RPUG 2023 Speaker’s Bios and Abstracts

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  • Session 0.1: TPF-5(399) Distresses Pooled Fund Meeting by Andy Mergenmeier, FHWA
    Bio:
    Andy Mergenmeier is a Senior Pavement and Materials Engineer with the FHWA. His primary responsibilities include pavement surface characteristics measurement and analysis, construction materials acceptance, and pavement construction. He is the FHWA liaison to the American Association of State Highway and Transportation Officials (AASHTO) Committee on Materials and Pavements Technical Section responsible for management of pavement measurement standards including pavement profiling, friction, rutting and cracking. He is managing the pooled fund study, TPF-5(299)/(399), Improving the Quality of Pavement Surface Distress and Transverse Profile Data Collection and Analysis, which he will be discussing this morning. Andy is the Field Project Engineer for the FHWA Friction Management Program project that includes demonstrating continuous friction measurement technologies within the framework of a friction management program. He came to this position in 2007 after 7 years as the state of Virginia’s Department of Transportation’s (VDOT) State Materials Engineer. At VDOT he was responsible for overseeing preliminary engineering and construction functions, such as, pavement design and construction materials acceptance and testing programs. Before VDOT, Mr. Mergenmeier worked for the FHWA for 15 years in various locations throughout the US.

    Mr. Mergenmeier is a Civil Engineering graduate from the University of Kansas, and a Registered Professional Engineer.
    Abstract:
    Improving the Quality of Pavement Surface Distress and Transverse Profile Data Collection and Analysis – Pooled Fund Meeting. This meeting is for its members and all others interested in this subject.

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  • Session 0.2: TPF-5(399) and TPF-5(354) Joint Meeting by Andy Mergenmeier and Dave Huft, FHWA and SDDOT and George K. Chang
    Bio:
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    Abstract:
    The joint meeting will start with a TPF-5(399), TPF-5(354), and ProVAL presentations that lead to the over-arching topics that involve both TPFs. The discussion will include the future direction of the TPF, potential merged TPF and its associated goals and ProVAL support.
  • Session 0.3: Ice-breaker Event by NA, NA
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  • Session 1.0: Session moderator by Steve Hale, NVDOT
    Bio:
    Steve Hale has worked for the Nevada Department of Transportation for 24 years, with the last 2 years serving as the Assistant Construction Engineer. Steve is the 2023 Chair of the RPUG steering committee and has attended 13, including this year’s, RPUG conferences over his career. Steve graduated from the University of Nevada, Reno, in 1998 with a bachelor’s degree in Civil Engineering and is a registered Professional Engineer in the State of Nevada. Steve is the father of three; Baylee (Age 21), Michael (Age 20), and Natalie (Age 16). He has also been in a relationship with the love of his life, Tanya, for the last 9 years. Steve is a native Nevadan and enjoys all that Nevada has to offer. His hobbies include walking/jogging, going to the movies, and traveling.
    Abstract:
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  • Session 1.1: Welcome by Steve Hale, NVDOT
    Bio:
    Steve Hale has worked for the Nevada Department of Transportation for 24 years, with the last 2 years serving as the Assistant Construction Engineer. Steve is the 2023 Chair of the RPUG steering committee and has attended 13, including this year’s, RPUG conferences over his career. Steve graduated from the University of Nevada, Reno, in 1998 with a bachelor’s degree in Civil Engineering and is a registered Professional Engineer in the State of Nevada. Steve is the father of three; Baylee (Age 21), Michael (Age 20), and Natalie (Age 16). He has also been in a relationship with the love of his life, Tanya, for the last 9 years. Steve is a native Nevadan and enjoys all that Nevada has to offer. His hobbies include walking/jogging, going to the movies, and traveling.
    Abstract:
    NA

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  • Session 1.2: Keynotes by Jon-Paul Kohler, Planning & Program Development Manager,
    FHWA – Illinois Division
    Bio:
    Jon-Paul Kohler is with the Federal Highway Administration’s Illinois Division in Springfield. He has been with FHWA for nearly 40 years and has served as the Illinois Division’s Planning & Program Development Manager since 2000. In this position, he oversees a nine-member staff who deliver the following federal-aid highway programs: Planning, Air Quality, Freight, Environment, Right-of-Way, Asset Management and Transportation Performance Management, Pavement and Materials, Highway Safety, and Mobility. Jon-Paul received his bachelor’s degree in Civil Engineering in 1987 from Missouri University of Science & Technology.
    Abstract:
    NA

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  • Session 1.3: Keynotes by Justan Mann, Deputy Director of the Office of Highway Project Implementation for Illinois DOT
    Bio:
    Justan Mann has over 30 years of experience working in the transportation industry. Justan began his career in this industry, working for a heavy highway construction company.
    Justan has a Master of Science in Civil Engineering from Southern Illinois University at Carbondale and is a licensed professional and structural engineer in the State of Illinois.
    Justan joined the Illinois Department of Transportation in January 1998 in the Bureau of Bridges and Structures. Since that time, Justan has held various positions within the department and is currently serving as a Deputy Director in the Office of Highways Project Implementation.
    Abstract:
    NA

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  • Session 1.4: Vendors’ oral introduction by All vendors,
    Bio:
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    Abstract:
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  • Session 1.5: Session Break by NA, NA
    Bio:
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  • Session 2.0: Session moderator by Dave Huft, SDDOT
    Bio:

    Abstract:
    NA

  • Session 2.1: TPF-5(354) Pooled Fund Updates by Dave Huft, SDDOT
    Bio:

