Heavy traffic volumes, frequent lane merges, toll plazas, and complex interchanges often create conditions for sudden and forceful vehicular stops, known as harsh braking (HB). Traditional safety studies rely on historical crash records, a reactive approach that delays countermeasures. Since HB events are continuously captured by connected-vehicle telematics, their spatial and temporal patterns offer a proactive surrogate for identifying crash-prone roadway segments. Therefore, this study evaluates the potential of harsh braking (HB) events as a surrogate measure of crash risk on New Jersey interstate highways. More than 8.5 million Drivewyze telemetry records and 45,000 police-reported crashes from July to December 2024 were analyzed. HB events were identified by a deceleration threshold of 6 ft/sec² (approximately 0.2g) and spatially matched to one-mile highway segments along with crash data. Descriptive analysis revealed strong spatial clustering of HB events and crashes along high traffic volume corridors such as I-95, I-80, I-78, and I-287, particularly near toll plazas and complex interchanges. Seasonal patterns showed HB counts peaking in late fall, coinciding with higher traffic congestion and adverse weather conditions. Statistical modeling using Negative Binomial (NB) and Zero-Inflated Negative Binomial (ZINB) regressions demonstrated a positive and significant relationship between HB events and crash counts. In the preferred ZINB model, the HB coefficient was 0.01 (p = 0.03), indicating that each additional HB event was associated with roughly a 1 % increase in expected crash frequency per segment. Although the per-event effect was modest, segments with repeated HB activity exhibited substantially elevated crash risk; for instance, an increase of 10 HB events correspond to an expected crash frequency of about 10 % higher. These findings demonstrate that crowdsourced telematics can serve as a practical, proactive tool for highway safety management, supporting early detection of high-risk locations and guiding countermeasures such as improved signage, targeted enforcement, and geometric enhancements before crash records accumulate.
Md. Tufajjal Hossain is a Ph.D. student in Transportation Engineering at the New Jersey Institute of Technology (NJIT). His research focuses on traffic flow modeling, intelligent transportation systems, and AI-driven traffic safety analysis. His recent work includes developing real-time incident detection models using crowdsourced Waze data and designing a data-driven framework for optimal Safety Service Patrol route identification based on historical crash data. He also explores crash severity prediction using large language models to enhance roadway safety analytics. At NJIT, he serves as a Teaching Assistant and has contributed to NJDOT-funded research at the Intelligent Transportation Systems Research Center. He is the recipient of the 2025 ITSNJ Outstanding Graduate Student Award and the Best Poster Award at the 2024 ITSNJ Annual Meeting, recognizing his academic excellence and contributions to advancing intelligent and data-driven transportation systems.
A significant portion of ready-mixed concrete, estimated at around 3% of total production, is returned to plants for disposal each year due to issues such as slump loss during transport, surplus production, and strict adherence to the 90-minute discharge time limit set by ASTM C94 and referenced in ACI 318-19. While this rule aims to preserve concrete quality, it often leads to the rejection of truckloads, particularly in congested urban areas, thereby increasing costs, waste generation, and environmental impacts.
To address this challenge, research funded by the Ready Mixed Concrete (RMC) Research & Education Foundation and Portland Cement Association (PCA) examined the effects of extending discharge time on durability and performance. Concrete mixtures, representative of field practice, were prepared and tested at intervals up to 150 minutes, with properties such as air content, slump, temperature, compressive strength, freeze-thaw resistance, and surface resistivity evaluated.
The findings revealed that extending discharge time to 150 minutes had no significant adverse effect on fresh or hardened properties, suggesting that current specifications are overly conservative and could be revised to reduce unnecessary waste, costs, and environmental burdens.
Mohamed Mahgoub, PhD and PE, is an NJIT Associate Professor and Concrete Industry Management Program Director. He is also a Fellow of ACI. He is an expert in bridge rehabilitation, inspection, rating, design and analysis. Dr. Mahgoub received his Master’s Degree from McMaster University in Hamilton, Ontario, Canada and his doctorate from Carleton University, Ottawa, Canada. Prior to joining NJIT, he was the lead bridge engineer for the Chicago consulting firm Alfred Benesch & Company, working on bridge design for the Michigan DOT. His personal experience includes: highway bridge analysis and design, rehabilitation and construction, and scour analysis. Dr. Mahgoub has designed several bridges in Michigan, Illinois, Wisconsin and Pennsylvania. He has also performed several bridge inspections and load rating in several big cities in Michigan. He was in charge of performing annual scour analyses of all primary and secondary bridges in Calhoun County, MI. After joining NJIT, Dr. Mahgoub was involved in research of several construction material projects for several associations, companies, and state institutions. He was also involved in RAC research. Dr. Mahgoub has served as a member in organizations such as ASCE, PCI, ICRI, and ACI. Dr. Mahgoub has been appointed as the vice president of the local New Jersey ACI Chapter, has been selected as a judge for their annual award, and is also the advisor of NJIT ACI Student Chapter. Dr. Mahgoub has more than 20 technical and scientific publications and presentations to his credit. Dr. Mahgoub has been also serving as a panelist for the NSF and NRC.
Current structural design practices for infrastructure projects rely on time-intensive manual calculations and code compliance verification, creating bottlenecks in project delivery and potential for human error. This research presents a multi-agent Large Language Model (LLM) framework that automates code-compliant infrastructural design while maintaining interpretability and verifiability which is essential requirements for infrastructure applications.
The framework employs specialized LLM agents coordinated through task distribution: a Task Dispatcher routes design queries to dedicated Design and Evaluation agents, which interface with deterministic calculation tools programmed according to structural design codes. An Expert Consultation agent enables iterative refinement through natural language interaction, supporting the design optimization process. Case studies on reinforced concrete beam design demonstrated exceptional performance: 97% accuracy compared to industry-standard software (SAP2000), 90% time reduction compared to traditional methods, and complete transparency through step-by-step calculations with explicit code references. Statistical validation across 30 design cases showed Mean Absolute Percentage Error below 3% for critical structural parameters.
The framework’s modular architecture enables adaptation to various infrastructure applications by incorporating different design codes and specialized calculation modules. Engineers can specify requirements in natural language while receiving compliant solutions with detailed explanations, facilitating rapid design iteration and supporting workforce development through transparent educational content. This research demonstrates an approach to infrastructure design automation that preserves engineering judgment while eliminating routine calculation tasks. The framework represents a significant step toward preparing the engineering workforce for AI-enhanced infrastructure development.
Jinxin Chen is a PhD candidate in Civil Engineering at Stevens Institute of Technology, specializing in the integration of artificial intelligence and machine learning into structural design and infrastructure applications. His research focuses on developing automated design tools that enhance workforce efficiency while maintaining engineering rigor and code compliance. Mr. Chen has authored multiple peer-reviewed publications on computational methods in structural engineering, including work on machine learning for ultra-high-performance concrete and AI-assisted design frameworks. His current research on large language model frameworks for infrastructure design aims to streamline project delivery while supporting knowledge transfer and workforce development in the engineering profession.
On August 27, 2025, the FHWA hosted a webinar titled “NJDOT’s Pilot Program for Internally Cured High Performance Concrete for Bridge Decks.” NJDOT Project Manager and Infrastructure Preservation CIA team lead Samer Rabie presented the department’s internally cured concrete (ICC) initiative.
The webinar highlighted NJDOT’s work as a case study for more than 300 participants nationwide, enabling agencies to learn from New Jersey’s experience with ICC and consider applications in their own states. After Mr. Rabie’s presentation, attendees asked questions about the EPIC2 initiative, including advice on how to achieve even water distribution, the expected life span of High Performance Internally Cured Concrete (HPIC) bridge decks, and whether internal curing techniques could be applied to other types of concrete.
