1) at NJDOT, for his Replacing Inlet Curb Pieces in Existing Concrete Barrier Curb project.
There is still time to share your ingenious solutions! Past examples of NJ’s recognized BABM award winning entries can be found here. More information about how to enter the competition and to download an entry form can be found here.
Every two years, FHWA works with state transportation departments, local governments, tribes, private industry, and other stakeholders to identify and champion a new collection of innovations that merit accelerated deployment through the Every Day Counts initiative (EDC). In preparation for the next EDC phase, FHWA has announced a Call for Ideas seeking suggestions for market-ready innovations to deploy in 2026 as part of the eighth round of Every Day Counts (EDC-8).
FHWA is interested in submissions for innovations that describe how the innovation will address the following areas:
National Impact: How will it benefit the transportation system nationally?
Game Changing: How is it transformative in making our transportation system adaptable, sustainable, resilient, equitable, and safer for all?
Urgency and Scale: How will it positively impact the environment, safety, congestion, freight movement, construction techniques, contracting methods, project costs, maintenance, preservation, or emergency response?
Locations: Where has the innovation been deployed?
The submission deadline for this Call for Ideas is February 4, 2025. For more information on the Every Day Counts initiative and how to submit suggestions, visit here.
The innovations championed during the seventh round of Every Day Counts include Enhancing Performance with Internally Cured Concrete, Environmental Product Declaration for Sustainable Project Delivery, Integrating GHG Assessment and Reduction Targets in Transportation Planning, NextGen TIM: Technology for Saving Lives, Nighttime Visibility for Safety, and Strategic Workforce Development. To learn more about innovative initiatives promoted in previous rounds of Every Day Counts and the status of their deployment in New Jersey, visit here.
Traffic safety and mobility, two critical areas in transportation engineering, both require the collection and analysis of large data sets to produce proactive and comprehensive solutions. Transportation engineers have started to increasingly focus on using innovative technologies to efficiently and effectively process this data.
We had the opportunity to speak with Dr. Deep Patel, a former Ph.D. candidate and research fellow at Rowan University, whose work is at the forefront of this mission. Recently, Patel received the NJDOT Outstanding University Student Research Award for his contributions to transportation research. In this interview, Patel shares insights from his research journey, including his work on the Real-Time Traffic Signal Performance Measurement Study and the development and implementation of machine learning tools to predict high-risk intersections. His dedication to improving traffic operations and safety, along with his new industry role as a Traffic Safety and Mobility Specialist, highlights the significant impact of combining academic research with practical industry applications.
Q. Could you tell us about your educational and research experience and how you became a PhD candidate and research fellow at Rowan University?
A. First of all, thank you for your time and for considering me for the opportunity to be interviewed about my recent NJDOT award. I would also like to thank the NJDOT review committee members and my Ph.D. advisor Dr. Mohammad Jalayer, who supported me in receiving this award.
I started my master’s study in 2018 as a civil engineering student without a research focus. Then, during my first semester, I took a course called Transportation Engineering with Dr. Mohammad Jalayer. When he sought traffic counting assistance for a traffic analysis project, I eagerly joined him, becoming his first research student.
Deep Patel conducting roadside research. Courtesy of Deep Patel.
Through that experience, I started thinking about what could streamline the traffic counting process and the various uses for the data we collected. I went on to work on several research projects with Dr. Jalayer, both funded and non-funded, where we had frequent discussions, and I would present my ideas to him. Eventually, he asked me to join him as a researcher and to continue my master’s work with a research focus, which I did for two years. When he suggested I continue my studies to earn a Ph.D., I was initially surprised, but I decided to go for it since I had a lot of ideas for future research projects.
At the end of my master’s study, I began Phase One work for a Real-Time Traffic System Performance Measure Study led by Dr. Peter Jin, Dr. Thomas Brennan, and Dr. Jalayer. This project connected me with a team from Rutgers, TCNJ, and a few professionals from NJDOT and other industry folks. I represented Rowan’s end for this project, where our focus was on understanding the safety aspects including safety parameters and performance and how we could assist NJDOT transform this new technology to help save lives. For the first phase of the project, we worked on understanding the traffic signal system performance measures, and what had been adopted by other DOTs. My experience on this project drove me to pursue more research and to expand my knowledge in traffic safety.
Q. You worked on Phase One through Three of this Real-Time Traffic Signal Performance Measurement Study. What part of this project interested you the most?
A. My main takeaway from this project focused on learning more about how the transportation industry looks towards the research outputs and outcomes from the university teams. It is very interesting to understand how university-based research is being adapted for industry acceptance. Additionally, I learned what problem-solving features the industry looks for from the research component.
From a technical aspect, I learned how New Jersey signals can be enhanced and how we can optimize the performance of these signals and achieve cost savings. Let’s say you have a scenario where there is no vehicle at an intersection; how can we provide recommendations to change the signal to a red light and give the other side of the intersection a green light? So, we gathered several components in terms of mobility, safety, and economic parameters from the study that can help enhance our traffic signals in New Jersey, sharing this information with the NJDOT team.
Example of real-time performance monitoring on County Road 541 and Irwick Road, Burlington County, NJ
Q. How did you see your role on the research project develop as you moved from the earlier phases to the latest phase?
A. In the first phase, we completed a comprehensive literature review to understand what is happening across the nation, which systems are being adapted, what are the best systems for providing traffic signal safety performance measures, and what are the kind of performance measures that can be adapted in an industry setting. In Phase Two, the team focused on developing mechanisms and performance measures aligned with NJDOT’s existing data, including deploying the Automated Traffic Signal Performance Measures (ATSPM) system to enhance traffic signal monitoring and optimization. To guide these efforts, an adaptability checklist was created to benchmark practices from other states and identify strategies that could be adapted to benefit NJDOT’s operations. Building on this foundation, Phase Three advanced to the demonstration and application of dashboards and performance measures, providing actionable recommendations to NJDOT on enhancing mobility and safety across various regions and corridors. These efforts aimed to save time and lives, while the integration of connected vehicle (CV) technologies remains a key focus for future work, ensuring NJDOT’s leadership in traffic management innovation.
Q. What were the specific corridors that you worked on?
A. We started with seven/eight intersections on U.S. 1. Then, we explored the whole corridor of U.S. 1 as part of Phase Three, and we also brought in Route 18, Route 130, and other intersections during this phase.
Q. Did you discover any particular surprising or noteworthy findings from this research?
A. This was a long project, extending from 2019-2024. As a result,each year we discovered new findings, and new components were often added to the project. For example, we added a CV systems component as part of the Phase Two and Phase Three projects to start planning for the future and understand what kind of data could be received and sent from CV technologies. The main benefit from this project is that it not only established current problem-solving measures but also looked into the future, helping to better understand what’s coming and how we can best face anticipated challenges that we need to start integrating at this moment. I find the combination of the present and future integration of systems and technologies interesting and important from the findings.