    Abstract:
    TPF-5(354) Pooled Fund Updates

  • Session 2.2: Real-Time Smoothness (RTS) Updates by David K. Merritt, Transtec Group and George K. Chang
    Bio:
    David Merritt is a Project Director with The Transtec Group and has nearly 23 years of pavement engineering and testing experience. He currently manages The Transtec Group, Inc.’s Pavement Characteristics (PSC) program, overseeing engineering and testing efforts related to pavement smoothness, texture, friction, tire-pavement noise, and roadway safety. He has a Bachelor’s degree in Civil Engineering from Northern Arizona University and Master’s degree from The University of Texas at Austin, and is a registered Professional Engineer in Kanas, Minnesota, Missouri, and Texas.
    Abstract:
    Real-Time Smoothness (RTS) technology is a paving quality control (QC) tool to improve the as-constructed smoothness of concrete and asphalt pavements. RTS technology measures the profile of a concrete slab or asphalt mat behind the paver, providing real-time feedback on smoothness during paving. This gives contractors a real-time assessment of pavement smoothness rather than waiting until the finished pavement is profiled. RTS provides the real-time impact of the paving processes (changes in mix design, paving operations, etc.) on smoothness, such that adjustments can be made in time as well as corrective actions. In 2014, FHWA initiated an RTS equipment loan program as part of the implementation of SHRP2 technologies. This equipment loan program, which has continued under the FHWA-CP Tech Center Cooperative Agreement, has provided tremendous insight into the benefits, limitations, and overall usefulness of RTS technology for concrete paving. In 2020, a proof-of-concept of asphalt real-time smoothness (ARTS) was sponsored by the National Road Research Association (NRRA) pooled fund study. Though with a limited device under the NRRA ARTS project, the benefits of RTS technology for improving asphalt smoothness were apparent through two field demonstration projects. This presentation summarizes the lessons learned from the FHWA RTS program and NRRA ARTS project to provide the updated road map for future RTS development and applications.
  • Session 2.3: Revisions to AASHTO Standards to Address Road Profile Measurement on Urban and Low-Speed Roadways by John Senger, ILDOT and Steve Karamihas
    Bio:
    John Senger received a Bachelor of Science in civil engineering from Bradley University. John has been at the Illinois Department of Transportation for 8 years and is currently the Engineer of Pavement Technology. Prior to joining IDOT, John worked as a consultant engineer, where he was involved in a wide variety of projects. John is responsible for Illinois DOT’s ride quality specifications, and friction program and manages ICART. John is currently serving as the chair of the Pavement Surface Properties Consortium and as the vice chair of the RPUG steering committee.
    Abstract:
    Recent changes to the National Highway System have raised the importance of valid profile measurement on urban and low-speed roads; and recent advancements in technology have been developed to meet this need. AASHTO R56 defines standard methods for certification of inertial profilers, but it does not address urban and low-speed operation. In particular, it does not include test conditions designed to assess profiler performance for conditions that occur on urban and low-speed roads, such as travel at very low speed, during braking, or in stop-and-go operation. NCHRP project 10-93 examined test methods for these conditions, and suggested revisions to AASHTO standards to help ensure accurate and repeatable measurement of profile on urban and low-speed roadways in NCHRP Report 914. A small group from Pooled Fund Study TPF-5(354) has incorporated and refined the revisions to AASHTO R56, R57, and M328 proposed in NCHRP Report 914. This presentation presents the proposed revisions, and highlights the technical basis for the methodology.
  • Session 2.4: Relationship Between IRI and Vehicle Dynamic Response to Road Roughness by Steve Karamihas, UMTRI
    Bio:
    Steve Karamihas is a Research Area Specialist Senior at the University of Michigan Transportation Research Institute.
    Abstract:
    Several misconceptions persist about the International Roughness Index (IRI). In particular, many pavement engineers believe that the Golden Car model and its input parameters correspond to a specific out-of-date automobile suspension system. This corresponds to a classical misconception that the IRI is based on a 1960s Chevrolet Impala. This presentation provides education materials related to the relationship between the IRI and the dynamics of modern vehicles. The presentation explains the original methodology and philosophy behind the IRI, the relationship between the IRI and more detailed vehicle models, and the relevance of the IRI to modern automobiles and trucks. Theoretical and analytical demonstrations are used to help with conceptual explanations, and field measurements are used to provide examples that lend credibility. The presentation also addresses a few common special cases, such as tuning and wheelbase filtered responses to period roughness.
  • Session 2.5: Advancement of Airport Pavement Roughness Evaluation using RRI by Richard Ji, FAA
    Bio:
    Richard Y. Ji is a FAA airport pavement R&D branch project manager. Dr. Ji’s responsibility is managing and overseeing the FAA-funded projects at the FAA National Airport Pavement Test Facility (NAPTF). Dr. Ji received his doctoral degree in Civil Engineering from Michigan State University in 2005, with a specialization in pavement design and analysis. Dr. Ji is an active member of professional and technical organizations, including the Transportation Research Board (TRB), the American Society of Civil Engineers (ASCE), and the National Cooperative Highway Research Program (NCHRP). He has been a registered professional Engineer since 2007.
    Abstract:
    To assist airports in the assessment of the surface profile roughness of in-service runways the FAA has developed a new Runway Roughness Index (RRI). This index was established under research conducted by the FAA Airport Research and Technology Branch. The RRI was developed based on the Boeing Bump Index (BBI), pilot ratings to simulator testing, International Organization for Standardization (ISO) human vibration discomfort standards, and ProFAA’s aircraft simulation. Two types of the RRI were developed to categorize airport pavement roughness. The first as an average, total length, root mean square (RMS) RRI, and the second is a single event Transient RRI which is based on moving RMS. Threshold values were validated for the proposed ranges for acceptance, monitoring, and excessive levels of roughness needing immediate remediation. Built from an aircraft simulation, this index is more sensitive to long wavelength runway roughness than the international roughness index or 25-foot profilograph index. The RRI is shown to compliment the BBI and give a useful total pavement ride quality metric. Roughness events that would not have been identified using the BBI can be located using the RRI application in ProFAA.

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  • Session 2.6: Airport Runway Roughness Assessment using a Road Surface Profiler by Arturo Espinoza, Applied Pavement Technology and Gen Long
    Bio:
    Mr. Espinoza-Luque is an Engineering Associate at Applied Pavement Technology, Inc. (APTech), with a primary focus on research projects for federal and state clients, such as the Federal Highway Administration (FHWA), Strategic Highway Research Program (SHRP), the National Cooperative Research Program (NCHRP), and state Departments of Transportation (DOTs). Mr. Espinoza-Luque served as the student researcher for the Illinois Center for Transportation (ICT) for several projects in the field of asphalt materials testing and characterization. He is a licensed professional engineer in California and Illinois.
    Abstract:
    Pavement roughness assessment of roadway facilities is primarily focused on determining the ride quality experienced by vehicle passengers. In an airfield setting, the emphasis of roughness assessment is on the increased wear and tear on aircraft suspension components caused by surface irregularities. Depending on the aircraft, speed of travel, and loading characteristics, single discrete bumps in the pavement surface could lead to structural failure in the aircraft suspension system, which is intended to absorb energy during landing, not dampen the response to discrete bumps. While airplane passenger discomfort caused by roughness on runways and taxiways is a concern, the duration of this discomfort is much shorter than on roadways.
    In the fall of 2021, Applied Pavement Technology Inc. (APTech) conducted roughness testing at a major US commercial airport using the road surface profiler on its automated data collection vehicle. The testing, which was part of a study to identify the maintenance and rehabilitation (M&R) needs for the airport’s infrastructure, involved collecting profile data on all of the runways at 10-ft and 17.5-ft offsets from the runway centerline, as recommended in FAA Advisory Circular (AC) 150/5380-9 (Guidelines and Procedures for Measuring Airfield Pavement Roughness). The collected data were then processed using the ProFAA 3.0 software, and the results were presented in terms of the Boeing Bump Index (BBI), which is the ratio between the measured and acceptable bump heights. None of the analyzed runs had a BBI higher than 1.0, indicating that excessive roughness (that could induce additional stress on an aircraft) was not present on any runway.
    This presentation highlights the process used to collect, categorize, and analyze road profiler data to evaluate runway roughness using the BBI.

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  • Session 2.7: Detecting Bridge Deck Roughness at Highway Speeds by Ray Mandli, Mandli
    Bio:
    For over 40 years, Ray has been pushing the envelope in the visualization of ideas and knowledge through the thorough collection and reduction of real world data, especially where infrastructure is the subject matter. Mandli’s Team has provided technology and services to state and municipal departments of transportation in all 50 states. Today these solutions fuel the understanding needed to maintain current infrastructure as well as prepare these agencies for the potential of future autonomous, connected, electric and shared mobility for everyone.
    Abstract:
    Bridge decks can be a difficult and costly environment for the collection of pavement condition data. A visual inspection has been the most common method for assessing pavement conditions for many DOT Structures and Pavement groups. Inspection needs to take place during the day, requiring bridges to close so a team can collect pavement data, which is costly and complex under normal circumstances. The logistics involved mean selecting which bridges to examine based on past reporting, as there is not enough time to manually inspect them all. Ultimately, this means choosing to inspect fewer bridges but being more thorough with each inspection.
    Tennessee DOT saw this challenge and knew they wanted data for more than a select group of bridges. Mandli Communications worked with Tennessee to collect bridge data as part of their statewide automated collection. The solution is to use a 3D pavement profiler to collect data and imagery for bridge decks and make the visual and crack analysis information available to DOT staff on their computers.
    3D laser crack measurement technology (the LCMS) provides network coverage and eases the logistical issues involved with closing bridges for collection. It has nighttime collection capability, making it both safer and easier to gather pavement data. The data can then be used to decide which bridges may need a visit for a more thorough analysis and sampling of the deck materials.
    In this presentation, Mandli Communications and Tennessee DOT will address the importance of collecting all bridges in a network, instead of a select few, and address the LCMS as a proven technology to provide a more efficient and cost-effective solution. Ultimately, providing a cost-effective and efficient means of making this information available to DOT staff for analysis and planning.