Webinar Presentation
Transverse early-age cracking
As part of Round 6 of the Every Day Counts (EDC) initiative, NJDOT began implementing Ultra High Performance Concrete (UHPC) for Bridge Preservation and Repair, with plans to institutionalize its use in the upcoming bridge design manual. UHPC’s low water-cement ratio and high use of supplementary cementitious materials (SCMs) increase durability and extend service life, but also raise the risk of transverse early age cracking. This cracking results from autogenous shrinkage, when the cement consumes too much internal water, creating capillary stresses.
Cracks in UHPC bridge decks require costly, time-intensive sealing that must be reapplied every five to ten years, significantly increasing life-cycle costs. To address this issue, FHWA launched the Enhancing Performance with Internally Cured Concrete (EPIC2) initiative under EDC-7. Internal curing uses pre-wetted lightweight fine aggregate (LWFA) to supply additional moisture, improving water distribution and offsetting capillary stresses during the curing process. More than 30 years of studies show that internal curing enhances durability, lowers costs, and reduces waste.
Over 180 EPIC2 Bridge Decks are in service according to FHWA
To date, more than 15 states have deployed internal curing on over 180 bridge decks. NYSDOT, an early adopter of HPIC, reported a 70 percent reduction in early-age cracking with no added cost compared to conventional HPC or UHPC decks. NYSDOT has since mandated internal curing for all continuous bridges and bridge decks statewide. In May 2024, Mr. Rabie participated in a New York State peer exchange on the EPIC2 initiative in Albany.
NJDOT launched its HPIC implementation plan by reviewing existing research, assessing resources and mix plants, and conducting extensive coordination—internally with subject matter experts and divisions, and externally with LWFA suppliers, producers, and contractors. NJDOT also conducted risk evaluations and identified candidate bridges for potential pilot projects.
To support implementation, NJDOT secured a $125,000 STIC Incentive Grant, which funded the purchase of centrifuge apparatuses, staff training, and third-party lab support. The centrifuges measure LWFA moisture content, replacing the traditional “paper towel method,” in which pre-wetted aggregate is weighed, dried manually with industrial-grade paper towels until no moisture remains, and then oven-dried before an assessment is made of surface and absorbed moisture. While the centrifuge approach requires specialized equipment and training, it is significantly faster, less labor-intensive, and more accurate. NJDOT will phase in this method as staff gain experience.
NJDOT has identified 11 candidate bridges for HPIC pilot projects: one under construction, eight in design, and two in concept development. The active pilot—North Munn Avenue over I-280 in East Orange—features twin bridge decks, one built with UHPC and the other with HPIC, enabling a direct comparison under similar conditions.
Twin bridge deck pilot at North Munn Avenue over I-280 in East Orange
Alongside pilot projects, NJDOT is developing materials and construction guide specifications for HPIC. These include substituting 30–50 percent of total fine aggregate with LWFA, establishing a formula to measure absorbed LWFA moisture, and targeting a water content equal to 7 percent of the volume of cementitious materials. Aside from these adjustments, HPIC batching mirrors current UHPC practices.
Early HPIC bridge decks are expected to carry added upfront costs: approximately $50,000 for new mix design, trial batches, and test slabs to validate the process before construction, plus a 20–40 percent increase in unit production costs. Mr. Rabie noted that costs should decrease as specifications are refined, experience grows, and economies of scale take effect. While initial expenses may be higher, HPIC is projected to deliver substantially lower life-cycle costs, primarily by reducing resealing, which can cost around $100,000.
NJDOT’s next steps include a concrete plant outreach program in fall 2025, followed by HPIC workshops and centrifuge training in winter 2025/2026. The department will also continue to assess potential pilot projects through 2025–2026 and monitor the performance of active HPIC bridge deck projects.
Q&A
Q.Will HPIC extend the expected 25-year life span of a bridge deck?
A. The study is assessing how much maintenance HPIC bridge decks require over a 25-year lifespan. Preliminary findings suggest HPIC decks may require only about one-third the maintenance of conventional decks. NJDOT’s Bureau of Research, Innovation, and Information Transfer (BRIIT), in partnership with Rutgers University, is conducting a separate study evaluating how HPIC could extend overall service life. Early findings from NYSDOT suggest HPIC bridge decks may last up to 75 years.
Q.In South Carolina, we have faced difficulties achieving a uniform distribution of moisture for our pre-wetted lightweight fine aggregate using conventional methods like sprinklers. Do you have any suggestions on ways to fix this issue?
A. Some states have tried alternative methods for wetting LWFA. In Louisiana, for example, large bins are filled with water—like a small pool—and the aggregate is soaked for a set period to ensure uniform moisture distribution, rather than using sprinklers.
Q.Can internal curing be used on conventional concrete or is it just for HPC and UHPC?
A. Internal curing could technically be applied to conventional Class A concrete, but it is generally unnecessary. Class A concrete already contains higher water content, reducing its susceptibility to autogenous cracking. UHPC, being relatively moisture starved, benefits most from internal curing.
Q.Does NJDOT have set shrinkage limits?
A. Shrinkage is assessed project-by-project. After crack mapping is completed, a percentage of shrinkage is calculated, but there is no set limit.
A recording of the FHWA webinar is available here.
For more about HPIC and EPIC2, read the NJDOT Tech Transfer Q&A article with Samer Rabie and Jess Mendenhall.
The NJ State Transportation Innovation Council (NJ STIC) met virtually for its second Triannual Meeting of 2025 on August 6. Attendees heard updates the Core Innovation Area (CIA) Teams on progress towards the Every Day Counts Round 7 (EDC-7) goals and a featured presentation, Overcoming Challenges – Recruiting, Developing and Maintaining a Workforce to Meet Current and Future High Construction Needs, by Vicki Tilghman-Ansley, Director of Civil Rights and Affirmative Action at NJDOT.
Welcome Remarks
Amanda Gendek, Deputy Director of Statewide Planning at NJDOT, welcomed participants on behalf of Assistant Commissioner Eric Powers. She reviewed the meeting agenda and highlighted the workforce development presentation, noting its connection to the theme of the upcoming 27th Annual Research Showcase in October.
FHWA Updates
Christopher Paige, Innovation Coordinator and Community Planner at the FHWA NJ Division Office, was unable to attend this meeting. In his absence, Giri Venkiteela, Innovation Officer at the NJDOT Bureau of Research, Innovation, and Information Transfer, reported that there were no FHWA updates at this time. He added that Mr. Paige would notify NJDOT if any arose.
Mentimeter Engagement Activity Summary
Innovation recommendations from Mentimeter Engagement Activity (click to enlarge)
Following the FHWA updates, Dr. Venkiteela summarized results from the previous meeting’s Mentimeter Engagement Activity, which explored NJ STIC members’ perceptions, initiatives, challenges, requests, and projects related to innovation.
Key takeaways included:
STIC members define innovation as creativity and thinking outside the box
Member prioritize advancing AI integration and expanding electric vehicle infrastructure
Organizational silos and limited resources challenge progress
Members recommend engaging global experts and academia
Innovation efforts focus on safety, efficiency, and environmental management
Core Innovation Areas (CIA) Updates
Leaders from the Core Innovation Area (CIA) Teams provided updates on their progress toward deployment goals for their respective innovation efforts. Representatives from NJDOT and FHWA discussed EDC-7 initiatives organized under the five CIA teams: Safety, Planning and Environment, Infrastructure Preservation, Mobility and Operations, and Organizational Support and Improvement. Each team outlined their current projects, highlighting implementation efforts, key achievements, and challenges. A brief summary of each team’s update follows:
Safety
Pedestrian Scale Lighting Research & Guide. Researchers from the Alan M. Voorhees Transportation Center (VTC) at Rutgers University and Rowan University continue revising their draft pedestrian scale lighting resource. This guide will help communities identify, scope, and assess safety and community needs before implementing best practices for pedestrian-scale lighting design. Feedback from Subject Matter Experts (SMEs) is being integrated before the resource is shared with NJDOT.
Nighttime Visibility for Safety. NJDOT is finalizing the design details for traffic signal poles and mast arms in compliance with the 2015 AASHTO LRFD requirements for signalized intersection. The design improvements include enhanced integration of backplates with retroreflective tape on signal indications. Comments from key stakeholders are being incorporated into the final deliverable.