Q. What kind of impact do you think you and your research will have on NJDOT traffic operations and traffic safety, especially with your role now working in the industry?
A. With my previous experience as part of a university-led research team and now as a Traffic Safety and Specialist in the private sector, I am better positioned to facilitate the efficient and effective implementation of research findings. A key factor enabling this transition is that Kelly McVeigh, who supervised the original research project, also oversees the current work that our firm is doing for NJDOT. Being on the industry side allows me to introduce and operationalize new ideas more rapidly, compared to the academic research side. This streamlined approach ensures that innovative performance measures can be deployed more quickly, and even a small modification has the potential to save lives, underscoring the value of this work.
Q. Moving to a different topic, your research frequently incorporates Machine Learning (ML) and Artificial Intelligence (AI) aspects. In your experience, what benefits does AI contribute to transportation research?
A. Over the past few years, AI and ML have undergone drastic modifications and growing levels of industry acceptance. Additionally, in research outcomes, AI and ML have played a key role in enhancing and providing new methodologies and new ways of problem-solving. As an engineer, the first thing we have to do is understand how we can solve an existing problem, and how fast, effectively, and efficiently we can do it.
Transportation is now highly reliant on big data and intensive analysis, so AI and ML back up the processing of this data, coming up with meaningful outcomes and enhancing solution measures much quickly than previous methods. In 2012 or 2013, a standard engineer would need to sit down to do a traffic study and go through manual counting, then process the data, then come up with solutions, which takes much longer to solve a problem. The problem may even change during the months-long process of developing a solution.
In traffic safety, we cannot wait for the four to five months it could take to solve a problem due to the pressing safety implications of doing so. Thus, we must start implementing countermeasures swiftly, and AI and ML components help us to quickly process data with more effective and efficient results.
During my early days as a student researcher, I would stand on the roadside, manually counting the vehicles and pedestrians to collect data for traffic studies. However. during my doctoral research, I developed my AI-driven tools that utilize advanced video systems for detection and analysis. This proactive approach enables the identification of intersections prone to high-crash scenarios well before crashes occur, allowing for timely interventions. By integrating AI and ML, my research introduced innovative methodologies for crash prediction and prevention, showcasing the feasibility of data-driven solutions to enhance roadway safety.
There is a certain chaos in human beings’ lives and surroundings that requires transportation to be a multidisciplinary field, which includes human-focused aspects. For some parts, AI is definitely required, but with other parts, we need to go through different approaches.
Q. Do you think that because of AI’s data collection and analysis possibilities, almost all engineers in the near future will need to start incorporating AI into their research?
A. It really depends. For our part of traffic engineering, very specifically, I would say yes, it would be one of the major requirements that an engineer would need to adopt. But if I was a traffic engineer working on policy or equity measures there might be some concerns related to data sharing or data privacy issues that might restrict them.
It depends on what side you are focusing on. When it comes to data collection, I would say AI incorporation is a must to collect and process data faster and more efficiently. But in terms of developing policies, rules, or statutes, there are certain psychological aspects that need to be in the thought process. Knowing human concerns and people’s approaches requires an emotional touch, which AI still lacks.
Transportation is a field connected with multiple disciplines; it touches on people’s emotions. For example, on a day when traffic does not work well when you’re returning home, you can get frustrated, and that frustration can end up in a fatal crash. There is a certain chaos in human beings’ lives and surroundings that requires transportation to be a multidisciplinary field, which includes human-focused aspects. For some parts, AI is definitely required, but with other parts, we need to go through different approaches.
Q. Congratulations on your recently approved dissertation. Could you give us some quick highlights of the research methods that went into producing your dissertation, “A Comprehensive ML and AI Framework for Intersection Safety”? What are the most important takeaways from your dissertation?
Deep Patel presenting his poster at the 2022 NJDOT Research Showcase Poster Session. Click image for PDF of the poster.
A. New Jersey is home to some of the most dangerous intersections in the United States, with four intersections ranked among the top 15 most dangerous, including the 1st, 2nd, and 3rd positions. Since 2019, there has been a trend of steadily increasing intersection-related crashes and correlated crashes within intersection boundaries. This prompted me to ask, “Why do we need to wait for crashes to happen to address the problem?”
To tackle this issue, I developed a proactive approach inspired by my work on the NJDOT research project. The approach focuses on analyzing near-miss incidents and traffic violations, using the concept of surrogate safety measures to identify potential risks before crashes occur. Surrogate safety measures help us detect near-miss events and violations, offering a predictive understanding of high-risk scenarios at intersections.
Using AI and ML, we developed tools that analyze vehicle and pedestrian trajectories in detail. These tools detect and classify conflicts, such as left-turn conflicts or yielding conflicts, enabling us to predict potential crash scenarios based on behavioral patterns at intersections. This proactive analysis allows us to recommend design changes and interventions before crashes occur.
Then, we explored the noncompliance component in a certain area, like red light violations or jaywalking. For instance, our analysis revealed that one in every four pedestrians does not use crosswalks. By integrating historical crash data, proactive trajectory analysis, and noncompliance trends, we developed a tool that ranks intersections based on multiple criteria. These include potential high-crash scenarios, contributing factors, and the economic impact of injury severity at specific locations.
Determining Key Factors Linked to Injury Severity in Intersection-Related Crashes in NJ. Deep Patel, Rowan University (2023 Research Showcase). Click image for slides.
Additionally, the research explored how emerging technologies, such as connected and autonomous vehicles, could be adapted to enhance intersection safety. By conducting trajectory analyses, we assessed how data from these technologies could inform future safety measures and interventions.
Overall, my research focused on identifying key factors within intersection boundaries to reduce crashes, improve mobility, and do so in a cost-effective manner. This comprehensive approach combines proactive analysis, advanced technologies, and human behavior insights to deliver practical and impactful solutions for roadway safety.
Q. So this tool seems to be one of the most important takeaways. Is the tool ready for NJDOT use to identify potential high crash risk intersections? Is that the main intent of the tool?
A. Yes, exactly. The tool is ready but not yet publicly available. We tested it on several intersections. It is currently a proprietary tool of my professor and myself at Rowan University. Anyone interested in using the tool can connect with us, but it is not yet publicly available and certain permissions are required.
Q. Is NJDOT using it or can they use it?
A. No, the department is not using it because this was part of my recent defense. They are aware of the tool’s capabilities because it was part of an innovative showcase. The tool’s documentation has been published through the University Transportation Center (UTC). Hopefully, in the near future, it could be applied by NJDOT.
Q. Looking ahead, you have your new position in an industry role. Would you like to continue with this sort of focus on transportation research, or are you anticipating a different career direction?
A. With my new position as a Traffic Safety and Mobility Specialist, I will be focused on transportation research, conducting high-quality industry research where I would help develop safety and mobility performance measures on certain corridors designed to move traffic more effectively and enhance safety on the roadways. My work will also include industry deployment and understanding the agencies’ concerns regarding the challenges they face.