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  • Session 2.8: Qs and As by Dave Huft, SDDOT
    Bio:
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  • Session 2.9: Lunch by NA, NA
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  • Session 2.91: Poster session in the Foyer room by NA, NA
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  • Session 2.92: 3D LiDAR for road network pavement quality management by Jacopo Alaimo, XenomatiX
    Bio:
    Jacopo joined XenomatiX to lead the expansion of its revolutionary and simple LiDAR technology in the North American region. With the vision to contribute to safer roads and transportations he is convinced of the advantages that the True Solid State could bring to these sectors. In his earlier career he covered R&D managerial positions in Marelli and Koito. Jacopo earned an MS in Aerospace Engineering and a Mountain Guide Certification, qualifications that reflect his passion for exploration and techniques.
    Abstract:
    LiDAR smart sensors used in self-guided vehicles are already being used today during periodic inspections of paved roads. The LiDAR sensor creates a digital copy of the road surface so that policymakers can observe and analyze the entire road network and its subsystems at a glance.
    The 6D measurement data includes a total image of the surface:
    – 3D digital representation of the surface (XYZ)
    – intensity measurements that visualize the marking
    – 2D camera images that overlap perfectly with the 3D point cloud
    In the following project, a LiDAR system creates a 6D digital copy of the road surface and contributes as such to efficient management of road works and maintenance.
    Objective analysis of road quality based on a calculation of IRI and rutting for the city of Leuven. By mapping the IRI (International Roughness Index) and rutting for roads in Kessel-Lo, a district of Leuven, the city’s municipal public works department has an overview of crucial sections of their road network. The data collected enable the identification and classification of other distresses like potholes, cracking, faulting, and shoving.
    Quality indices have been added to the GIS platform for simple and integrated preview and year over year tracking.

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  • Session 2.93: LiDAR certification for Roughness Profiling by Jacopo Alaimo, XenomatiX
    Bio:
    Jacopo joined XenomatiX to lead the expansion of its revolutionary and simple LiDAR technology in the North American region. With the vision to contribute to safer roads and transportations he is convinced of the advantages that the True Solid State could bring to these sectors. In his earlier career he covered R&D managerial positions in Marelli and Koito. Jacopo earned an MS in Aerospace Engineering and a Mountain Guide Certification, qualifications that reflect his passion for exploration and techniques.
    Abstract:
    LiDAR smart sensors used in self-guided vehicles are already being used today during periodic inspections of paved roads. The LiDAR sensor creates a digital copy of the road surface so that policymakers can observe and analyze the entire road network and its subsystems at a glance. New generation lidars brings the advantages of a portable sensor that leverage solid state electronic components, with high reliability and not subject to damages by vibrations. Collecting not only the profile but the full map of the road enables a more detailed analysis and the use of the same survey data not only for quality evaluation and certification but also for pavement design, equipment control like in 3D milling, and for a complete PMS data collection. In this presentation the performance of the new generation lidar has been compared with certified APL mechanical profilers proving its accuracy and repeatability and becoming a new standard in Belgium for pavement quality and roughness measurement and certification.
  • Session 2.94: The use of Texture Measurement for Chip Seal Quality Assurance by Ahmad Alhasan, ARA and Hyung Lee, Brian Moon, Douglas Steele, and John Senger
    Bio:
    Dr. Ahmad Alhasan is a Senior Engineer and the Research and Technology Deployment Team leader at Applied Research Associates (ARA) Inc. Ahmad specializes in transportation infrastructure performance evaluation and management, pavement and geomaterials assessment and design, pavement surface characterization and its impacts on traffic safety, and statistical analysis for multi-attribute decision making under uncertainty.
    Abstract:
    In recent years, chip seal applications have become a more common maintenance and preservation treatment for deteriorated pavement surfaces. These applications are mainly used to seal the fine cracks on a pavement surface to extend the life span of the existing pavement. In addition, chip seals are also frequently used to create a skid-resistant pavement surface with sufficient texture (or friction) for improving roadway safety. In general, chip seal applications involve spraying/spreading a layer of asphalt binder followed by a layer of aggregates (chips) which, in turn, is compacted so that the aggregate particles are adequately embedded into the binder. As such, a significant characteristic that affects the performance of chip seals is the percent embedment (PE) of aggregate particles. In this study we will discuss the use of PE as a QA measurement for newly constructed chip seals. The study involves an evaluation of PE measured from cores extracted from more than 15 sites in Illinois and using image analysis techniques. The presentation will discuss the image analysis process and estimation of PE and texture form images. The initial findings showed that multiple definitions can be used to quantify an average PE for a construction site. These definitions have shown significant correlations between each other in most cases yet had resulted in multiple values for the same sections. In addition, the presentation will include a discussion on the use of surface texture as a rapid alternative for in-situ testing. The procedure developed in this study can lead to simplified calibrated curves that estimate the percent of exposed aggregate to backcalculate the PE values. We will present the initial findings for the use of surface texture as an alternative to destructive testing as a QA procedure.
  • Session 2.95: Relationship of Asphalt Mix Gradation to Macrotexture and Safety – Preliminary Results by Gerardo Flintsch, VTTI and Amir Golalipour, Behrokh Bazmara, and Edgar de Leon
    Bio:

    Abstract:
    Pavement safety is provided through adequate pavement surface properties and two key surface properties—friction and macrotexture—are critical to make roads safe in all weather conditions. Thus, agencies must ensure adequate levels of friction and macrotexture to maximize contact and traction at the pavement-tire interface and minimize the risk of crashes. In particular, several past studies have identified a statistically significant relationship between roadway crashes and macrotexture. The presentation will discuss the preliminary results of a FHWA sponsored study aimed at providing the background to incorporate safety considerations as part of the hot-mix asphalt design. The final objectives of the project are to develop a field-calibrated macrotexture prediction model for asphalt surfaced pavements and provide guidance for agencies and construction contractors to consider macrotexture and safety in designing asphalt mixtures. The initial phase of this study explores and discusses: (1) Collected as-constructed macrotexture data and production mix design from three states, (2) Developing a set of initial models to estimate the macrotexture of mixes based on aggregate gradation and mix design parameters, and (3) Identifying the most relevant parameters to be controlled during the mix design process. The study started by reviewing and synthetizing scholarly and technical work on macrotexture definition, lab, and field testing and characterization, and relationship between macrotexture and safety. In the next step, the results were used to design an experiment, collect all relevant data, and develop a set of traditional linear and non-linear regression and machine learning based models. Then, they were compared to select the most appropriate approach, and preliminarily identify the most relevant aggregate gradation and mix design paraments that must be considered. Future steps include validating the model with data from additional states and developing guidelines to facilitate the adoption of the macrotexture and safety consideration in mix design practice.

  • Session 3.0: Session moderator by Gerardo Flintsch, VTTI
    Bio:

    Abstract:
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  • Session 3.1: Quantifying the Impact of Friction and Macrotexture on Roadway Crashes by Gerardo Flintsch, VTTI and Edgar de Leon, Ross McCarthy, Samer Katicha
    Bio:

    Abstract:
    The proposed contribution will present the final results of a study to quantify the impact of friction and macrotexture improvements on roadway crashes on a variety of roadway facility types, which includes segments, intersections, curves, and ramps on each category as applicable. The study was sponsored by FHWA and developed SPFs and Crash Modification Factors and Functions (CMFs/CMFx) using data from several states. These CMFs/CMFx can be used to predict and evaluate the effect of pavement friction and macrotexture improvement interventions on safety performance and to demonstrate how to evaluate pavement friction improvements as a cost-effective safety improvement.
    The analysis confirmed a strong statistical association between pavement surface frictional properties (friction and macrotexture) and crash rates. Lower crash rates were observed with higher friction (SFN40) and macrotexture (MPD) on all roadway types. Friction was found to have a statistically significant effect for predicting total crashes on all the roadway facility types; and macrotexture was found to have a statistically significant effect for predicting total crashes on most the roadway facility types, except on rural 2-lane, 2-way roads. These rural roads generally have lower speeds and macrotexture is more important at high speeds. The results suggests that potential reduction of up to 30% of total crashes can be achieved with a 10-point increase in SFN40. The study also developed illustrative friction investigatory thresholds for the various roadway facility and site types. They were developed based mostly on visual observation on the crash rates for different friction levels. As expected, the investigatory levels are higher for higher friction demand sites.

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  • Session 3.2: Towards Non-Contact Tire-Pavement Friction by Ahmad Alhasan, ARA and Brian Moon, Hyung Lee, John Senger
    Bio:

    Abstract:
    Tire-Pavement friction is a complex phenomenon affected by multiple factors including, but not limited to, the pavement surface texture, tire geometry and material characteristics, sliding speed, slip ratio, and skew angle. Currently, friction testing requires physical testing system requiring careful calibration, specialized tires, and water supply. In this study, the team will present the initial findings from a study using high density laser texture scans and high-speed texture scans to estimate friction coefficients from the Locked Wheel Skid Trailer (LWST) and the dynamic friction tester (DFT) test results. The study included 14 pavement surfaces and skid resistance test results that were acquired using the smooth and ribbed LWST tires and DFT for speeds between 10 km/h and 80 km/h. High-density texture scans were acquired at two spots on each pavement section, to capture the macrotexture and a portion of the microtexture. Moreover, the team collected a continuous texture profile using a high-speed texture scans on all pavement sections. Using the texture scans, the team developed a simplified model based on the Persson friction model to derive a pareto model that can relate different texture parameters to estimated friction test results on dry and wet pavements. The surface texture was characterized using wavelets energy as an average representation of the power spectral density (PSD) within a given bandwidth The presentation will introduce the concepts used in Persson’s friction model, the perturbation approach to simplify the model, and the experimental and modeling findings form this study. In addition, the team will discuss some of the requirements to collect texture data that can be sued for friction and skid resistance evaluation.