Planning and Environment
Centrifuge Apparatus
Congestion Mitigation and Air Quality Improvement Program (CMAQ) and Carbon Reduction Program (CRP). NJDOT is advancing projects aimed at reducing congestion, improving air quality, and promoting low-emission technologies. CMAQ priorities include public transit expansion, intersection upgrades, intelligent transportation systems, and EV incentives. CRP efforts focus on battery-electric buses, Complete Streets, and municipal green fleet transitions. Both programs track progress using performance metrics such as greenhouse gas reduction, increased transit use, and cleaner air. Next steps include accelerating implementation, applying AI-based traffic management, and expanding partnerships. The “It Pay$ to Plug” grant program, a CMAQ initiative, collaborates with NJDEP to expand the number of EV charging stations.
Infrastructure Preservation
Enhancing Performance with Internally Cured Concrete (EPIC2). The team received the centrifuge apparatuses purchased through STIC Incentive Fund grants and identified additional bridges as potential candidates for the EPIC² initiative. Current efforts include planning an FHWA webinar, coordinating distribution of centrifuge apparatuses to regional materials offices, and preparing final design submissions for pilot project bridges.
Mobility and Operations
Weather Savvy. NJDOT upgraded the Weather-Savvy system by installing wireless routers in vehicles to bypass the in-cab tablets, which previously disrupted data transfers to NJDOT and NJIT servers due to shutdowns or locks. The new system is installed on three trucks, with plans to equip the remaining 42 trucks by December 2025.
How the Weather Savvy router system works
Truck Parking Pilot. Data collection continues at the Harding and Carney’s Point sites. Portable DMS signs recently installed on I-287 and I-78 now alert commercial vehicle drivers to available parking at the Harding site. The next phase involves installing data collection technology such as traffic microwave sensors and in-pavement micro radar sensors at the Knowlton Rest Area on I-80.
Streetlight. The team procured Streetlight Insight, a data platform that collects and analyzes data from connected and Internet of Things (Iot) devices to measure vehicles, transit, bike, and foot traffic nearly anywhere. NJDOT employers interested in using Streetlight data should contact the Mobility and Operations CIA team.
iNET ATMS. Launched on April 29, iNET ATMs is New Jersey’s first Advanced Traffic Management System, a browser-based interface to enter incidents, monitor traffic speeds, and view assets such as CCTVs and DMS signs statewide. NJDOT recently received the 2025 Excellence in Engineering Award at the NJ Alliance for Action. iNET will support the Central Dispatch Unit (CDU), the Safety Service Patrol (SSP) Team, and law enforcement.
Organizational Support & Improvement
Strategic Workforce Development. The initiative remains in the development stage. While FHWA confirmed funding approval, disbursement has been delayed due to funding pauses and other constraints. NJDOT is collaborating internally with its Division of Procurement and has partnered with NJDOL’s Workforce Development Services to advance training and apprenticeship preparation programs. In June 2025, NJDOT met with the Contractor Compliance Unit to discuss union engagement, apprenticeship programs, addressing the aging workforce, and strategies to increase membership.
Feature Presentation: Overcoming Challenges – Recruiting, Developing and Maintaining a Workforce to Meet Current and Future Highway Construction Needs
Vicki Tilghman-Ansley, Director of Civil Rights and Affirmative Action at NJDOT, delivered the meeting’s feature presentation, outlining current challenges in sustaining a highway construction workforce and describing strategies and initiatives to address them.
Several key laws have shaped Equal Employment Opportunity (EEO) and workforce development programs:
Title VII of the Civil Rights Act of 1964
Federal Aid Highway Act of 1968
Title IX of the Education Amendments of 1972
Federal Highway Administration regulations (23 CFR Part 230) of 1975
NJDOT’s Operations Apprentice Program
NJDOT administers an On-the-Job Training Program (OJT), based on the Federal Aid Highway Act of 1968, to develop a more competent and diverse workforce. Each federally funded project is evaluated to determine its training capacity, with larger, longer projects offering greater opportunities for meaningful training. While the program has made progress, barriers remain that limit its full potential.
The OJT Supportive Services Program complements OJT by preparing individuals for success in the highway construction workforce. It funds pre-apprenticeship training programs, assists contractors with recruitment and counseling, and supports mentorships and other ongoing resources. One major challenge has been securing union support to transition NJDOT trainees into the union apprenticeship programs, though recent union staffing shortages may open new opportunities.
Challenges NJDOT Faces
NJDOT’s workforce development programs face several challenges. New Jersey’s highway construction workforce is highly unionized, and several years into OJT, a union-led change required contractors to work through the unions for training. This shift ended NJDOT’s “off the street” recruitment strategy, which created greater opportunities for women and people of color. Highway construction unions remain predominately male and less diverse, with the laborers’ union being a notable exception. Additional difficulties include an aging workforce, gaps in training and skills, challenges with retention, and competition from other employers offering higher wages.
Strategies to Overcome Barriers
NJDOT’s Youth Corps Urban Gateway Enhancement Program
To overcome these barriers, NJDOT is strengthening partnerships and agreements with heavy highway construction contractors, unions, the NJ Department of Labor and Workforce Development, and the Utility & Transportation Contractors Association (UTCA). It is engaging alternative training providers, exploring opportunities with community colleges and trade schools, and building connections with community-based non-profits that serve women, minorities, and disadvantaged populations to provide job readiness and support services.
Using Information to Drive Solutions
Planned actions include developing feedback and reporting systems to track OJT outcomes, establishing dedicated funding to strengthen training program success, launching a website as a resource center for prospective workers, and hosting construction career days targeted to women, minorities, and others interested in NJDOT highway work.
Current NJDOT Partnerships:
Construction Industry Advancement Program of NJ
Associated General Contractors of NJ
NJ Youth Corps
Associations for Women in Construction
NJ’s One-Stop Career Centers
State Workforce Boards
Announcements and Reminders
Save the Date!
The 27th Annual NJDOT Research Showcase will be held on October 29, 8:30 AM – 3:00 PM, at Mercer County Community College, with a virtual option available. This year’s theme, “Preparing the Workforce for the Future,” ties into Vicki Tilghman-Ansley’s feature presentation.
Submit Your Research or Innovative Idea!
Share your innovative, research, or market-ready ideas using one of the forms available here.
Next Meeting
The NJ STIC 3rd Triannual Meeting is scheduled for December 10, 10:00 AM – 12:00 PM. The Mobility & Operations CIA Team will give the feature presentation.
A recording of the NJ STIC 2025 2nd Triannual Meeting is available here. The day’s presentations can be found here and in sections below.
Welcome Remarks & FHWA Updates
CIA Team Update: Safety
CIA Team Update: Planning & Environment
CIA Team Update: Infrastructure Preservation
CIA Team Update: Transportation Mobility
CIA Team Update: Organization Support & Improvement
Feature Presentation: Overcoming Challenges – Recruiting, Developing and Maintaining a Workforce to Meet Current and Future Highway Construction Needs
In summer 2025, the FHWA Every Day Counts (EDC)-7 Strategic Workforce Development (SWD) team hosted the Careers in Gear Summer Series—a webinar series highlighting innovative workforce development programs and success stories from across the country.
Featuring real-world examples and conversations with skilled trades professionals, program leaders, and other industry innovators, the series spotlighted practical strategies to strengthen the construction workforce—and help build the infrastructure of tomorrow.
Dates and Times
July 23 | 1:00-2:00 PM: Training Success Stories A webinar hosted by the Federal Highway Administration (FHWA) Every Day Counts-7 Strategic Workforce Development (SWD) team featuring short videos and real-world examples of training programs that are making a difference.
The speakers included:
Marguerite Givings (Wisconsin Department of Transportation)
Rich Granger (DriveOhio)
Liam Murphy (Teaching the Autism Community Trades)
Charlie McCullough (Indiana Constructors Inc)
Marjani Rollins (Caltrans)
Airton Kohls (University of Tennessee)
August 6 | 1:00-2:00 PM: Fireside Chat on Youth Development Programs A dynamic fireside chat exploring how youth development programs are building pathways into transportation and skilled trades careers, with insights from leaders driving innovative workforce initiatives across the country.