Looking ahead, I see my career direction as a blend of research and practical implementation, ensuring that innovative solutions are not just developed but also applied to make a real-world impact. Ultimately, if my work can contribute to saving even a single life, I will consider it a meaningful and worthwhile achievement.
Patel, D., P. Hosseini, and M. Jalayer. (2024). A framework for proactive safety evaluation of intersection using surrogate safety measures and non-compliance behavior. Accident Analysis & Prevention, Vol. 192. https://trid.trb.org/View/2242428
Patel, D. (2024). “A Comprehensive ML and AI Framework for Intersection Safety: Assessing Contributing Factors, Surrogate Safety Measures, Non-Compliance Behaviors, and Cost-Inclusive Methodology.” Theses and Dissertations. 3305. https://rdw.rowan.edu/etd/3305
For over 45 years, the Transportation Pooled Fund (TPF) Program has made it possible for public and private entities to combine resources for high‑priority transportation research. By pooling funds and expertise, participating organizations can support research that can lead to innovative solutions at a lower cost to agencies and extend the reach of their research budgets.
State DOTs often fund TPF Program studies using State Planning and Research (SP&R) funds, which can be applied to transportation studies as well as research, development, and technology (RD&T) transfer activities.
We spoke with Dr. Giri Venkiteela, Innovation Officer in the Bureau of Research, Innovation and Information Transfer (BRIIT), to learn about NJDOT’s recent involvement with the Transportation Pooled Funded Program.
Q. What is the primary goal of Transportation Pooled Fund (TPF) Program?
The Federal Highway Administration leads the Transportation Pooled Fund Program
A. The Transportation Pooled Fund Program, or TPF, makes it possible for state DOTs, the Federal Highway Administration (FHWA), and other organizations to partner when there is a shared interest in solving a transportation-related problem. Partners contribute funds and other resources to cost-effectively address problems through research, planning, and technology transfer activities.
The FHWA administers the TPF Program. Only the FHWA or a State DOTs may initiate and lead a pooled fund study. Local and regional transportation agencies, private industry, foundations, and institutes of higher education can partner with sponsoring agencies to conduct pooled fund projects.
Q. What is your involvement with the TPF Program?
A. I work in NJDOT’s Bureau of Research, Innovation and Information Transfer (BRIIT) and serve as the Transportation Pooled Fund Program’s project manager, or coordinator on behalf of NJDOT. Among my responsibilities, I disseminate information about new “open” solicitations for projects from sponsoring agencies to NJDOT’s subject matter experts (SMEs) to gauge their interest in participation. Sometimes NJDOT SMEs or our customers — who network with their peers at other agencies — will hear about an upcoming or worthwhile project and ask that I monitor its status so that NJDOT can join as a partner once the project is posted. Depending on the topic, I may also serve as the agency’s SME on a particular project.
Q. How does NJDOT select project topics from “open solicitations” to join through the TPF Program?
A. The FHWA pooled funded website is publicly available and anyone can view the many “open solicitations” for projects that seek funding. We have a research budget that can and does support participation in pooled funded studies, but we also must set-aside funds and commit to the projects we join for several years over the lifetime of the research. Our budget is not a static number but dynamic. The amount that we can commit depends on how many projects NJDOT is interested in joining.
BRIIT’s Research Manager works with leadership in departmental units seeking funding to ascertain the value potential of individual projects and I offer my advice during this process as a member of BRIIT.
Q. How do NJDOT staff participate in these studies, and what are the requirements for participation?
A. The NJDOT unit managers need to assign an SME for the research project study. I serve as the research program manager but we need to have an SME who is interested in being the participant. I coordinate with FHWA on our financial commitment and make sure the FHWA website is up-to-date with our participation.
Once the project receives the necessary financial commitments, the lead state is responsible for the administration of the research project, which may include the selection of universities or contractors to perform the research.
Once we all contribute the money, the project proceeds like a regular research project. The lead state holds quarterly meetings, prepares quarterly progress reports and disseminates the research. They keep the various participating agencies informed of progress. The lead state uploads progress reports to the FHWA’s website and the states will have their own websites to share project reports, latest news and other tools.
If SMEs or other researchers want to know what’s going on in any particular quarter, they can find the information that is shared. Our SMEs may also be involved in the development of a scope of work and, over the course of the project, may have specific needs that they would like for the selected research team to address — for example, such as thorough testing of materials.
Q. What are some examples of successful pooled funded studies and their outcomes that NJDOT has joined?
Researchers at Midwest Roadside Safety Facility state-of-the-art computer software, including LS-DYNA, to simulate real-life impact events. Using computer simulation, it is possible to reduce design costs and better understand system behavior. Click for examples.
A. The Midwest Roadside Safety Pool Fund program is a fantastic pooled fund study where a lot of crash testing of roadside barriers with different materials has been performed. The costs for such testing would be difficult for one state to bear so it makes sense for the states to come together so that more testing can be done. In this case, Nebraska DOT leads the research. Back in 1990, three Midwestern states started this pooled funded research effort, but it has grown to now include 22 lead and partnering states. The participating state DOTs collaborate with the Midwest Roadside Safety Facility at the University of Nebraska-Lincoln. So, if our SMEs see a new design or material that needs testing, they can put this request forward through this study.
Clear Roads Winter Maintenance Research TPF-5(353), led by the Minnesota Department of Transportation, was a 2024 Recipient of the FHWA Transportation Pooled Fund Excellence Awards.
The Clear Roads Winter Highway Operation — now in its third phase — is another great example. The Clear Roads pooled fund project began in 2004 with four members interested in snow clearance and related issues. The project performs real-world testing of winter maintenance materials, methods, and equipment and has grown to include 39 participating states. The Minnesota’s DOT leads the project, and was recently recognized with a TPF 2024 Excellence Award.
This is just a handful of examples — there are many others being driven by state DOTs, each of which have their own unique flavors.
Learn more about research on and use of Ultra-High Performance Concrete. David Hawes, Resident Engineer for Pulaski Skyway, NJDOT is featured at 2:13.
I would also like to mention one non-state DOT sponsored research project. The Structural Behavior of Ultra High Performance Concrete project is led by the FHWA itself through its Turner Fairbanks Research Center. The project conducts various experiments with UHPC. Every state wants to know what is happening with this relatively new material. The project objective is to develop knowledge on the structural performance of UHPC materials in highway bridges and structures. The test results are expected to inform proposed structural design guidance for UHPC components and support usage of UHPC by interested DOTs.
Q. How are the results and findings of these studies disseminated to the participating agencies, public or other stakeholders?
A. Some projects are ongoing like the Midwest Roadside Safety study. Information is flowing through their research hub with project reports and other materials posted on their website along with information on conference presentations, trainings, and newsletters. If you need any information, it will be conveyed through the program.