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  • Session 3.3: Texture Performance Models for North Carolina’s Primary Road Network by Boris Goenaga, NC State U and B. Shane Underwood, Cassie Castorena, and Paul Rogers
    Bio:
    Boris Goenaga is an instructor professor at Universidad del Norte in Barranquilla, Colombia. Boris got a bachelor’s degree and a master’s in civil engineering from the same institution; since his graduation, he has been studying pavement performance, transport planning, and highway safety.
    In 2018 Boris joined the Transportation Systems and Material research group at the Department of Civil, Construction, and Environmental Engineering of North Carolina State University (NCSU), where he is pursuing a Ph.D. degree under the direction of Dr. Shane Underwood and Dr. Cassie Castorena.
    Boris’ dissertation focused on the relationship between highway safety and road surface characteristics, the integration of a Pavement Friction Management Program (PFMP) and a Pavement Management System (PMS), and the quantification of uncertainty in pavement condition predictions. During his time as a student at NCSU he has participated in the TRB as a speaker and was awarded the International Road Federation (IRF) fellowship in 2020.
    Abstract:
    When a tire rolls over a pavement there will be different interactions between the critical components depending on the amount of deformation and the properties of the contact interface. In the literature, it is reported that the skid resistance available at the tire-pavement interface depends on two main mechanisms: adhesion and hysteresis. The first is related to the aggregate mineralogy and shape, whereas the second is proportional to the energy loss resulting from the tire deformation caused by the texture profile. Though both mechanisms are important across the entire speed range, it is accepted the macrotexture is predominant at high speeds, especially in wet conditions. On the other hand, measuring the surface macrotexture is relatively easy when compared to measuring friction. This fact is reflected in the amount of literature and protocols currently available for characterizing texture at a network level in contrast to those dedicated to friction characterization. Moreover, different authors have successfully used the surface texture characteristics, such as the Mean Profile Depth (MPD), as a crash predictor in a Safety Performance Function (SPF), the models presented until now have shown that crash risks increase when the MPD reduces. In consequence, knowing the amount of texture available in a surface during the pavement service life is important; for this reason, a set of texture performance models have been calibrated for North Carolina’s mixtures. More than 150 pavements with different ages, aggregate gradation, and mix type were incorporated during the calibration process. The resulting models suggest the initial texture depends on the aggregate gradation shape – here represented by the gradation coefficient of curvature (Cc) – and the binder content in the mix. The deterioration rate is a function of the climate regime. The expression proposed can be used to predict the available texture over the pavement life, which could facilitate calibrating a set of SPFs that incorporates the MPD as a safety predictor.

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  • Session 3.4: Identifying the In-Service Lifecycle of Pavement Friction by Isaac Briskin, WDM and Ryland Potter, Laura Thriftwood
    Bio:
    Isaac Briskin is the Director of Analytics at WDM USA Limited. Isaac has bachelor’s and master’s degrees in Applied Statistics from the University of Pittsburgh. Before joining WDM USA Limited, Isaac had a background in biostatistics. He worked at the Cleveland Clinic as a biostatistician, primarily working on research in orthopedic surgery, ophthalmology, neurology, and telemedicine, and he co-authored over 30 publications. Looking for new challenges, Isaac joined WDM USA, where he has applied his love for problem-solving to road safety analysis.
    Abstract:
    For both pavement maintenance and safety engineers, an understanding of the factors that drive substantial changes in the lifecycle of pavement friction are key to the timing and efficacy of surface treatments. This presentation explores the relationship between pavement friction performance, network and pavement characteristics, and time. Research published by North Carolina State University [Evolution of Pavement Friction and Macrotexture After Asphalt Overlay, Underwood et al] found that pavement friction either (a) increases from an initial post-overlay friction value until it peaks and afterwards decreases at a constant but potentially unequal rate or (b) decreases immediately after overlay. To determine which of those trajectories an in-service pavement’s lifecycle may follow and to model future friction values, WDM USA built a sample SCRIM® dataset of Kentucky Transportation Cabinet (KYTC)-maintained roads. SCRIM® data, including friction, macrotexture, roughness, and road geometry features (e.g. curvature, grade, crossfall), were collected annually over a three-year period and summarized at 0.005-mile increments. Network features (e.g. AADT, speed limit, lane count, lane/shoulder width) and mix design data included in the analysis were provided by the KYTC. Factors contributing to in-service friction performance in the sample dataset were analyzed with Repeated Measures ANOVA; time to friction failure was analyzed using Survival Analyses, including Kaplan Meier Analysis and Cox Proportional Hazards models. Explanatory variables considered in model construction include macrotexture (MPD and SMTD), pavement roughness, road geometry features, network features, and mix design information. Model selection, preliminary results, and the potential for modeling the in-service lifecycle of pavement friction on a statewide basis will be shared.
  • Session 3.5: Vehicle Control and Skid Resistance by John Andrews, Powele
    Bio:
    John Andrews is a graduate of Johns Hopkins University in Physics and is currently the Principal of Powel Enterprises. John spent much of his career in the design and manufacture of devices and machinery. In the 20 years prior to his retirement from Maryland State Highway Administration in 2019, he was responsible for the collection of highway and bridge condition data statewide. During that time, John worked on a local and national level to advance the state-of-the-art in highway data collection and analysis. One of these advances was the establishment of a program for the collection and analysis of GPR bridge deck data on a network basis. He was also the lead author of several AASHTO standards on highway data collection.
    Abstract:
    This presentation is a discussion of the tire/pavement interaction that is often called Skid Resistance or miss-titled as Friction. It is a pavement metric heavily responsible for vehicular control and the resultant safety of the traveling public. This is an attempt to present the complexities of this interaction between tire and pavement and the difficulty in effectively measuring the pavement’s contribution to vehicle control. Factors including micro texture, macro texture, micro-profile, macro-profile, contamination, skid forces, differential speed, metrics, and measurement techniques will be discussed. The hope is to initiate an in-depth discussion involving pavement designers, asset managers, and equipment manufacturers on how to move forward in providing the safest possible surface and on how to measure the true performance as effectively as possible.
  • Session 3.6: Session break by NA, NA
    Bio:
    NA
    Abstract:
    NA
  • Session 4.0: Session moderator by Steve Karamihas, UMTRI
    Bio:
    Steve Karamihas is a Research Area Specialist Senior at the University of Michigan Transportation Research Institute.
    Abstract:
  • Session 4.1: Pavement Evaluation Open Discussion – 1. Friction and Texture – Safety, 2. Crowd-sourced data, 3. Network Testing Equipment 4. Other by NA, NA and Steve Karamihas, Edgar D. de León Izeppi, Eric Prieve, Stephanie Weigel, and George Chang.
    Bio:
    NA
    Abstract:
    This is an open discussion on various hot topics on pavement evaluations.
  • Session 4.2: RPUG Business Meeting by Steve Hale, NVDOT
    Bio:
    Steve Hale has worked for the Nevada Department of Transportation for 24 years, with the last 2 years serving as the Assistant Construction Engineer. Steve is the 2023 Chair of the RPUG steering committee and has attended 13, including this year’s, RPUG conferences over his career. Steve graduated from the University of Nevada, Reno, in 1998 with a bachelor’s degree in Civil Engineering and is a registered Professional Engineer in the State of Nevada. Steve is the father of three; Baylee (Age 21), Michael (Age 20), and Natalie (Age 16). He has also been in a relationship with the love of his life, Tanya, for the last 9 years. Steve is a native Nevadan and enjoys all that Nevada has to offer. His hobbies include walking/jogging, going to the movies, and traveling.
    Abstract:
    NA
  • Session 4.3: Board Busses from hotel to Arch by NA, NA
    Bio:
    NA
    Abstract:
    NA
  • Session 4.4: Security at Arch by NA, NA
    Bio:
    NA
    Abstract:
    NA
  • Session 4.5: Evening Activity at Arch by NA, NA
    Bio:
    NA
    Abstract:
    NA
  • Session 4.6: Return from Arch to hotel by NA, NA
    Bio:
    NA
    Abstract:
    NA