The speakers included:
Lisa Rose (Mineta Transportation Institute)
Rich Granger (DriveOhio)
Dr. Stephanie Ivey (University of Memphis Southeast Transportation Workforce Center)
The Federal Highway Administration’s National Highway Institute (NHI) offers a variety of web-based environmental training courses focused on air and noise pollution. These courses are designed to meet the needs of transportation professionals working in engineering, design, and project development/NEPA units within transportation agencies—primarily state DOTs. They may also be valuable for individuals involved in planning, asset management, operations, and maintenance.
Expected participants include experienced staff from state DOTs, local governments, Tribal governments, federal and state agencies, and consulting firms.
Air Quality Planning: Clean Air Act Overview (FHWA-NHI-142068, 1.5 hours, free) The purpose of this training is to provide participants with an overview of air quality planning, including requirements, processes, interactions with and implications for, transportation planning and project development.
Air Quality Planning: SIP and TCM Requirements and Policies (FHWA-NHI-142069, 1 hour, free) This course covers the different types of SIPs and key CAA SIP requirements general to all SIPs and specific to ozone, CO and PM SIPs; discusses how the EPA processes SIPs; explores the key features of EPA SIP policies and how they differ from CAA requirements; and explains RACM and how it applies to TCMs.
Air Quality Planning: SIP Development Process(FHWA-NHI-142070, 2 hours, free) This course provides an overview of the State Implementation Plan (or SIP) development process, focusing on agency roles, with an explanation of the problem definition and solution parts of the process. This course also covers motor vehicle emission budgets that are included in SIPs and used in conformity determinations, as well as describes EPAs procedures in approving and disapproving SIPs.
Air Quality Planning: Transportation Conformity (FHWA-NHI-142071, 1.5 hours, free) This course defines transportation conformity and is designed for individuals that are new to transportation conformity, with little to no experience with the Transportation Conformity Rule.
Acoustics of Highway Traffic and Construction Noise (FHWA-NHI-142086, 2 hours, free) The goal of this course series is to help learners understand the regulations, foundational scientific concepts, and processes associated with performing highway noise studies that lead to design and construction. The courses in this series provide an overview of highway traffic and construction noise based upon and focused on the FHWA’s 23 CFR 772.
Highway Traffic and Construction Noise Regulations (FHWA-NHI-142087, 2 hours, free) The modules in this course provide an overview of legislation, regulations, and policies that apply to highway traffic noise and include: Noise Legislation, Regulation, and Policy, 23 CFR 772, Project Types, Impacts and Land Use Categories, Feasibility, Reasonableness, Construction Noise.
How to Measure Highway Traffic Noise (FHWA-NHI-142088, 2 hours, free) The modules in this course focus on noise measurement and include: Basic Concepts and Resources, Field Instrumentation, Planning and Execution, Site Selection and Sampling Periods, Documentation, Multimodal Projects.
Abatement and Design Considerations for Highway Traffic Noise (FHWA-NHI-142089, 2 hours, free) The modules in this course focus on operational noise abatement including: Non-Barrier Abatement Methods, Barrier Methods – Noise Walls, Barrier Methods – Berms, Structure Mounted Noise Walls, Special Features for Walls, Wall Materials, Multimodal Projects.
An Introduction to the Traffic Noise Model (TNM) 3.0 (FHWA-NHI-142090, 3 hours, free) The modules in this course focus on TNM modeling and include: Overview of TNM, Noise Studies ─ Type I and Type II Projects, Use of Noise Analysis Areas, Inputs ─ Roadways, Inputs ─ Traffic, Inputs ─ Paths and Receivers, Non-Residential Receptor Analysis, Basic Barrier Design Considerations Outputs, Low Volume Road Noise Calculation Tool.
Public Involvement for Highway Traffic and Construction Noise Projects (FHWA-NHI-142091, 1 hour, free) The modules in this course focus on public involvement as it relates to noise projects including: Overview of Public Involvement Programs, Best Practices, Roles and Responsibilities, Tasks by Project Phases.
How to Mitigate Construction Noise (FHWA-NHI-142092, 1 hour, free) The modules in this course focus on construction noise including evaluation and abatement techniques.
We recently spoke with Vandana Mathur, Supervisor of Transportation Mobility & Research at NJDOT, to learn more about the agency’s ongoing innovative mobility and operations initiatives. The discussion navigated advancements such as enhanced IMR truck equipment for safer incident response, real-time weather monitoring through the Weather Savvy program, and smart truck parking technology to address parking space shortages. These efforts reflect NJDOT’s commitment to using data-driven, next-generation solutions to improve roadway safety and efficiency across the state.
Q. Can you tell us about the initiative to equip NJDOT Incident Management Response (IMR) trucks with lighting towers and LED flares at incident scenes as part of the EDC-7 Next-Generation TIM – Technology for Saving Lives?
A. NJDOT secured funding from the Federal Highway Administration (FHWA) to enhance its Incident Management Response (IMR) trucks by equipping them with light towers and LED flares. This initiative has already significantly improved NJDOT’s on-scene operational capabilities—particularly in low-light conditions—by increasing both safety and efficiency. The light towers provide critical illumination, enabling first responders to better assess the scene, identify debris, and evaluate the extent of the crash. The improved visibility also enhances personnel safety by alerting approaching drivers to the presence of an emergency scene, giving them time to slow down and avoid secondary incidents.
LED flare deployed at an incident site
Unlike traditional emergency lights, which can be blinding, the LED flares equipped on NJDOT’s IMR trucks use a calmer, sequential lighting pattern that is less jarring to drivers while still maintaining a strong visual presence. The light towers provide wide-area illumination that surpasses the limited reach of standard vehicle emergency lights, ensuring that all personnel working at the scene are clearly visible. Designed for quick deployment, the towers deliver lighting rapidly when it’s most needed.
This initiative plays a critical role in supporting Traffic Incident Management (TIM) by enhancing the safety for both emergency responders and drivers during roadway incidents.
Q. You mentioned the benefits of the lighting towers and LED flares compared to traditional flashing lights – are emergency responders moving away from using flashing lights altogether? Additionally, have they been installed and implemented into all NJDOT IMR trucks or is this an ongoing process?
A. Yes, we often use the new tools instead of the flashing lights, especially because they can be deployed immediately. We have installed the lighting towers and LED flares on 22 IMR trucks across the state. These tools are used frequently—on average, once per week or several times per month—which shows they’re a valuable and necessary source for incident management. Because they have proven so effective, it is now standard practice to include light towers and LED flares on all new IMR trucks added to the fleet.
Q. Staying on TIM, can you describe the Drivewyze alert project? How does it collect and distribute data, and what are some potential benefits?
A. Drivewyze is a product that we are purchasing through the University of Maryland as part of the Transportation Data Marketplace (TDM) and the Eastern Transportation Coalition, which benefits New Jersey and the 19 other coalition member states. Drivewyze sends safety alerts to commercial vehicles’ Electronic Logging Devices (ELDs)—which all truckers have—and since the alerts are free, both drivers and fleet operators can sign up to receive them.
The system generates alerts using INRIX data and provides warnings for low bridges, high rollover zones, weight restrictions, “no trucks in left lane” zones, and sudden slowdowns and congestion. Because commercial vehicles need more time to stop than passenger vehicles, due to their size and weight, timely slowdown warnings can be especially critical for safety.
Drivewyze dashboard displaying the number of alerts, the type of alerts, and where the alerts are located
As part of its service, Drivewyze provided us with a dashboard that show the number of alerts sent, categorized by alert type. We use this data to assess performance. For example, by reviewing the number of alerts issued over the past three months, we evaluate whether alerts are being sent to the right places at the right times. When I joined the NJDOT team, I emphasized the importance of verifying and validating this data—not just accepting numbers that look good on paper.