But for some pooled fund projects, they need to implement some of the tools that they are developing so that is how they would come to contact the states, such as to have something tested or looked at. The first priority would be given to the states that are participating in the pooled funded study.
For FHWA, if something new comes out of the pooled funded study, I think they may elevate the innovations into other areas such as through the Every Day Counts Program.
Recently FHWA started a pooled fund excellence awards to highlight the importance of collaboration and partnership in transportation research and encourage states to participate. Actually, I participated as a judge last year. We selected two projects for the inaugural TPF Excellence Awards. I already mentioned the Clear Roads Winter Maintenance Research project. The other award was given for an Indiana DOT project, Member-Level Redundancy in Built-up Steel Members, which led to new AASHTO Guide Specifications.
Q. How do NJDOT SMEs who are participating in the pooled funded studies share what they have learned?
A. We have started to ask that the SMEs share a short yearly progress report that reflects upon what they may be learning. Since NJDOT is obligating funding, we need to have some kind of justification for the commitment. The reporting can help us consider the benefits of the research or innovations being advanced, and to consider some of its possible implications for NJDOT practices.
With a good and continuing dialogue with our SMEs, we should be able to determine if it makes sense to have the SMEs speak at a future NJ STIC meeting to share what they are learning and convey what is innovative about the pooled funded study’s research.
Q. Do you foresee opportunities for having selected researchers from funded projects for which NJDOT was a partner share their findings with NJDOT employees such as at a Tech Talk?
A. The SMEs are well-positioned to help us to identify whether it might make sense to invite a researcher from the study to speak. They can help identify how best to promote and disseminate the research and innovation through some other activity.
Q. Has NJDOT served as the lead organization on pooled funded research? Are there projects that NJDOT would like to lead?
A. We have not led a pooled funded research project yet, although we had some initial plans to do so before the pandemic. At this point, we think it may be more productive to join as a participating organization. We think serving as participating organization may be a cost-effective way to direct some of our funds and have our SMEs connected to meaningful research.
Of particular note, we just joined the Northeast Transportation Research Consortium (NTRC), a pooled funded study for our AASHTO Region 1, that will support peer exchange activities. The effort seeks to enhance member state collaboration in solving our common problems. This is a pooled fund initiative that is just getting launched and is led by Vermont DOT. NJDOT is one of the six participating state DOTs in the Northeast.
Q. Are there any other projects that are you are thinking of joining at this time?
A. Yes. This is an ongoing process. There are a few projects that we are considering. Solicitations can pop up throughout the year.
Resources
National Cooperative Highway Research Program. 2023. “TPF: Transportation Pooled Fund” (website). https://www.pooledfund.org/
National Cooperative Highway Research Program. 2024. “Transportation Pooled Fund – Open Solicitations” (web page). https://pooledfund.org/Browse/open
National Cooperative Highway Research Program. 2024. “Structural Behavior of Ultra-High Performance Concrete” (web page). https://pooledfund.org/Details/Study/695
National Cooperative Highway Research Program. 2024. “TPF: National Transportation Research Consortium (NTRC) (website). https://pooledfund.org/Details/Study/783
AASHTO. 2018. Guide Specifications for Internal Redundancy of Mechanically Fastened Built‑Up Steel Members. Washington, DC: American Association of State Highway and Transportation Officials.
AASHTO. 2018. Guide Specifications for Analysis and Identification of Fracture Critical Members and System Redundant Members. Washington, DC: American Association of State Highway and Transportation Officials.
The New Jersey Department of Transportation (NJDOT) Research Library has approximately 200 publications from the American Association of State Highway and Transportation Officials (AASHTO) available electronically in an internal SharePoint drive. These documents are available only to NJDOT employees and will not be found in the New Jersey State Library’s catalog.
These documents include manuals, specifications, and guidance from AASHTO and its industry partners. A current list of publications that can be accessed is here.
Additional documents are available in print and/or electronic formats from the NJDOT Research Library. There is some overlap in the electronic and print documents. For more information on the library’s AASHTO resources, please see Did You Know? AASHTO and TRID Resources – NJDOT Technology Transfer
To request any of these documents, please contact the NJDOT research librarian, Eric Schwarz, MLIS, at (609) 963-1898, or email library@dot.nj.gov. Many of the documents require a special login procedure, which will be explained when the Research Library sends the user a link to the document.
Artificial Intelligence (AI) is rapidly reshaping transportation by improving safety, efficiency, and sustainability across various applications. From real-time traffic monitoring to predictive infrastructure maintenance, AI is becoming a critical tool for advancing transportation systems in New Jersey and nationwide. This article covers the use of AI in transportation research and implementation, with examples from the 2024 NJDOT Research Showcase, New Jersey and other state DOTs.
AI on Display at the 2024 Research Showcase
NJDOT held its 2024 Research Showcase on October 23, highlighting innovative transportation research and its implementation throughout New Jersey. During the morning panel discussion, Giri Venkiteela, Innovation Officer in NJDOT’s Bureau of Research, Innovation & Information Transfer, stated that Artificial Intelligence (AI) held significant promise for producing economic and environmental advancements in transportation due to its real-time predictive capabilities and proposed that NJDOT adopt protocols that can adapt to the pace of AI. Similar insights were heard throughout the showcase, where AI emerged as a central theme across numerous presentations and discussions.
AI, encompassing subcategories like Machine Learning (ML) and Artificial Neural Networks (ANN), allows researchers to analyze and model large data sets in real-time, saving significant labor hours and producing efficient, immediate results. Throughout the showcase, various projects ranging from enhancing pedestrian safety to predicting natural disasters utilized AI-based models.
Deep Patel received the 2024 Outstanding University Student in Transportation Research. As part of a research team at Rowan University, Patel deployed the AI model, YOLO-v5, to analyze video data from multiple New Jersey intersections, providing information on pedestrian volumes, traffic volumes, and the rate of vehicles running red lights, among other variables. The team then ranked intersection safety using the metrics analyzed by the AI model.
Slide from Meiyin Liu’s presentation on real-time traffic flow analysis.
Patel’s research exemplifies the growing trend of integrating AI methods into traffic safety analyses, which continued into several presentations given in the afternoon Safety Breakout Sessions. Here, Rutgers professor Meiyin Liu presented her method for estimating real-time traffic flow through a combination of Unmanned Aerial Systems (UAS) and deep learning algorithms. A computer-mounted UAS would be used to record video data of a highway, which then gets transmitted to the YOLO-v5 computer vision AI that detects vehicle volume and estimates speed. This data collection method facilitates a real-time traffic flow analysis across a comprehensive geographic coverage that could enhance traffic performance and crash risk prediction. Afterward, Branislav Dimitrijevic, a member of an NJIT research team, showcased an AI-driven project that utilized LiDAR technology and YOLO-v5 computer vision to activate a Rectangular Rapid Flashing Beacon (RRFB) when pedestrians approached crosswalks, enhancing road safety.
Poster by Indira Prasad from the 2024 NJDOT Research Showcase.