    • “

  • Session 5.0: Session moderator by Andy Mergenmeier, FHWA
    Bio:
    Andy Mergenmeier is a Senior Pavement and Materials Engineer with the FHWA. His primary responsibilities include pavement surface characteristics measurement and analysis, construction materials acceptance, and pavement construction. He is the FHWA liaison to the American Association of State Highway and Transportation Officials (AASHTO) Committee on Materials and Pavements Technical Section responsible for management of pavement measurement standards including pavement profiling, friction, rutting and cracking. He is managing the pooled fund study, TPF-5(299)/(399), Improving the Quality of Pavement Surface Distress and Transverse Profile Data Collection and Analysis, which he will be discussing this morning. Andy is the Field Project Engineer for the FHWA Friction Management Program project that includes demonstrating continuous friction measurement technologies within the framework of a friction management program. He came to this position in 2007 after 7 years as the state of Virginia’s Department of Transportation’s (VDOT) State Materials Engineer. At VDOT he was responsible for overseeing preliminary engineering and construction functions, such as, pavement design and construction materials acceptance and testing programs. Before VDOT, Mr. Mergenmeier worked for the FHWA for 15 years in various locations throughout the US.

    Mr. Mergenmeier is a Civil Engineering graduate from the University of Kansas, and a Registered Professional Engineer.
    Abstract:

    • ”
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  • Session 5.1: TPF-5(399) Pooled Fund Updates by Andy Mergenmeier, FHWA
    Bio:
    Andy Mergenmeier is a Senior Pavement and Materials Engineer with the FHWA. His primary responsibilities include pavement surface characteristics measurement and analysis, construction materials acceptance, and pavement construction. He is the FHWA liaison to the American Association of State Highway and Transportation Officials (AASHTO) Committee on Materials and Pavements Technical Section responsible for management of pavement measurement standards including pavement profiling, friction, rutting and cracking. He is managing the pooled fund study, TPF-5(299)/(399), Improving the Quality of Pavement Surface Distress and Transverse Profile Data Collection and Analysis, which he will be discussing this morning. Andy is the Field Project Engineer for the FHWA Friction Management Program project that includes demonstrating continuous friction measurement technologies within the framework of a friction management program. He came to this position in 2007 after 7 years as the state of Virginia’s Department of Transportation’s (VDOT) State Materials Engineer. At VDOT he was responsible for overseeing preliminary engineering and construction functions, such as, pavement design and construction materials acceptance and testing programs. Before VDOT, Mr. Mergenmeier worked for the FHWA for 15 years in various locations throughout the US.

    Mr. Mergenmeier is a Civil Engineering graduate from the University of Kansas, and a Registered Professional Engineer.
    Abstract:
    TPF-5(399) Pooled Fund Updates

    • ”
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  • Session 5.2: Pavement Management Roadmap by Max Grogg, APT
    Bio:
    Mr. Grogg has been a Senior Engineer for Applied Pavement Technology for five years, working on various pavement design, materials quality, and pavement and asset management projects. Before that, he worked for the Federal Highway Administration for over 32 years in various offices, where he worked on a wide range of pavement technologies and practices with various States and the administration of the Federal-aid Highway Program. Max also worked for three years for the Illinois Department of Transportation in District 8. Mr. Grogg has a B.S. in Civil Engineering from the Missouri University of Science and Technology and an M.S. from the University of Illinois. He is a registered professional engineer in the State of Virginia.
    Abstract:
    The FHWA’s update to its Pavement Management Roadmap helps to identify the steps that will address current gaps in pavement management and establish research initiatives and priorities. Initial gaps were identified based on a literature review, project team knowledge, and a satisfaction survey of Federal, State, and local pavement management practitioners. The gaps were grouped according to four themes:
    • Theme 1: Data focused on data collection, data quality, and data management.
    • Theme 2 Pavement Management Analysis Tools and Other Applications focused on performance modeling, treatment rules and impacts, pavement management analysis, and performance measures.
    • Theme 3 – Workforce and Organization Issues, focused on training, workforce development, technical assistance, tools, communication, and organizational challenges.
    • Theme 4 – Technological Advancements – New Tools, Methodologies, and Technology focused on promoting strategies for using new technology to support pavement management data collection and analysis.
    The Roadmap was derived from a series of virtual stakeholder workshops in which representatives from State and local agencies, academia, private industry, and the FHWA met to discuss and prioritize suggestions for enhancing current practices. The Roadmap contains 72 action items (46 short-term and 26 long-term) with an estimated cost of $30.225 million in 15 improvement areas across the four themes. The results can be used to determine new research, development, and technology transfer opportunities.

    • ”

  • Session 5.3: Accuracy versus quantity – can they co-exist? by Richard Wix, ARRB
    Bio:
    Richard Wix is the ARRB/National Transport Research Organisation’s (NTRO) Discipline Leader for Infrastructure Measurement. During his time at ARRB/NTRO, Richard has had a strong focus on the collection and analysis of functional and structural pavement condition data for road managers in Australia and New Zealand. He has also been integral in introducing and integrating innovative technologies into road survey platforms to help road agencies improve the management of their road networks and associated infrastructure. Richard has also been involved in developing the Austroads test methods for pavement condition evaluation and is a member of several international committees and groups that help him keep up to date with the latest developments in data analysis and automated pavement condition data collection technologies from around the world.
    Abstract:
    The FHWA Highway Performance Monitoring System (HPMS) pavement data item reporting requirements are partly in response to current legislation (along with the more general 23 U.S.C./CFR requirements). A detailed overview of the HPMS pavement data item reporting requirements will be presented in support of the FHWA Transportation Performance Monitoring (TPM) and management effort as well as the more general HPMS requirements. A brief description of potential and existing problematic areas and issues will be included. Data items primarily include IRI, rutting, faulting, and cracking along with various other associated item requirements such as reporting cycles, dates, and metadata.

    • “

  • Session 5.4: A Case Study in the Application of Guidelines for Cracking Assessment for the Vendor Selection Process by Douglas Frith, QES
    Bio:
    Doug Frith is Vice President of Quality Engineering Solutions, Inc. and a Principal Engineer with 34 years of highway engineering and construction experience. His primary emphasis has been on pavement engineering, including research, evaluation, management, and design. He received Bachelor’s and Master’s of Civil Engineering Degrees from the University of Idaho. He is a former member of the TRB Pavement Management Committee and a current member of the TRB Pavement Condition Evaluation Committee.
    For the past 22 years, Mr. Frith has been applying modern technical developments in pavement management, maintenance, and design in the consulting field. He currently manages the Quality Assurance and Data Validation efforts for over 50,000 miles of pavement management data collected for multiple state agencies annually.
    Abstract:
    In 2020 FHWA published a report titled “Developing Guidelines for Cracking Assessment for Use in Vendor Selection Process for Pavement Crack Data Collection/Analysis Systems and/or Services” as FHWA Publication Number FHWA-RC-20-005. In 2022, in conjunction with the Federal Lands procurement of high-speed distress data collection, proposing vendors were encouraged to participate in the collection and reporting of pavement distress data across six control sections located around the Washington DC area. This study focuses on the application of the documented methodology which main goal is to identify vendors or equipment that give similar results as the ground reference or results close enough to not affect the outcomes. Three different vendors (Vendor A, Vendor B, and Vendor C) participated in the high-speed data collection and delivery, and two groups collected the manual ground reference data (QES and Federal Lands). The ground reference teams collected the cracking data manually, whereas each of the vendors used their integrated pavement data collection vehicles equipped with 3D laser technology for crack detection. The cracking criteria selected for the study was the highway performance monitoring system (HPMS) cracking which is the percentage of the total area exhibiting visible cracking for all severity levels in the wheelpaths. The HPMS rating served as the basis to determine outcome equivalence between vendors and ground reference. The statistical test known as paired equivalence testing was conducted for each site for multiple risk levels. The HPMS ratings equivalence were used to determine recommended limits and risk levels for the future application. The results obtained and the analysis of cracking data indicate that the variability between vendors, in this case, is large enough to provide different pavement management system recommendations.