We reached out to NJIT, our resource center, to help us conduct real-world testing during peak hours to confirm whether the alerts were actually reaching vehicles on the road. Initially, NJIT found that static alerts were working well, but congestion alerts were not coming through. When I contacted Drivewyze, they responded that they had forgotten to enable congestion alerts and said they had fixed the issue. NJIT conducted follow-up test runs in April to confirm the fix.
In the second round of testing, static alerts continued to perform well—NJIT even received a new static message related to a closure of Exit 34 due to a sinkhole. However, congestion alerts still underperformed. Despite driving through 83 congestion zones at speeds under 25 mph, NJIT researchers only received 5 congestion alerts. We will continue working with Drivewyze to make sure this issue is fully resolved.
Q. Moving to a different topic, at the most recent NJ STIC meeting you mentioned recent advancements in the Weather Savvy pilot. What technologies are used in the Weather Savvy program, what benefits does it provide, and how has it evolved since it first began?
A. We launched the Weather Savvy pilot project in 2020 to gain real-time situational awareness of roadway conditions. We began by equipping 12 NJDOT vehicles with Vaisala MD30 weather sensors. These sensors collect a range of data such as air temperature, road surface temperature, grip levels, frost point, dew point, and whether the road surface is wet, icy, or dry. Each vehicle also contains tablets that display this information to the driver and relays it to a central server, administered by NJIT, via a wireless router installed in the vehicle. A road-facing camera mounted on the vehicle provides real-time video of roadway and weather conditions.
Screenshot of the Weather Savvy portal hosted by NJIT
Since the project began, we have expanded from 12 to 45 NJDOT vehicles, including plow trucks, Safety Service Patrol (SSP) trucks, and operations supervisor pickup trucks. All collected data is accessible through a web portal developed by NJIT, which features a map showing each vehicle’s location, online/offline status, and travel history over the past 15 minutes. The portal also includes color-coded indicators for road surface conditions and allows users to click on specific locations for detailed information.
Last year, NJIT enhanced the portal by integrating additional roadside sensors, including Vaisala GroundCast and acoustic sensors. GroundCast is a battery-operated, in-pavement cylindrical sensor that collects data on surface, ground, and base temperatures, as well as the presence of roadway chemicals. The acoustic sensors record the sound of vehicles driving over the road and use an AI model to classify the road surface conditions. All of this data has been integrated into the Weather Savvy web portal to support better live monitoring of road conditions.
NJDOT workers installing Vaisala GroundCast into the pavement
Right now, we are working toward integrating three sources of weather data: the mobile Weather Savvy vehicles, stationary road sensors across the state, and potential virtual Road Weather Information Systems (RWIS) data. Our goal is to merge all three sources to create the most accurate, real-time understanding of road and weather conditions. This phase is still in the early pilot stage.
Q. Is NJIT’s Weather Savvy web portal publicly accessible, or is it only shared with NJDOT?
A. Right now, the Weather Savvy web portal is internal-only, since it’s still a pilot project. We want to ensure that we have a solid, data-driven foundation before releasing any information to the public. That said, it has been really exciting to see how the data comes together. I have shared many images during STIC and other state meetings to give people a look at the portal. It is a very cool and innovative project. In fact, NJDOT, NJIT, and our technical partners from Vaisala and EAI won the 2021 “Outstanding Project Award” from the Intelligent Transportation Society of New Jersey (ITS-NJ) for Weather Savvy.
Q. During the previous STIC meeting, the Mobility and Operations team mentioned that you are testing direct streaming from sensors to servers on two of the Weather Savvy vehicles. Can you explain this initiative?
A. For the Weather Savvy project, one of the challenges we’ve faced is ensuring consistent data transmission from the trucks. Since drivers are inside the vehicles managing multiple devices—including laptops and tablets—there are times when the laptops shut off or something else interrupts the data flow. With a fleet of 45 trucks, keeping them all fully operational is a year-round task that keeps us constantly busy.
To address these issues, NJIT developed an API that allows the data to be sent directly to their server, bypassing the middle steps involving the tablet, laptop, and router. At first, they planned to roll this change out across the entire fleet, but I told them to start with a small test—just two trucks—to see how well the direct data transmission works. This change will also only apply to certain vehicles; for example, the IMR trucks will keep their tablets in place.
Q. Can you describe some of the technology used in the Truck Parking Pilot, what NJDOT has implemented so far, and some next steps for the future?
A portable traffic microwave sensor deployed at the entrance of a rest area
A. For the Truck Parking Pilot, we have deployed a range of technologies to better monitor and manage available spaces. First, we use in-pavement magneto-resistive sensors—referred to as “pucks”—manufactured by a company called Sensis Networks. These sensors detect whether a truck is occupying a particular space, and because truck parking spaces are so long, we have installed two pucks per space to ensure accurate detection. In addition to pucks, we installed traffic microwave sensors—one at the entrance and one at the exit of rest areas—to help us count the number of trucks entering and exiting each site. We also equipped the rest areas with CCTV cameras that provide live video feeds, supplementing the sensor data with visual information.
To transmit the collected data to NJIT servers, we use 4G and LTE modems, along with 4-port switches and Power over Ethernet devices. Each rest area has a dedicated equipment cabinet—installed by NJIT—that houses the pucks, cameras, and data transmission components.
We launched our first pilot site at the Harding rest area in 2021. That site features two microwave traffic sensors at the exit and entrance, nine CCTV cameras, and 44 pucks. In 2023, we expanded to the Deepwater rest area (also known as Carney’s Point), where we installed two traffic microwave sensors, one CCTV camera, and 68 pucks. All of this data feeds into a truck parking portal dashboard developed by NJIT to provide real-time insights. The dashboard displays the number of vehicles entering and exiting each site, average dwell time for trucks, the number of vehicles currently parked, and the occupancy status of individual parking spaces. It also tracks how long each spot has been occupied and provides historical usage statistics, including peak usage times.
The Truck Parking Pilot dashboard at Carney’s Point displaying the occupied parking spaces
A virtual video wall offers live views of each rest area and shows how many trucks are currently parked and how many spaces remain available, based on the combined data sources. This is particularly valuable because truck parking demand is so high in New Jersey that drivers often end up parking at entrances, along curbs, or even perpendicular to marked spaces—creating unsafe conditions and occasionally blocking cameras.
To help address this, we have been working with NJIT to install two portable Dynamic Message Signs (DMS) near the Harding pilot site, located within five miles of the rest area on I-287 and I-78. These signs will display real-time parking availability.
More recently, we started the process of expanding the project to the Knowlton rest area. My team and I, along with NJIT, recently visited the site to begin the process of installing the necessary technologies.
Q. Are there any other projects or innovations that your or your team are working on that you would like to highlight?
A. Right now, we are focusing on expanding the existing projects we already have in place. In addition, we have started exploring virtual RWIS technology, which is still very new to us. It is currently in the early stages of development, so nothing has been substantiated yet.
Video Recording: 2025 Research Showcase Lunchtime Edition
On May 14, 2025, the NJDOT Bureau of Research, Innovation, and Information Transfer hosted a Lunchtime Tech Talk! webinar, “Research Showcase: Lunchtime Edition 2025”, featuring four presentations on salient research studies. As these studies were not shared at the 26th Annual Research Showcase held in October 2024, the webinar provided an additional opportunity for the over 80 attendees from the New Jersey transportation community to explore the wide range of academic research initiatives underway across the state.
The four research studies covered innovative transportations solutions in topics ranging from LiDAR detection to artificial intelligence. The presenters, in turn, shared their research on assessing the accuracy of LiDAR for traffic data collection in various weather conditions; traffic crash severity prediction using synthesized crash description narratives and large language models (LLMs); non-destructive testing (NDT) methods for bridge deck forensic assessment; and traffic signal detection and recognition using computer vision and roadside cameras. After each presentation, webinar participants had an opportunity to ask questions to the presenters.