AI’s critical role in the maintenance and preservation of infrastructure was also evident in the afternoon’s Sustainability Breakout Sessions. Indira Prasad, a Stevens Institute of Technology graduate student, conducted a review of future innovations in sustainable and resilient infrastructure. Prasad explained how AI’s pattern recognition capabilities could be used to analyze large data pools and help forecast natural disasters, enabling a rapid response to augment existing infrastructure. Surya Teja Swarna, a Rowan University postdoctoral researcher, demonstrated an innovative approach where state DOTs could use mobile phones mounted on vehicles to record roadway surface deformations, which then would be analyzed in real-time by an AI computer vision software, drastically reducing the time and costs required for road condition assessments.
Deployment of AI in Programs and Project Implementation
In addition to research from academic institutions, State DOTs and various other state, local and public transportation organizations have started to deploy AI-based methods and tools on various programs and projects.
Peter Jin, a Rutgers professor, received the 2024 NJDOT Research Implementation Award for his role in the New Brunswick Innovation Hub Smart Mobility Testing Ground (Data City SMTG). The project, created in partnership with NJDOT, the City of New Brunswick, and Middlesex County, functioned as a living laboratory for transportation data collection, containing Self-Driving Grade LiDAR sensors and computing devices across a 2.4-mile multi-modal corridor. Private and public sectors can use the data to enhance their advanced driving systems, automated vehicle models, and other AI-based projects.
Additionally, NJDOT has established a program integrating unmanned aerial systems (UAS) into its transportation operations. UASs provide high-quality survey and data mapping information, which, when paired with AI-based technologies, can be analyzed in real time to document roadway characteristics or conduct damage assessments for natural disasters. Meiyin Liu’s real-time traffic flow assessment research is one example of how UAS can be paired with AI.
The methods used by CAIT to detect and analyze railroad-grade crossings. Courtesy of CAIT.
The use of AI for railroad-grade crossing detection has been demonstrated on several projects in recent years. NJ TRANSIT, the statewide transit agency, recently received a $1.6 million grant from USDOT to implement a railroad-grade crossing detection system. The system, developed in partnership with CAIT researchers, will be deployed at 50 grade crossings and aboard five light rail vehicles throughout the state. The railroad-grade crossing detection system features multiple cameras on grade crossings and light rail vehicles to record data for an AI computer vision model that monitors and analyzes grade crossing behavior such as near-miss incidents.
Visual example of how LiDAR senses the surrounding environment.
Other State DOTs have also started to implement AI-based programs. The Georgia Department of Transportation, in partnership with Georgia Tech, completed a survey of 22,000 road signs around potentially dangerous road curves using AI and vehicle-mounted mobile phone cameras to improve safety at road curves. The Texas Department of Transportation (TxDOT) assessed pavement conditions using LiDAR and AI. TxDOT’s project shares similarities with the research presented by Surya Teja Swarna, but it utilized LiDAR instead of a mobile phone camera.
In 2022, the Nevada Department of Transportation partnered with the Nevada Highway Patrol, the Regional Transportation Commission of Southern Nevada, and a private technology company to launch an AI-based platform that facilitated the reporting of real-time crash locations. A study on this project found that the AI platform uncovered 20 percent more crashes than previously reported and reduced emergency response time by nine to ten minutes on average while eliminating the need to dial for help.
Recent National Research
Responses from state DOT officials demonstrate the varied applications of ML solutions. Courtesy of NCHRP.
The National Cooperative Highway Research Program (NCHRP) published a 2024 research report, Implementing and Leveraging Machine Learning at State Departments of Transportation, that identifies trends in AI transportation research and implementation with a specific focus on machine learning and creates a roadmap for future implementation. The researchers surveyed State DOTs on plans regarding AI, reported case studies of ML implementation by State DOTs, and listed strategies to help DOTs facilitate further inclusion of AI solutions.
The survey of the state DOT officials covered various topics, including the transportation agency’s familiarity with AI methods and tools, types of methods and applications utilized, and challenges in implementation. Among the challenges to implementation, DOT officials noted a lack of public trust, insufficient data collection and storage infrastructure, and, most commonly, scarce labor with knowledge of AI. Most computer and data scientists choose to work in the private sector, and it can be difficult to recruit them to a transportation agency.
The NCHRP report also included multiple case studies from state DOTs such as Nebraska, California, and Iowa, documenting the experiences of these agencies in developing and implementing ML programs.
Nebraska DOT (NDOT) used a computer vision Convolutional Neural Network (CNN) algorithm to detect and analyze guardrail quality. NDOT recorded 1.5 million images of guardrail data and used AI to save time and money compared to the manual detection alternative. Among the challenges, NDOT observed that their agency did not have the necessary infrastructure to process large volumes of data and lacked in-house ML expertise. The agency solved the former issue by using a private vendor to process the data and the latter by collaborating with consultants from the University of Nebraska. The algorithm achieved accuracies of 97 percent for guardrail detection and 85 percent for their classification into three types.
The California Department of Transportation (Caltrans) has leveraged AI/ML applications across various projects and partnered with numerous tech companies, including Google. One area of emphasis for Caltrans has been workforce capacity development. While most staff do not have experience with AI-based data analytics, they do have experience with GIS. Caltrans has worked with GIS tool developers to incorporate ML functionalities into the basic user interface of GIS programs, making it more intuitive for their workforce.
Iowa State University, funded by the Iowa Department of Transportation, developed a real-time ML tool to monitor highway performance, enabling a rapid response to traffic congestion. The researchers identified the need for high-performance computing as a significant challenge preventing large-scale implementation. Mass deployment of the tools used in the research study would require a considerable expense, partially due to the stipulation that the code be at least 99 percent reliable.
For more information on the application and implementation of AI by transportation agencies, the National Academies of Sciences, in collaboration with the NCHRP, published two additional reports in 2024. One, Artificial Intelligence Opportunities for State and Local DOTs: A Research Roadmap, utilizes machine learning methods to analyze research trends in AI and how State DOTs can implement the research. The other, Implementing Machine Learning at State Departments of Transportation: A Guide, serves as a complementary document to the NCHRP report on implementing and leveraging machine learning.
On a national level, USDOT published its Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence compliance plan in September 2024. USDOT has taken several measures to advance the implementation of AI, including forming an AI Governance Board chaired by the Deputy Secretary and vice-chaired by a new Chief Artificial Intelligence Officer (CAIO), creating an AI Accelerator Roadmap, and providing funds for AI research and implementation.
Lastly, the American Association of State Highway and Transportation Officials (AASHTO) hosted a knowledge session examining the role of AI in transportation in April 2024. Practitioners on the panel highlighted the potential of AI in eliminating the dangerous aspects of data collection and allowing for proactive solutions rather than reactively responding to crashes or injuries. The panelist discussion touched upon the importance of building trust in a period of rapid AI development, noting the critical role that academic researchers can play as partners with state DOTs to advance and develop the AI technology in ways beneficial for traffic safety and workforce safety, among other topics.