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  • Session 5.5: A Case Study of Pavement Management Products Using Human Evaluation Versus Automated Techniques for Local Governments by Jacob Walter, ARA
    Bio:
    Mr. Jacob Walter, P.E. is a Principal Engineer with Applied Research Associates from the Camp Hill, PA office just outside of Harrisburg. He has spent the last 24 years implementing infrastructure management systems across North America, specializing in pavement management and software for asset management applications. He has worked in all aspects of these projects, including data collection, evaluation, implementation, quality control, and project management. His clients include all types of agencies in North America, including States, highway agencies, counties, cities, and towns. Mr. Walter has a degree in Civil Engineering from George Washington University and a Professional Engineer’s license from the State of Ohio.
    Abstract:
    The two major roles of a Pavement Management System (PMS) are to report current pavement condition and to optimize maintenance and rehabilitation (M&R) planning based on available funding or performance targets. Evaluation techniques have evolved over the past 25 years to the point where human raters can be replaced, in part or in full, with programs that automate the evaluation process. However, as we move closer to fully automated evaluation, a surprising side effect is that treatment recommendations are also changing along with pavement evaluation technology.
    This ongoing case study compares the results of condition ratings and treatment selection from human-rated and automated surveys in a municipal environment – Adams County, Illinois.
    ARA implemented a PMS in 2015 for the County Highway Department. In 2018 and 2021, the County’s pavement was evaluated using Pavemetrics’ Laser Crack Measurement System (LCMS) which provides data in a format that enables automated evaluation techniques. While the LCMS provides raw distress identification, classification software is required to determine a well-known rating such as PCI. ARA used ICC Connect for this purpose. ARA used existing performance models and treatment criteria to create a capital improvement plan using our iAM analysis software.
    This presentation will discuss a quantitative comparison between the 2018 survey and 2021 survey with a focus on both pavement condition ratings and selected treatments. The presenter will discuss concerns that occur more frequently in municipal (i.e., non-highway, non-state maintained) networks when using automated evaluation and some of the advantages of moving to the automated process. The presenter will focus on the change in the ultimate work products of the PMS: the current condition inventory and the capital plan. Finally, the presenter will discuss what ARA currently sees (as of 2023) as issues and advantages of using automated evaluation for similar agencies throughout North America.

    • ”

  • Session 5.6: Qs and As by Andy Mergenmeier, FHWA
    Bio:
    NA
    Abstract:
    NA
  • Session 5.7: Session break by NA, NA
    Bio:
    NA
    Abstract:
    NA
  • Session 6.0: Session moderator by Steve Hale, NVDOT
    Bio:
    Steve Hale has worked for the Nevada Department of Transportation for 24 years, with the last 2 years serving as the Assistant Construction Engineer. Steve is the 2023 Chair of the RPUG steering committee and has attended 13, including this year’s, RPUG conferences over his career. Steve graduated from the University of Nevada, Reno, in 1998 with a bachelor’s degree in Civil Engineering and is a registered Professional Engineer in the State of Nevada. Steve is the father of three; Baylee (Age 21), Michael (Age 20), and Natalie (Age 16). He has also been in a relationship with the love of his life, Tanya, for the last 9 years. Steve is a native Nevadan and enjoys all that Nevada has to offer. His hobbies include walking/jogging, going to the movies, and traveling.
    Abstract:

    • “

  • Session 6.1: Performance Monitoring of Mechanistically Designed Pavements in Illinois by John Senger, ILDOT and Arturo Espinoza, Prashant Ram, and David Peshkin
    Bio:
    John Senger received a Bachelor of Science in civil engineering from Bradley University. John has been at the Illinois Department of Transportation for 8 years and is currently the Engineer of Pavement Technology. Prior to joining IDOT, John worked as a consultant engineer, where he was involved in a wide variety of projects. John is responsible for Illinois DOT’s ride quality specifications, and friction program and manages ICART. John is currently serving as the chair of the Pavement Surface Properties Consortium and as the vice chair of the RPUG steering committee.
    Abstract:
    The Illinois Department of Transportation (IDOT) has been conducting surveys to monitor the performance of mechanistically designed pavements since 1986. The primary purpose of this effort is to verify, validate, and if necessary make adjustments to the design procedures and life-cycle cost models used in the pavement selection process. Currently, the performance of 96 full-depth hot-mix asphalt (HMA) pavement sections (representing 882 lane-miles), 53 jointed-plain concrete pavement (JPCP) sections (representing 409 lane-miles), and 29 continuously reinforced concrete pavement (CRCP) sections (representing 481 lane-miles) is being monitored.
    Until 2018, the distress surveys were conducted manually using a 3-person survey crew. Rutting and roughness measurements were not included as a part of the manual surveys. In 2019, the IDOT transitioned to a semi-automated data collection approach using an automated data collection vehicle equipped with a laser crack measurement system (LCMS) to generate high-resolution 2D and 3D profiles of the road. The pavement imagery data are then manually reviewed by a rater to identify distress types and quantify extents and severities over the length of the pavement section. In addition to the distress data, rutting and International Roughness Index (IRI) data are also collected using a road surface profiler that is attached to the data collection vehicle. Once the data are collected and summarized, the patching quantities over time and the service life of the wearing course are analyzed for each pavement type and compared to the projections based on IDOT’s mechanistic models. To date, IDOT has found no strong evidence to justify revisions to the current design procedures or to the maintenance and rehabilitation models. IDOT will continue monitoring performance of these pavement sections into the future.
    This presentation highlights the tools and technologies used by IDOT to monitor the performance of its mechanistically designed pavements and how the collected data are being applied by the Department.

    • ”

  • Session 6.2: 3-D Pavement Surface Measurement Technology/Certification and Automated Pavement Distress Identification and Reporting by John Yeaman, PMS
    Bio:
    John Yeaman is a pavement asset management specialist with over 30 years of experience in the industry. Following a career in the Australian Army, John joined his father, Dr. John Yeaman, in the business, and together they built a successful pavement management consultancy which Fugro ultimately bought. John Senior may be known to some of you as he studied under Professor Carl Monismith at the University of California, Berkeley. John reacquired the company eight years ago and continues to build on his father’s legacy. With specialist services in highway condition monitoring, pavement management systems, and pavement design capabilities, John’s company, Pavement Management Services continues to be one of Australia’s leading and well-respected civil engineering consultancies.
    Abstract:
    As one of the only two automatic crack detection systems in Australia, the using the Automated Road Analyzer (ARAN LCMS) has been in high demand following the aftermath of recent floods on the east coast. Recently, the ARAN has been deployed in the City of Brisbane as part of the Flood Impact Assessment project. It has been scanning every street in Brisbane City for potholes and cracks and was featured on 7NEWS for its crucial work in restoring the city’s streets. This presentation focuses on ARAN – a fully automated system that can automatically extract crack data, including crack type and severity. The high resolution of the LCMS means it can simultaneously detect ruts, macrotexture and raveling. The LCMS has a built-in 3D imaging system that provides both range and intensity data which differentiates it from other automatic crack detection techniques. ARAN LCMS’ lasers allow the extraction of much finer cracks – as fine as 3mm, and its advanced GPS system enables reliable crack location data to be generated. ARAN imagery relies on the Pave 3D subsystem that uses high-speed cameras, custom optics and laser line projectors to acquire both 2D images (black and white intensity) and high-resolution 3D profiles (surface elevations) of the road. A detailed image of the pavement surface can therefore be produced: ideal for identification and rating of pavement defects. Automated pavement distress algorithms can then more easily calculate the extent and severity of pavement cracks and distresses, resulting in more accurate and repeatable rating of pavement cracking and distresses.