Presentation #1 –Assessing the Accuracy of LiDAR for Traffic Data Collection in Various Weather Conditions by Abolfazl Afshari, New Jersey Institute of Technology (NJIT)
Mr. Afshari shared insights from a joint research project between NJIT, NJDOT, and the Intelligent Transportation Systems Resource Center (ITSRC), which evaluated the accuracy of LiDAR in adverse weather conditions.
LiDAR (Light Detection and Ranging) is a sensing technology that uses laser pulses to generate detailed 3D maps of the surrounding area by measuring how long it takes for laser pulses to return after hitting an object. It offers high resolution and accurate detection, regardless of lighting, making it ideal for traffic monitoring in real-time.
The research study began in response to growing concerns about LiDAR’s effectiveness in varied weather conditions, such as rain, amid its increasing use in intelligent transportation systems. Mr. Afshari stated that the objective of the research was to evaluate and quantify LiDAR performance across multiple weather scenarios and for different object types—including cars, trucks, pedestrians, and bicycles—in order to identify areas for improvement.
To conduct the research, the team installed a Velodyne Ultra Puck VLP-32C LiDAR sensor with a 360° view on the Warren St intersection near the NJIT campus in Newark. Mr. Afshari noted that newer types of LiDAR sensors with enhanced capabilities may be able to outperform the Velodyne Ultra Puck during adverse weather. They also installed a camera at the intersection to verify the LiDAR results with visual evidence. The research team used data collected from May 12 to May 27, 2024.
The researchers obtained the weather data from Newark Liberty Airport station and utilized the Latin Hypercube Sampling (LHS) method to identify statistically diverse weather periods for evaluation and maintain a balance between clear and rainy days. They selected over 300 minutes of detection for the study.
The study area for the LiDAR detection evaluation
To evaluate how well the detection system performed under different traffic patterns, they divided the study area into two sections. The researchers used an algorithm for the LiDAR to automatically count the vehicles and pedestrians entering these two areas, then validated the LiDAR results by conducting a manual review of the video captured from the camera.
The research team found that, overall, the LiDAR performed well, though there were some deviations during rainy conditions. During rainy days, the LiDAR’s detection rate decreased for both cars and pedestrians, with the greatest challenges occurring in accurately detecting pedestrians. On average, the LiDAR would miss nearly .8 pedestrians and .7 cars per hour during rainy days, around 30 percent higher than on clear days.
Key limitations of the LiDAR detection identified by the researchers include: maintaining consistent detection of pedestrians carrying umbrellas or other large concealing objects, identifying individuals walking in large groups, and missing high-speed vehicles.
Mr. Afshari concluded that LiDAR performs reliably for vehicle detection but pedestrian detection needs enhancement in poor weather conditions, which would require updated calibration or enhancements to the detection algorithm. He also stated the need for future testing of LiDAR on other weather conditions such as fog or snow to further validate the findings.
Q. Do you think the improvements for LiDAR detection will need to be technological enhancements or just algorithmic recalibration?
A. There are newer LiDAR sensors available, which perform better in most situations, but the main component to LiDAR detection is the algorithm used to automatically detect objects. So, the algorithmic calibration is the most important aspect for our purposes.
Q. What are the costs of using the LiDAR detector?
A. I am not fully sure as I was not responsible for purchasing the unit.
Presentation #2 – Traffic Crash Severity Prediction Using Synthesized Crash Description Narratives and Large Language Models (LLM) by Mohammadjavad Bazdar, New Jersey Institute of Technology
Mr. Bazdar presented research from an NJIT and ITSCRC team effort focused on predicting traffic crash severity using crash description narratives synthesized by a Large Language Model (LLM). Predicting crash severity provides opportunities to identify factors that contribute to severe crashes—insights that can support better infrastructure planning, quicker emergency response, and more effective autonomous vehicle (AV) behavior modeling.
Previous studies have relied on traditional methods such as logit models, classification techniques, and machine learning algorithms like Decision Tree and Random Forests. However, Mr. Bazdar notes that these approaches struggle due to limitations in the data. Crash report data often contains numerous inconsistencies and missing values for varying attributes, making it unsuitable for traditional classification models. Even if you get a good result from the model, it cannot be used to reliably identify contributing factors because of all the data that is excluded.
To address this challenge, the research team explored the effectiveness of generating consistent and informative crash descriptions by converting structured parameters into synthetic narratives, then leveraging large language models (LLMs) to analyze and predict crash severity based on these narratives. Since LLMs can parse through different terminologies and missing attributes, it allows researchers to analyze all available data, and not the minority of crash data that has no inconsistencies or missing variables.
The research team used BERT, an Encoder Model LLM, to analyze over 3 million crash records from January 2010 to November 2022 for this study. Although crash reports often contain additional details, the team exclusively utilized information regarding crash time, date, geographic location, and environmental conditions. Additionally, they divided crash severity into three categories: “No Injury,” “Injury,” and “Fatal.”
The narratives synthesized by BERT include six sentences, with each sentence describing different features of the crash, such as time and date, speed and annual average daily traffic (AADT), and weather conditions and infrastructure. BERT then tokenizes and encodes the narrative to generate contextualized representations for crash severity prediction.
They also found that a hybrid approach—using BERT to tokenize crash narratives and generate crash probability scores, followed by a classification model like Random Forest to predict crash severity based on those scores—performed best. An added benefit of the hybrid model is that it produces comparable, if not better, results than the BERT model, in hours rather than days.
In the future, Mr. Bazdar and the research team plan to enhance their model by integrating spatial imagery, incorporating land use and environmental data, and utilizing decoder-based language models, hoping to achieve more effective results.
Q. How does your language model handle missing data fields?
A. The model skips missing information completely. For example, if there is a missing value for the light condition, the narrative will not mention anything about it. In traditional models, a report missing even one variable would have to be discarded. However, with the LLM approach, the report can still be used, as it may contain valuable information despite the missing data.
Q. What percentage of the traffic reports were missing data?
A. The problem is that while a single value like light condition, may be missing in only a small percentage of crash reports, a large portion—nearly half—of crash reports have some missing data or inconsistency.
Presentation #3 – Forensic Investigation of Bridge Backwall Structure Using Ultrasonic and GPR Techniques by Manuel Celaya, PhD, PE, Advance Infrastructure Design, Inc.
Dr. Celaya described his work performing non-destructive testing (NDT) on the backwall structure of a New Jersey bridge, utilizing Ultrasonic Testing (UT) and Ground Penetrating Radar (GPR).
The bridge in the study, located near Exit 21A on I-287, was scheduled for construction; however, NJDOT had limited information about its retaining walls. To address this, NJDOT enlisted Dr. Celaya and his firm, Advanced Infrastructure Design, Inc. (AID), to assess the wall reinforcements—mapping the rebar layout, measuring concrete cover, and detecting potential cracks and voids in the backwalls.
The team used a hand-held GPR system to identify the presence, location, and distribution of reinforcement within the abutment wall. The GPR device collects the data in a vertical and horizontal direction, indicating the distance of reinforcement like rebar and its depth of penetration. This information was needed to ensure that construction on the bridge above would not impact the abutment walls.
SAFT images of the bridge abutment produce by the Ultrasonic Testing
They also employed Ultrasonic Testing (UT), a method that uses multiple sensors to transmit and receive ultrasonic waves, allowing the team to map and reconstruct subsurface elements of the bridge wall. The system captures a detailed cross-sectional view of acoustic interfaces within the concrete using a grid-based measurement pattern, ensuring precise and reliable data collection. Additionally, they used IntroView to evaluate the UT data and produce Synthetic Aperture Focusing Technique (SAFT) images to illustrate and identify anomalies within the concrete.
AID also conducted NDT to assess the depth of embedded bolts in the I-287 bridge abutments using GPR scans, but aside from detecting steel rebar reinforcements, no clear signs of the bolts were found. However, the UT results offered valuable insights, revealing that the embedded bolts in the west abutment wall were deeper than those in the east abutment.