TRID Database
Artificial Intelligence-based research can be found via TRB’s TRID database. The following are some relevant articles published on recent New Jersey transportation research in AI.
Bagheri, M., B. Bartin, and K. Ozbay. (2023). Implementing Artificial Neural Network-Based Gap Acceptance Models in the Simulation Model of a Traffic Circle in SUMO. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2677. https://trid.trb.org/View/2166547
Hasan, A.S., M. Jalayer, S. Das and M. Bin Kabir. (2024). Application of machine learning models and SHAP to examine crashes involving young drivers in New Jersey. International Journal of Transportation Science and Technology, Vol. 14. https://trid.trb.org/View/2162338
Hasan, A.S., M. Jalayer, S. Das and M. Bin Kabir. (2023). Severity model of work zone crashes in New Jersey using machine learning models. Journal of Transportation Safety & Security, Vol. 15. https://trid.trb.org/View/2190127
Najafi, A., Z. Amir, B. Salman, P. Sanaei, E. Lojano-Quispe, A. Maher, and R. Schaefer. (2024). A Digital Twin Framework for Bridges. ASCE International Conference on Computing in Civil Engineering 2023, American Society of Civil Engineers, pp 433-441. https://trid.trb.org/view/2329319
Nayeem, M., A. Hasan, M. Jalayer. (2023). Investigation of Young Pedestrian Crashes in School Districts of New Jersey Using Machine Learning Models. International Conference on Transportation and Development 2023, American Society of Civil Engineers. https://trid.trb.org/View/2196775
Patel, D., P. Hosseini, and M. Jalayer. (2024). A framework for proactive safety evaluation of intersection using surrogate safety measures and non-compliance behavior. Accident Analysis & Prevention, Vol. 192. https://trid.trb.org/View/2242428
Zaman, A., Z. Huang, W. Li, H. Qin, D. Kang, and X. Liu. (2023). Artificial Intelligence-Aided Grade Crossing Safety Violation Detection Methodology and a Case Study in New Jersey. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2677. https://trid.trb.org/VCiew/2169797
Zaman, A., Z. Huang, W. Li, H. Qin, D. Kang, and X. Liu. (2024). Development of Railroad Trespassing Database Using Artificial Intelligence. Rutgers University, New Brunswick, Federal Railroad Administration, 80p. https://trid.trb.org/view/2341095
Rail Safety, I. D. E. A. (2024). An Artificial Intelligence Aided Forward-Facing Camera Video Data Analytics System for Rail Safety. The National Academies of Sciences and Transportation Research Board. https://www.trb.org/Main/Blurbs/183277.aspx
The 26th Annual NJDOT Research Showcase provided an opportunity for the New Jersey transportation community to learn more about the broad scope of research projects and technology transfer activities being conducted by institutions of higher education partners and their associates. The annual event serves as a showcase to highlight the benefits of transportation research, including NJDOT’s own program. This event was an in-person event with a livestreaming option with sessions held from 9:00am-2:45pm on October 23, 2024.
This year’s Showcase theme, “Pathways to Sustainability,” served as the organizing framework for the speakers and panelists during the morning plenary session. Throughout the day the Research Showcase featured presentations on infrastructure, safety, and sustainability topics being performed by research faculty, staff, students, and NJ agencies. Several awards were presented in recognition of research and implemented innovations.
TheResearch Showcase Program Agendaprovides more information on the day’s proceedings, including presented topics and invited speakers. Recordings of the plenary and breakout sessions, and the presentations and posters shared during the event can be found below.
MORNING
WELCOMING AND INTRODUCTORY REMARKS
David Maruca, Program Development Administrator, Rutgers Center for Advanced Infrastructure and Transportation (CAIT), served as the moderator for the morning session, offering some housekeeping remarks and walked through the morning’s agenda.
Morning Plenary and Keynote
Eric Powers, Assistant Commissioner Statewide Planning, Safety and Capital Investment at NJDOT, welcomed attendees to the 26th Annual NJDOT Research Showcase, explaining the purpose and theme of the event, “Pathways to Sustainability,” and acknowledging several parties, including NJDOT Bureau of Research, Innovation and Information Transfer (BRIIT) staff, Rutgers-CAIT, and the leadership of NJDOT and FHWA for their planning and participation in the day’s event along with the research partners whose work was being showcased.
Francis O’Connor, Commissioner, NJDOT, thanked several partners for their involvement in organizing the Research Showcase event. He expressed his enthusiasm for the research mission, noting that research is at the heart of progress for innovation in transportation. He framed the event as an opportunity to convene and collaborate with talented researchers and staff in tackling challenges that still confront us in transportation. Mr. O’Connor spoke about the day’s sustainability theme and emphasized the integral importance of safety in all that the agency does. The recent actions by NJDOT to improve safety for all road users, and the NJDOT highway workforce were highlighted by the Commissioner, among other topics.
Francis O’Connor, Commissioner, New Jersey Department of Transportation
Sutapa Bandyopadhyay, Planning and Program Development Manager, Federal Highway Administration (FHWA) New Jersey Division, praised the NJDOT Research Showcase’s “Pathways to Sustainability” theme and noted its close alignment with FHWA’s newest strategic plan which contains climate and sustainability as a core goal. She spoke of the strategic plan’s focus on greenhouse gas (GHG) emissions reduction and resilient infrastructure. She highlighted select formula and discretionary programs supported through the Infrastructure Investment and Jobs Act (IIJA), including the Carbon Reduction Program, the National Electric Vehicle Infrastructure (NEVI) deployment, and discretionary programs to reduce truck emissions in port facilities. In her remarks, she also emphasized the importance of research to assist in supporting the current administration’s major planning goals and targets (e.g, net-zero carbon emissions by 2050, adoption of resiliency plans by 50% of the states and MPOs by 2026, and 40 percent of the transportation clean energy benefits delivered to disadvantaged communities in alignment with the Justice40 initiative).
KEYNOTE ADDRESS
Jim Tymon, Executive Director at American Association of State Highway and Transportation Officials (AASHTO) provided the keynote address, “Navigating the Storm: Resilience, Sustainability and Surface Transportation”. His address reminded those in attendance of the importance of collaboration in continuing to build a resilient and sustainable transportation network.
Mr. Tymon began his talk by introducing AASHTO, a multi-modal focused trade association that works with 52 state DOTs (including D.C. and Puerto Rico) to provide codified guidance and a platform for sharing knowledge. AASHTO is governed by a strategic plan, created in 2020, that expands their focus beyond the technical goals of transportation to developing “quality of life through strategic leadership”.
AASHTO hosts over thirty different committees and councils in which state DOTs can learn from each other’s experiences. Tymon’s remarked that AASHTO’s President has coined this process as “R&D” — or rip-off and duplicate. This form of “R&D” keeps departments from having to re-invent the wheel themselves and often leads to more successful outcomes.