    • “

  • Session 6.3: An Update to the Little Book of Profiling by Steve Karamihas, UMTRI
    Bio:
    Steve Karamihas is a co-author of the Little Book of Profiling, and is working on an update.
    Abstract:
    Since 1995, The Little Book has provided basic information about road profile measurement and interpretation to road profiler users. An update to the Little Book has been developed with support from TPF-5(354). While much of the material in the Little Book remains pertinent, an update was needed that addresses changes to the state of practice since the 1990s. These include: (1) Increased application of road profilers for construction quality control and assurance, (2) Upgrades to profiler and sensor technology, (3) Establishment of standard profiler certification practices, (4) increased use of road profilers to measure urban and low-speed roadways, and (5) advancements in our understanding of measurement errors.
    This presentation describes the scope of the Little Book, the motivation for the update, and major changes to the structure and technical material of the document. The presentation emphasizes material added or heavily modified to address the changes to the state of the art listed above, and includes several of the new illustrations.

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  • Session 6.4: Transverse Pavement Profile Certification and Validation: A Vendor’s Perspective by Stefan Brylski, Mandli
    Bio:
    Stefan Brylski graduated from the University of Wisconsin – Milwaukee with a degree in Physical Geography. He has been with Mandli Communications for 11 years, working in various roles. In his current position as a Pavement Product Specialist, he helps oversee the production of Mandli’s pavement-related products. He develops processing and summarizing workflows for each project, maintains QA/QC processes used by the company, and assists in the development and implementation of new technologies and products.
    Abstract:
    With the transverse pavement profile (TPP) standard (AASHTO pp 106-11) appearing in more and more network data collection, Mandli Communications wants to share a vendor’s perspective on the journey to meeting TTP validation and certification.
    In April 2022, Mandli participated in a pilot project conducted by FHWA to test the accuracy of our methodology to meet the new TPP standard. A significant hurdle that was cleared by Mandli was the ability to create an initial workflow for creating the TPP AASHTO data deliverables using the 3D laser crack measurement system (LCMS). Based on the testing during this pilot project, we have actionable areas of improvement to guide our future work. Mandli found that on the road to meeting repeatability and accuracy defined by the new standard, the first step is getting data formatted so that it can be reviewed for those statistics by all parties.
    In this presentation, Mandli will share our experience participating in a pilot data collection for TPP validation. During this presentation, we will highlight a few of these tests and explore ways to meet the new standards. Mandli will discuss what worked in the pilot, what didn’t, and the lessons learned that can help guide the industry forward.

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  • Session 6.5: Successful Practices for Data Quality Management by Amanda Gilliland, Transtec Group and George K. Chang
    Bio:
    Amanda Gilliland is an engineer and project manager at The Transtec Group, specializing in pavement research and design. Her expertise encompasses pavement surface characteristic data quality and intelligent construction technologies. Ms. Gilliland participated in the recently-completed “”Guidance for Quality Management of Pavement Surface Condition Data Collection and Analysis”” project. The final report from this project summarizes successful practices for data quality management programs related to pavement surface condition data. During the project, she successfully piloted newly developed certification and verification procedures for transverse pavement profiling and automated crack detection equipment. Ms. Gilliland offers help desk support and contributes to training workshops through the ProVAL Support Center. She attended the University of Utah and resides in Juneau, Alaska.
    Abstract:
    US DOTs collect pavement surface characteristics (PSC) data to evaluate road network quality. The PSC data include functional (International Roughness Index [IRI]) and distress metrics (cracking, rutting, and faulting) per the US Highway Performance Monitoring System (HPMS) field manual definitions as required per 23 CFR 490.319(c). The HPMS data uses national standard definitions to evaluate road networks nationally (e.g., good, fair, or poor). In addition to HPMS data requirement, some DOTs also collect state-specific metrics for maintenance and rehabilitation decision. However, some states have different definitions for cracking and record different cracking parameters, such as type, severity, and length. State pavement management programs depend on these specific data definitions for maintaining data consistency and making historical comparisons and budgeting processes.
    Since most US DOTs report that their road networks are their largest asset, ensuring high-quality PSC data is paramount. However, data verification is not easily performed by DOTs due to the variety of technologies and, until recently, the lack of certification and verification standards. Under the Transportation Pooled Fund (TPF)-5(299)/(399), efforts are devoted to improving PSC data quality and management processes and developing standards to certify data collection equipment and evaluate the collected data. The proposed presentation will include findings from the recently completed project “Successful Practices for Quality Management of PSC Data Collection and Analysis,” including the latest PSC quality practices from the projects completed under TPF-5(299)/(399). These projects include procedures to certify 3D data collection systems that collect transverse pavement profile (TPP) and cracking metrics using control sites and ground reference data. The presentation will include ready-to-implement data quality checks that can be incorporated into existing data quality management programs (DQMPs) and be tailored to DOTs with varying data definitions, network lengths, budgets, and resources.

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  • Session 6.6: lunch by NA, NA
    Bio:
    NA
    Abstract:
    NA
  • Session 6.61: Poster session in the Foyer room by NA, NA
    Bio:
    NA
    Abstract:
    NA
  • Session 6.62: Methods for assessing accuracy of deep learning crack detection models with imperfect ground truth by Anmol Sharan Nagi, Fugro and Harshpal Singh
    Bio:
    Anmol Sharan Nagi is an Innovation Engineer at Fugro. Anmol specializes in the research and development of computer vision techniques using deep learning. Anmol received his M.A.Sc. degree in Systems Design Engineering with a specialization in Machine Learning from the University of Waterloo, ON, Canada in 2020.
    Abstract:
    Fully automated, highly accurate pavement distress detection from 2D or 3D pavement imaging systems has long been a challenge in the pavement management industry. Early approaches to solving this challenge using classical computer vision-based algorithms have been found to have low accuracy in detecting defects such as cracking and produce considerable false positives. This leads to additional manual verification overhead which is a costly and slow process. The rise of popularity and access to machine learning, and more recently deep learning techniques have revolutionized applications in computer vision, however one challenge in developing models which are proven to produce accurate results lies in both the quantity and quality of pavement distress annotations that can be used to train the models and assess the accuracy of the model output. Traditional image segmentation metrics such as mIOU and F1 score are accurate when pixel perfect annotations are available especially for thin line objects like cracks. In this paper we will present methods for assessing the quality of crack detection models in the absence of pixel perfect crack line annotations. Experiments reveal that the model can detect the underlying crack when trained on loosely labeled data where annotations follow the general trend of the crack. This considerably reduces the time and costs to annotate datasets. We calculate the crack graph branch coverage and the total crack length coverage (CLC) metrics by comparing the skeletons of predicted segmentation results with the ground truth masks. Although the predictions do not completely overlap the imperfect ground truth, by buffering the annotations an overlap percentage (CLC) can be calculated for each crack branch in the crack skeleton graph.
  • Session 6.63: Deep Learning-based pavement distress identification with 3D pavement surface images: challenges and opportunities by Haitao Gong, TX State U
    Bio:
    Haitao Gong is a postdoctoral scholar affiliated with Texas State University, where he is focusing on improving pavement distress measurement through the application of deep learning techniques. He recently received his doctoral degree in Material Science, Engineering, and Commercialization from Texas State University, after earning his bachelor’s and master’s degrees in Transportation Engineering, along with a minor in Computer Science. Prior to his academic pursuits, he served as a transportation engineer and infrastructure investment consultant with China Communication Construction Company for five years. His research has resulted in several publications and has generated viable business concepts that are currently undergoing commercialization.
    Abstract:
    Recently, Deep Learning (DL) methods have been intensively studied in pavement surface distress classification, detection, and segmentation. The results of these studies indicate a great potential of DL methods for accurate pavement condition assessment. This presentation will discuss the opportunities and challenges of applying DL methods to industry-level 3D pavement surface images for pavement distress identification based on the practice of the research team. The contents will be divided into three parts: 1) data preparation, 2) architecture design, and 3) model selection. Data preparation is the first and basic step of DL-based model development. The main challenge is to develop a training dataset that covers a wide variety of pavement surface characteristics and is annotated with accurate distress information. Experiments have been conducted to explore the effects of data quality and quantity on model performance, and the main results will be discussed in the presentation. Neural network architecture design is another important part of model development. While we already have access to hundreds of available architectures, it is essential to adopt the ready-made ones or develop new ones that are suitable for pavement distress identification. Experiments have been conducted to illustrate how different architectures would perform differently over the same dataset, and the main results will be discussed in the presentation. Model selection is the last step before deployment. The basic strategy for model selection is to select the model that delivers the best performance over the test dataset. A set of measurements of effectiveness (MOE) should be adopted for the model evaluation and selection. In addition, many other factors must be considered. For example, Explainable AI (XAI) may help make better model selection.