Q. What was the process workflow like for the Ultrasonic Testing?
A. It is not that intuitive compared to Ground Penetrating Radar. With GPR, you can clearly identify structures on the site. However, with UT, there has to be post-processing analysis in the office, it cannot be attained in the field. This analysis takes time and requires a certain level of expertise.
Presentation #4 – Traffic Signal Phase and Timing Detection from Roadside CCTV Traffic Videos Based on Deep Learning Computer Vision Methods by Bowen Geng, Rutgers Center for Advanced Infrastructure and Transportation
Mr. Geng shared insights from an ongoing Rutgers research project that evaluates traffic signal phase and timing detection using roadside CCTV traffic video footage, applying deep learning and computer vision techniques. Traffic signal information is essential for both road users and traffic management centers. Vehicle-based signal data supports autonomous vehicles and advanced Traffic Sign Recognition (TSR) systems, while roadside-based data aids Automated Traffic Signal Performance Measures (ATSPM) systems, Intelligent Transportation Systems (ITS), and connected vehicle messaging systems.
While autonomous vehicles can perceive traffic signals using on-board camera sensors, roadside detection relies entirely on existing infrastructure such as CCTV traffic footage. Mr. Geng noted that advancements in computer vision modeling provides a resource-efficient tool for improving roadside traffic signal data collection, compared to other potential solutions like infrastructure upgrades, which would be costly. For the study, the researchers decided to develop and implement methodologies for traffic signal recognition using CCTV cameras, and evaluate the effectiveness of different computer vision models.
Most previous studies have concentrated heavily on vehicle-based traffic signal recognition, while roadside-based TSR has received relatively limited attention, with some previous studies using vehicle trajectory to determine traffic signal status. Furthermore, early research relied on traditional image processing techniques such as color segmentation, but more recent studies have shifted toward a two-step pipeline using machine learning tools like You Only Look Once (YOLO) or deep learning-based end-to-end detection methods. Both the two-step pipeline and end-to-end detection approaches have their advantages and drawbacks. The two-step pipeline uses separate models for detection and classification, requiring coordination between stages and creating slower process speeds, but making it easy to debug. In contrast, end-to-end detection is faster and more streamlined but more difficult to debug.
Real-time traffic signal detection using the research model
In this study, the researchers adopted three different methodologies; two using the two-step pipeline, and one using an end-to-end detection model. All three models employed YOLOv8 for object detection; however, they differed in color classification methods. The researchers used video data from the DataCity Smart Mobility Testing Ground in downtown New Brunswick, across five signalized intersections.
The model achieved an overall accuracy of 84.7 percent, with certain signal colors detected more accurately than others. Mr. Geng shared that the research team was satisfied with these results. They see potential for the model to be used to support real-time traffic signal data logging and transmission for ATSPM and connected vehicle messaging system applications.
Q. How many cameras did you have at each intersection?
A. For each intersection we had two cameras facing two different directions. For some intersections, we had one camera facing north and another facing south, or one facing east and the other facing west.
Q. What did you attribute to the differences in color recognition?
A. There was some computing resource issue. Since we are trying to implement this in real-time, there are difficulties balancing accuracy with possible latency issues and processing time.
The NJ State Transportation Innovation Council (NJ STIC) convened virtually for its first Triannual Meeting of 2025 on April 30. The meeting provided an opportunity for attendees to learn from the Core Innovation Area (CIA) Teams about their progress on the Every Day Counts Round 7 (EDC-7) initiatives and to view a featured presentation on High Performance Internally Cured Concrete (HPIC) from NJDOT’s Samer Rabie and Jess Mendenhall.
Welcome Remarks
Eric Powers, Assistant Commissioner of NJDOT Statewide Planning, Safety, and Capital Investment, welcomed attendees. Mr. Powers offered his gratitude to the NJ STIC community, emphasizing that the strength of STIC lies in the creativity and impact of its members. He concluded his remarks by stressing the meaningful contributions that CIA teams make in New Jersey, and officially opened the session.
FHWA Updates
Christopher Paige, Innovation Coordinator and Community Planner at the FHWA NJ Division Office, shared several key updates. He reminded attendees that final EDC-7 progress reports and STIC Incentive project reports should be directly submitted to him by May 9, 2025. Mr. Paige also announced that he will temporarily serve as the FHWA Co-Lead for the Infrastructure Preservation CIA team in collaboration with Shivani Patel, as well as on the Planning & Environment team with Simon Nwachukwu. Looking ahead, he stated that the FY25 STIC Incentive Funding Request applications are due by July 1, 2025, but encouraged early submissions. Applicants should include a project summary, schedule, and budget, and submit the application to Christopher Paige and NJDOT Innovation Officer Giri Venkiteela. Those interested in learning more about the application process for STIC funding should visit the STIC Incentive Funding Grant page on the NJDOT Tech Transfer website.
Mentimeter Engagement Activity
After the FHWA Updates, Giri Venkiteela, Innovation Officer at the NJDOT Bureau of Research, Innovation, and Information Transfer (BRIIT), hosted a Mentimeter Engagement Activity to learn the makeup of attendees, gauge their involvement with advancing innovation, and gather feedback on their current EDC initiatives. Questions included:
Which agency type do you represent?
What comes to mind when you think of innovation?
Is your organization or unit implementing or planning to implement any of the EDC-7 innovations?
What challenges are you facing in implementing innovations?
At the end of the survey, Mr. Venkiteela encouraged attendees to contact BRIIT staff if they had an innovation or research idea that they would like to propose to NJDOT.
Core Innovation Areas (CIA) Updates
The Core Innovation Area (CIA) Team leaders shared updates on progress toward achieving deployment goals for their respective innovation initiatives. CIA Team leaders from the NJDOT and FHWA discussed EDC-7 initiatives under the five CIA Teams: Safety, Planning and Environment, Infrastructure Preservation, Mobility and Operations, and Organizational Support and Improvement. Each team presented detailed reviews of their ongoing projects and outlined implementation activities, accomplishments, and challenges experienced in meeting the innovation’s deployment goals. A brief overview of team updates is included below:
Safety
Backplate with retroreflective tape on traffic signal indications
Pedestrian Scale Lighting Research and Resource. Researchers at the Alan M. Voorhees Transportation Center at Rutgers University and Rowan University continue to finalize a resource on best practices for pedestrian scale lighting. The Safety Team stated that the guide, designed for county and local governments, still needs additional edits and review from NJDOT SMEs before it can be released as a final deliverable. Additionally, in January, FHWA delivered an in-depth, two-day lighting workshop in Bordentown to an audience of NJDOT, MPO, and municipality staff. Workshop topics included visibility, human factors, safety, cost-benefit analysis,
Nighttime Visibility for Safety. The Safety Team reported progress on developing traffic signal pole and mast arm details for signalized intersection installations based on 2015 AASHTO LRFD requirements. The Division of Traffic Engineering continues to install backplates with retroreflective tape on existing signal indications where feasible, and the design consultant for the initiative is coordinating with fabricators on manufacturing options.
Planning and Environment
Congestion Mitigation and Air Quality Improvement Program (CMAQ). NJDOT is actively approving new projects based on their alignment with CMAQ goals and federal air quality targets; the process includes a cost-effectiveness analysis, where projects must demonstrate potential to reduce congestion, mitigate environmental impacts, and advance the adoption of low emission technologies. Project types include: public transit expansion, intersection modernization, intelligent transportation systems, and low-emission vehicle incentives.
Carbon Reduction Program(CRP). The Planning and Environment Team also announced that the CRP has transitioned from the planning stage to full-scale implementation. Key strategic advancements made by NJDOT include the deployment of battery-electric buses, the development of Complete Streets initiatives, and partnerships with municipalities for the transition to green fleets. NJDOT evaluates the effectiveness of CRP projects using performance indicators like reductions in CO2, increased transit ridership, and improved air quality. The next steps for NJDOT are to accelerate CRP-backed projects, integrate AI-based traffic management systems to optimize traffic flow, and continue collaboration with MPOs, industry leaders, and research institutions.