This collaboration, he pointed out, is necessary for navigating the storm of increased climate disasters and unpredictable weather conditions. In the transportation field, the effects of climate change are both economically devastating and logistically challenging to address. In 2023 alone, climate related disasters cost the U.S. at least $92.9 billion in damages and in the past forty-three years, there have been 376 disasters, each costing over $1 billion. He stated, “Whether or not you are a climate change denier, or somebody that believes in the fact that our climate is changing, we have events that we are dealing with on a regular basis that we need to adapt to and that we need to take into account as we are dealing with our transportation network”.
Mr. Tymon proceeded with additional data and statistics to illustrate how State DOTs were fiscally impacted by the storms. Mr. Tymon laid out two avenues of solutions for addressing this growing issue: 1) building a more resilient transportation system; and 2) building a more sustainable transportation system.
Jim Tymon, Executive Director at American Association of State Highway and Transportation Officials (AASHTO)
Navigating the Storm: Resilience, Sustainability and Surface Transportation. Mr. Jim Tymon, Executive Director, American Associations of State Highway and Transportation Officials (AASHTO).
To build a resilient transportation system and network, Mr. Tymon recommended deeply considering how we are designing and building transportation systems and taking into consideration a variety of changing climate factors. Mr. Tymon presented the Resilience Planning Cycle from the Port Authority of New York and New Jersey as a model for this type of planning. Fortunately, there is a variety of federal assistance programming available through the Infrastructure Investment and Job Act, including the PROTECT program. PROTECT (Promoting Resilient Operations for Transformative, Efficient, and Cost-saving Transportation) is a formula program that is given annually to each state to use for state resilience projects. This funding can also assist States with the development of a state Resilience Improvement Plan, which is not a requirement, but does ensure a higher federal match.
Mr. Tymon’s second recommendation, to build a more sustainable transportation system, can be made possible through intentional efforts such as encouraging a modal shift by transportation users. He noted that encouraging a shift of transportation usage from single use cars to buses, trains, walking, cycling, or using more fuel-efficient cars, can help to reduce carbon emissions that may slow the effects of climate change.
AASHTO recently assisted with the administration’s U.S. National Blueprint for Transportation Decarbonization, which laid out guidance for decarbonizing the transportation network. He highlighted several methods in the Blueprint from planning and leveraging telework, to e-commerce and travel demand management. State agencies receive financial support for developing carbon reduction strategies through programs like the Carbon Reduction Program as well as the National EV Infrastructure Program (NEVI).
Mr. Tymon closed his talk by sharing a recent commercial created by the Tennessee Department of Transportation which aired during a recent football game between Florida and Tennessee. The video highlighted the collective rebuilding and road improvement efforts of Tennessee DOT and Florida DOT volunteers in the wake of Hurricane Helene. Mr. Tymon explained that prior to landfall, Hurricane Helene was expected to impact Florida greatly. To help, Tennessee DOT members were preparing to travel down to Florida in its wake. Instead, when Tennessee became more impacted because of the Hurricane, Florida DOT employees traveled up to Tennessee to help. The video and situation, Mr. Tymon noted, represents how state DOTs “can work together to help mitigate some of those impacts (climate change) and recover.”
Mr. Tymon responded to questions in the Q&A session that followed his keynote remarks.
MORNING SESSION PANEL DISCUSSION
An interactive panel discussion, “How is New Jersey Department of Transportation Creating Pathways to Sustainability?” followed the keynote session. NJDOT staff representatives presented several examples of sustainability initiatives underway at NJDOT in various areas including construction and materials selection, pavement preservation, transportation planning, project management and research. The presenters reflected on the opportunities and persistent challenges as well as the benefits of addressing sustainability in New Jersey.
The panelists included:
Alex Borovskis, Director, New Jersey Department of Transportation Division of Construction and Materials
Robert Blight, Executive Manager, New Jersey Department of Transportation Division of Pavement & Drainage Management and Technology Bureau
Krishna Tripathi, Project Management Specialist, New Jersey Department of Transportation Division of Project Management
Mohab Hussein, Supervising Engineer, New Jersey Department of Transportation Bureau of Structural Design & Geotechnical Engineering
Sushant Dargi, Principal Engineer, Planning, New Jersey Department of Transportation Bureau of Statewide Strategies
Giri Ventikeela, Innovation Officer, Bureau of Research, Innovation & Information Transfer
Pathways to Sustainability Panel
How is New Jersey Department of Transportation Creating Pathways to Sustainability?
Participants responded to a series of questions posed by the moderator and by the audience members.
Panelists shared their views on how the New Jersey Department of Transportation is creating pathways to sustainability.
AWARDS
The program continued as Pragna Shah, New Jersey Department of Transportation, announced several awards given in recognition of research, innovation and implementation efforts. Below is a listing of the award winners presented at this year’s showcase:
2024 Outstanding University Student in Transportation Research Award – Deep Patel, Rowan University. Mr. Patel received the award for his valued contributions to research on “Real-Time Traffic Signal System Performance Measurement” through successive phases and several other recent and ongoing NJDOT projects.
2024 NJDOT Research Implementation Award – Dr. Peter Jin, Rutgers University, New Brunswick Innovation Hub Smart Mobility Testing Ground (Data City SMTG). This project, partially funded by NJDOT, generated a living laboratory for transportation data collection and smart technology innovation across a 2.4-mile multi-modal corridor in New Brunswick.
2024 Best Poster Award – Swathi Malluru, Rowan University, Performance Evaluation of Full-Depth Reclamation and Cold In-Place Recycling Asphalt Mixtures at Varying Amounts of Bituminous and Cementitious Additives. This poster described research activities conducted towards evaluating best practices in Full-Depth Reclamation (FDR) and Cold In Place Recycling (CIR) asphalt rehabilitation. The researchers distributed surveys to state agencies, conducted a literature review and performed laboratory tests, finding that 3 percent emulsion, with 1 percent cement worked best for FDR mixes, and 2 percent emulsion or 1.5 percent foamed bitumen for CIR mixes.
2024 Research Champion Excellence Award –Yong Zeng and Emmanuel Bassey, Technical Advisory Panel at the New Jersey Department of Transportation. This award recognized Yong Zeng’s and Emmanuel Bassey’s dedication serving as Technical Advisory Panel (TAP) members for the research project, Advanced Reinforced Concrete Materials for Transportation Infrastructure. Their work greatly contributed to the success and implementation of the project, which received an AASHTO National High Value Research Award in 2024.
2024 NJDOT Build a Better Mousetrap (BABM) Award – Bishoy Abdallah, Senior Engineer in Transportation Roadway Design at NJDOT. The BABM award was given to Bishoy Abdallah for his creative response to current NJDOT roadway standards that require all resurfacing and preservation projects to upgrade existing inlet curb pieces to have a smaller opening. To make more efficient the process of upgrading existing inlet curbs, Abdallah created two details; one specifically for barrier curbs that do not need to be replaced, and the second for damaged or cracked barrier curbs.