    • “

  • Session 6.64: Interpretation of 3-D Pavement Surface Data with
    Dual-tree Complex Wavelet Analysis by Kazuya Tomiyama, KIT and Yuki Yamaguchi, Kazushi Moriishi
    Bio:
    Dr. Kazuya Tomiyama is an associate professor in the field of mobility engineering at the division
    of Civil and Environmental Engineering, Kitami Institute of Technology, Japan. He received a
    doctoral degree of engineering from Kitami Institute of Technology in 2010. His research focuses
    on pavement engineering, road surface informatics and transportation engineering with respect to
    the human-road interaction. He is actively engaged in international and local cooperation research
    projects, and is involved in academic societies and organizations such as the Japan Society of Civil
    Engineers, the International Committee on Pavement Technology, and the Pavement Diagnosis
    Research Group.
    Abstract:
    Three-dimensional (3-D) measurement technologies are developing rapidly and increasing in demand for the application of pavement engineering fields. The point clouds acquired with 3-D measurement technologies yield much more information than traditional two-dimensional measurements in terms of diagnostic viewpoints of pavement surfaces. The analysis based on the 3-D measures possesses a wide variety of potential applications to the evaluation of surface characteristics. One of the applications to a pavement surface allows area-based evaluation and the detection of localized irregularities. For this purpose, the required characteristic needs to be detected effectively from the 3-D measured data because the pavement surface characteristics consist of gradient, roughness, texture, and their combination. In this presentation, the dual-tree complex wavelet transform (DTCWT) are proposed to analyze point clouds of 3-D measured pavement surfaces. DTCWT which is able to implement directional multiresolution analysis allows effective and efficient data processing for 3-D measurements, and diagnostic identification in terms of wavy characteristics such as the wavelengths, locations, and directions. It also ensures the clear and theoretical interpretation for the analysis result of point clouds. This presentation introduces the application of DTCWT to block pavements in a pedestrian zone as an example considering (1) visualization of surface fault, (2) identification of artificial structures on a surface, and (3) directional analysis of surface deformation. The result shows that the typical localized irregularities are distributed in specific wavebands and directions in terms of the wavy characteristics of the pavement surface. Finally, this presentation proves the capability of directional multiresolution analysis based on DTCWT to identify the areas of pavement surface which require maintenance and rehabilitation by use of the 3-D measurement technologies.

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  • Session 6.65: Bridge and Structure Profile Measurement and Analysis by Tom Wilson, ARA
    Bio:

    Abstract:
    The Illinois Tollway has been collecting longitudinal profile data for nearly 20 years. For the first 15 years of this effort, the profile data was truncated to eliminate the bridges and their adjacent structural elements from the analysis of pavement roughness. Recently, data collection and analyses have been expanded to include these bridge decks, the approach/leave slabs, and the transition slabs between the approach/leave and the mainline pavement. Analysis of these TADLT segments (transition-approach- deck-leave-transition) is the first step in documenting the progression of roughness along those structural surfaces and in particular, roughness associated with the transverse joints between each of the elements. The effort to collect TADLT data has coincided with the Tollway’s adoption of a new bridge deck smoothness specification. The new specification requires that all new bridge decks are constructed slightly thicker than design so that the surface can be diamond ground prior to opening to traffic. By diamond grinding the TADLT segments and a portion of the adjacent pavement, a smoother surface is provided at the very beginning of the service life of these elements. It is expected that the smoother surface will reduce vertical dynamic loading, which should increase the service lives of the bridge decks and their adjacent structural elements.
    The longitudinal profile data used for the TADLT evaluation is collected as part of the annual, network- level data collection effort carried out using ARA’s digital survey vehicles (DSVs). One advantage of using this data source has been the ability to analyze longitudinal profile data collected previously using the begin/end points established for each lane of each bridge. Annual analysis of the longitudinal profile data has included both the current year and a previous year’s data, providing a longer time series than would have been available if only the current year’s data were being used.

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  • Session 7.0: Session moderator by Colin McClenahen, PennDOT
    Bio:

    Abstract:
    NA

  • Session 7.1: Evaluating the relationships between different testing systems used on roadways to measure friction and macrotexture on state highway agencies to assess similar friction characteristics (microtexture and macrotexture) by Edgar D. de León Izeppi, VTTI and Gerardo W. Flintsch, Ross McCarthy, and Brian Diefenderfer
    Bio:

    Abstract:
    An important emphasis of the implementation of Pavement Friction Management Programs (PFMP) is the accreditation of the devices used to measure friction and texture. PFMPs involve the regular monitoring of network pavement friction and the use of friction and macrotexture thresholds that are linked to key safety performance measures. This presentation will show the first efforts to compare texture and skid resistance measurements taken with various devices at the Virginia Smart Road in May 2023. This project was made by the Transportation Pooled Fund TPF-5 (463) Managing the Pavement Properties for Improved Safety, with the collaboration of a variety of devices from various private equipment operators. The goal of this project is to use the results of this research effort to begin a process to implement accreditations of the various state agencies for their data collection. The process will need to complete intermediate qualifications (repeatability and reproducibility) that will allow the certification of the devices used in the comparisons made by the TPF-5(463) Pooled Fund.

  • Session 7.2: ICAR for Pavement Evaluation Tests by John Senger, ILDOT
    Bio:
    John Senger received a Bachelor of Science in civil engineering from Bradley University. John has been at the Illinois Department of Transportation for 8 years and is currently the Engineer of Pavement Technology. Prior to joining IDOT, John worked as a consultant engineer, where he was involved in a wide variety of projects. John is responsible for Illinois DOT’s ride quality specifications, and friction program and manages ICART. John is currently serving as the chair of the Pavement Surface Properties Consortium and as the vice chair of the RPUG steering committee.
    Abstract:
  • Session 7.3: Closing and Introduction to Next RPUG by Steve Hale, NVDOT
    Bio:
    Steve Hale has worked for the Nevada Department of Transportation for 24 years, with the last 2 years serving as the Assistant Construction Engineer. Steve is the 2023 Chair of the RPUG steering committee and has attended 13, including this year’s, RPUG conferences over his career. Steve graduated from the University of Nevada, Reno, in 1998 with a bachelor’s degree in Civil Engineering and is a registered Professional Engineer in the State of Nevada. Steve is the father of three; Baylee (Age 21), Michael (Age 20), and Natalie (Age 16). He has also been in a relationship with the love of his life, Tanya, for the last 9 years. Steve is a native Nevadan and enjoys all that Nevada has to offer. His hobbies include walking/jogging, going to the movies, and traveling.
    Abstract:
    NA
  • Session 8.1: Buses leave from hotel to ICAR test track by John Senger, ILDOT
    Bio:
    NA
    Abstract:
    NA
  • Session 8.2: Buses back from ICAR test track to hotel by John Senger, ILDOT
    Bio:
    NA
    Abstract:
    NA

    • “

  • Session 9.1: TPF-5(354) Pooled Fund Meeting by Dave Huft, SDDOT
    Bio:
    NA
    Abstract:
    Improving the Quality of Highway Profile Measurement – Pooled Fund Meeting
    This meeting is for its members and all others interested in this subject.

    • ”

  • Session 10.1: ProVAL workshop by George K. Chang, Transtec Group and Steve Karamihas of UMTRI, Amanda Gilliland of Transtec Group
    Bio:
    NA
    Abstract:
    This workshop is hands-on centric with ProVAL software excises. It will cover some fundamental ProVAL viewing/analysis, then get into more in-depth topics (Profile Editor/Filtering, PSD module, SAM/grinding simulation, profile comparison/PCM module). All participants need to bring their laptop computer preinstalled with ProVAL 3.61.

    • “

  • Session 10.2: TPF-5(345/463) Friction Pooled Fund Meeting by Edgar D. de León Izeppi, VTTI
    Bio:
    NA
    Abstract:
    Pavement Surface Properties Consortium: Phase III – Managing the Pavement Properties for Improved Safety – Pooled Fund Meeting
    This meeting is for its members and all others interested in this subject.

    • ”