Infrastructure Preservation
The twin bridges that will be studied to compare performance between HPC and HPIC
Enhancing Performance with Internally Cured Concrete (EPIC2). The Infrastructure Preservation Team has made progress on several initiatives to advance the EPIC2 program since the last STIC meeting. NJDOT’s Division of Procurement has posted the Request for Proposal (RFP) for a centrifuge apparatus and is currently awaiting bids. Verification testing for the High-Performance Internally Cured Concrete (HPIC) mix is underway on the program’s first pilot bridge in East Orange. In addition, six more pilot projects are in the final design stage, including a twin bridge pilot where one structure will use a traditional concrete mix as a control, while the other will incorporate the HPIC mix. Looking ahead, the team plans to complete a Final Design Submission for candidate bridges, begin scoping additional projects, and purchase the centrifuge apparatuses. Plans are also underway to host an EPIC2 workshop and a webinar, with dates to be determined.
Mobility and Operations
Weather Savvy. The Weather Savvy pilot has expanded from 24 to 45 vehicles since December 2023, with 44 currently active. The team has prioritized installations in plow trucks to allow for data collection during winter weather events. Hardware is now housed in a sealed junction box with a Plexiglas lid to prevent tampering and environmental damage. The team is also testing a new configuration that would enable data to stream directly from sensors to servers, improving the system’s efficiency.
An example of a Portable DMS, which will be installed near the Harding rest area.
Truck Parking Pilot. The Harding and Kearny Point locations continue to collect real-time truck parking data using cameras, remote traffic microwave sensors, and in-pavement micro radar sensors. The Mobility and Operations Team will soon install a portable dynamic message sign (DMS) five miles from the Harding rest area to inform drivers of available spaces. Additionally, NJDOT plans a third truck parking pilot site in Knowlton; the Mobility and Operations Team visited the Knowlton site on May 1.
Drivewyze Alerts. The Mobility and Operations Team also provided an update on the Drivewyze alert pilot. During the first round of testing in 2024, NJIT researchers received accurate static alerts, but no congestion alerts, prompting NJDOT and NJIT to conduct a second round of testing in April to verify the accuracy of the real-time congestion and slowdown alerts provided to drivers. The team awaits results for this phase of testing.
Vaisila GroundCast. NJDOT has installed Vaisala GroundCast, a wireless in-ground sensor system that provides long-term environmental data, at three locations (on NJ-29 and NJ-12) to measure road temperature and the amount of residual treatment material. The team is in the process of finalizing an additional location for installation.
Organizational Support and Improvement
Contractor Compliance Unit Collaboration. NJDOT continues to explore internal and external funding opportunities, including potential partnerships with the New Jersey Department of Labor and Workforce Development (NJDOL). NJDOL programs offer customizable transportation-related training and counseling services that could support NJDOT workforce needs. In March 2025, NJDOT met with the Contractor Compliance Unit to discuss union engagement, apprenticeship programs, strategies to address the aging workforce, and methods to increase membership. Upcoming outreach activities include an open house for individuals interested in working with NJDOT, and a contractor industry meeting scheduled for May 9.
Feature Presentation: High Performance Internally Cured Concrete (HPIC)
Samer Rabie and Jess Mendenhall, co-leads of the SME teams for both the EPIC2 EDC-7 initiative and the UHPC for Bridge Preservation and Repair EDC-6 initiative, delivered a comprehensive feature presentation explaining the principles of HPIC, demonstrating its significance for New Jersey, and highlighting NJDOT’s ongoing efforts to implement the use of this material.
Example of cracking on an HPC bridge deck
Under current specifications, NJDOT utilizes high performance concrete (HPC) and ultra-high performance concrete (UHPC) for bridge decks. Both HPC and UHPC contain a low water-cement ratio and large amounts of supplementary cementitious materials (SCMs), which enhances durability but also increases the risk of shrinkage cracking. This early-age cracking undermines the improved durability and requires frequent and costly sealing.
FHWA launched the EPIC2 EDC-7 initiative in response to decades of research showing that HPIC effectively targets and mitigates shrinkage cracking in HPC and UHPC, resulting in low-permeability concrete with enhanced durability. HPIC employs internal curing, in which water is supplied from within the concrete using pre-wetted lightweight fine aggregate (LWFA). The absorbed water remains in the LWFA during mixing and until the concrete sets, leading to improved water distribution throughout the concrete and reducing the risk of cracking.
To date, internal curing has been implemented and institutionalized by more than 15 states and transportation agencies, and used in over 150 bridge decks. New York Department of Transportation (NYSDOT), an early adopter of HPIC, has mandated internal curing for all continuous bridges and bridges in New York City, reporting no additional cost compared to using conventional HPC or UHPC alone. In May 2024, Samer Rabie and Jess Mendenhall attended a New York State Peer Exchange for the EPIC2 initiative held in Albany, NY.
States that have deployed and implemented HPIC
NJDOT’s implementation plan for HPIC has involved a long process of researching, drafting specifications, evaluating risk, coordinating internally, obtaining buy-In from manufacturers, launching pilots, and training staff. As part of this effort, NJDOT secured a $125,000 STIC Incentive Grant to support HPIC implementation. The funding will fund the purchase of testing equipment, staff training on the new equipment, and third-party lab assistance for concrete sampling and testing during construction. Additionally, the NJDOT BRIIT awarded Rutgers RIME a project focused on internal curing. Mr. Rabie stated the Infrastructure Preservation team plans to foster close collaboration with the Rutgers researchers going forward.
NJDOT will source LWFA from suppliers located in North Carolina and New York, with the material pre-soaked at the concrete facilities using sprinklers, then allowed to drain to achieve uniform moisture content. LWFA moisture testing is currently performed using the paper towel method, an accessible but less precise technique. A more accurate alternative, the centrifuge method, requires specialized equipment. To enhance testing reliability, NJDOT will use STIC Incentive Grant funding to procure centrifuge equipment. Once implemented, the centrifuge method is expected to supplement the paper towel test in future guide specifications.
Implementing HPIC will follow similar procedures as HPC and UHPC, including consistent placement, finishing methods, and external curing durations. However, the pilot projects for HPIC will initially require additional expenses to verify new mix designs and conduct trial batches and test slabs, and thus may face higher unit prices for concrete production. NJDOT expects these raised unit costs to decline once HPIC becomes standardized, as seen in New York following NYSDOT’s standardization.
The first pilot project – North Munn Avenue over I-280 in East Orange – has completed the mix design, verification batching, and most verification testing. The next milestone is the trial batch and test slab, which must be completed before bridge deck construction begins. Early challenges for implementation include high upfront costs, limited supplier buy-in due to restrictive specifications, scale-related inefficiencies, and a general lack of awareness among industry stakeholders.
To address these challenges and support broader implementation, NJDOT plans to conduct concrete supplier outreach and HPIC workshops in summer 2025, followed by centrifuge training in the fall. The Department will also evaluate pilot project performance, identify lessons learned, and refine specifications for future projects.
If you are interested in learning more about HPIC and EPIC2, read the NJDOT Tech Transfer Q&A article with Samer Rabie and Jess Mendenhall.
Announcements and Reminders
EDC Progress Reports. Dr. Venkiteela reminded CIA teams to submit their final EDC progress reports to Christopher Paige by May 9.
Research or Innovative Ideas. Dr. Venkiteela encouraged attendees to submit innovative or research ideas to BRIIT’s Manager Pragna Shah at pragna.shah@dot.nj.gov
Next Meeting. The NJ STIC 2025 2nd Triannual Meeting is scheduled for Wednesday, August 6 from 10:00 AM to 12:00 PM. The Organizational Support and Improvement CIA Team will deliver the feature presentation.
A recording of the NJ STIC 2025 1st Triannual Meeting meeting is available here. The day’s presentations can be found here, as well as, in the sections, below.
Welcome Remarks & FHWA Updates
CIA Team Update: Safety
CIA Team Update: Infrastructure Preservation
CIA Team Update: Organizational Support & Improvement