Awards Ceremony
Presentation of 2024 Awards
PRESENTATION OF AWARDS
2024 Outstanding University Student in Transportation Research Award, Deep Patel, Rowan University, Real-Time Traffic Signal System Performance Measurements
2024 NJDOT Research Implementation Award, Dr. Peter Jin, Rutgers University New Brunswick Innovation Hub Smart Mobility Testing Ground (Data City SMTG).
2024 Best Poster Award, Swathi Malluru, Rowan University, Performance Evaluation of Full-Depth Reclamation and Cold In-place Recycling Asphalt Mixtures.
2024 Research Champion Excellence Award, Yong Zeng and Emmanuel Bassey, New Jersey Department of Transportation. Advanced Reinforced Concrete Materials for Transportation Infrastructure.
2024 NJDOT Build a Better Mousetrap Award, Bishoy Y. Abdallah. New Jersey Department of Transportation, Division of Highway and Traffic Design. Replacing Inlet Curb Pieces in Existing Concrete Barrier Curb
HIGH VALUE RESEARCH
In addition to the awards announced and distributed by NJDOT for the 26th Annual NJDOT Research Showcase, the event highlighted two NJDOT research projects that were recognized with 2024 AASHTO National High Value Research Awards at the Research Advisory Committee (RAC) national meeting in Columbus, Ohio in late July 2024.
Advanced Reinforced Concrete Materials for Transportation Infrastructure. One of only 16 research projects nationwide to receive the 2024 AASHTO National High Value Research Award, this project evaluated the performance of three highly ductile concrete materials in comparison to two standard NJDOT mixtures. The results of the research can be used to guide best practices around deploying novel concrete materials to improve the service life of reinforced concrete infrastructure. Principal Investigators: Dr. Matthew Bandelt and Dr. Matthew Adams of New Jersey Institute of Technology; Technical Advisory Panel: Yong Zeng, Nehemie Jasmin, Emmanuel Bassey; Research Project Manager: Dr. Giri Venkiteela of NJDOT BRIIT.
Innovative Pothole Repair Materials and Techniques. This research project tested several new pothole repair materials and techniques including the use of recycled asphalt pavement (RAP) and PVA fibers. The research findings can be used to produce longer lasting and more sustainable roadways. The research project received a Supplementary National High Value Research Award from the AASHTO RAC. Principal Investigators: Dr. Hao Wang and Dr. Husam Najm at Rutgers-CAIT; Technical Advisory Panel: Sadime Absolam, Jeff Evanylo, Emmanuel Bassey, Kenrick Layne, Nicholas Colangelo, Anupkumar Patel, Roger Estivalletti, Yong Zeng; Research Project Manager: Dr. Giri Venkiteela of NJDOT BRIIT.
2024 National High Value Research Award, Yong Zeng, Nehemie Jasmin, Emmanuel Bassey, Giri Venkiteela, and Matthew Bandelt. NJDOT. Advanced Reinforced Concrete Materials for Transportation Infrastructure.
2024 AASHTO Supplementary National High Value Research Award, Sadime Absolam, Yong Zeng, Emmanuel Bassey, Giri Venkiteela, Husam Najm, Hao Wang and Anupkumar Patel. NJDOT. Innovative Pothole Repair Materials and Techniques.
AFTERNOON
In the afternoon, concurrent break-out sessions were held and research presentations were given on the topics of Infrastructure, Sustainability and Safety. Students and researchers at New Jersey’s colleges and universities also presented their research objectives, methods and findings in a concurrent poster session offering those in attendance an opportunity to learn more about ongoing and recently completed research and interact with the researchers.
INFRASTRUCTURE BREAKOUT
Infrastructure Sessions
Evaluation of Performance of Bridge Deck with UHPC and LMC Overlays through Accelerated Structural Testing. Nenad Gucunski, Rutgers University
Complex Simulation of Large Ship Impacts on Bridges. Anil K. Agrawal, The City College of New York
Navigating the Future: Sustainable & Resilient Infrastructure. Indira Prasad, Stevens Institute of Technology
Cost-Effective Pavement Management System for Municipalities in New Jersey. Yusuf A. Mehta and Surya Teja Swarna, Rowan University
SUSTAINABILITY BREAKOUT
Sustainability Sessions
How Concrete is Becoming a Carbon Sponge. Mohamed Mahgoub, New Jersey Institute of Technology
Development of Pavement Design Procedures and Construction Specifications for Cold Central Plant Recycling (CCPR) Asphalt Mixtures. Abhary Eleyedath, Rowan University
Towards Use of Stabilized Sediments as a Sustainable Alternative to Traditional Infrastructure Materials: A Laboratory and Numerical Study. Tyler J. Oathes, Rutgers University
Life-cycle assessment of ultra-high-performance concrete (UHPC) beams using advanced monitoring technologies. Fatemeh Mohammadi Ghahsareh, Stevens Institute of Technology
SAFETY BREAKOUT
Safety Sessions
Towards UAS-based Real-time Video Streaming and Data Analytics for Estimating Highway Traffic Flow Characteristics. Meiyin Liu, Rutgers University
Enhancing VRU Safety in Urban Streets Using LiDAR and Crossing Warning System. Joyoung Lee, New Jersey Institute of Technology
Examining the Applicability of Waze Crash Alert as a Real-Time Crash Detection Tool. Dejan Besenski, New Jersey Institute of Technology
Developing a Pedestrian-Scale Lighting Resource to Improve Safety for Vulnerable Road Users. Ruqaya Alfaris and Greg Woltman, Rowan University and Rutgers University
2024 POSTER PRESENTATIONS
Development of a model to predict the Micro-Deval Abrasion (MDA) Resistance Based on Mechanical and Minerals Oxides Properties of Aggregates
Investigating Mechanical Responses of Cold In-Place Recycled Asphalt Pavement Sections Under Accelerated Truck Loading by Finite Element Modeling
Integrating AI to Mitigate Climate Change in Transportation Infrastructure
Performance Evaluation of Full-Depth Reclamation and Cold In-Place Recycling Asphalt Mixtures at Varying Amounts of Bituminous and Cementitious Additives
Assessment of Box Culvert Reinforcement Using Ground Penetrating Radar: A Case Study of NJDOT Structures
“Equity & Safety” Hand in Hand on the Road to Success
Artificial Intelligence Aided Railroad Grade-Crossing Vehicular Stop on Track Detection and Case Studies
Review of Concrete Structure Demolition Technologies
Determining the Effectiveness of Commercial Vehicle Safety Alerts
The 26th Annual Research Showcase was organized and sponsored by the NJDOT Bureau of Research in partnership with the New Jersey Local Technical Assistance Program (NJ LTAP) at the Rutgers Center for Advanced Infrastructure and Transportation (CAIT) and co-sponsored by the Federal Highway Administration.
