RPUG 2024 Speakers Bios and Abstracts

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This is a TPF-5(463) Friction Pooled Fund Meeting to discuss the TPF’s friction studies.

All TPF members and friends are welcome!

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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 effort to compare texture and skid resistance measurements taken with various devices at the Illinois DOT Certification and Research Track (ICART) facility in May 2023. This project was organized 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 DOT and 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.

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With most fatal motor vehicle accidents resulting from roadway departures, pavement surface friction has become an essential and critical metric to measure for identifying hazardous (actual and potential) locations on a road network. As Continuous Friction Measurement Equipment (CFME) becomes more readily available for network and project level safety assessments in the United States, the need for a validation procedure is becoming more prevalent. While testing protocols have been generated, questions remain regarding the application of the data.
This presentation is intended to share recent efforts to work with Road Agencies to develop procedures for testing repeatability together with relationships to known metrics. With a predefined experimental factorial, repeat runs on a variety of known pavement surfacing types provides the framework for this effort. Initial testing has been conducted on a closed track to provide a more controlled testing environment. In addition, two different tire types have been included in the initial evaluation to assess the impact of this important factor on the test results.
Initial repeatability findings will be presented along with future testing initiatives being proposed with the objective of working towards a more unified and accepted validation/verification process that is recognized and accepted by the industry.
Hopefully through this presentation additional ideas and suggestions for improvement can be gathered.

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An industry demand for contactless and non-destructive pavement friction evaluation has existed for many years. This presentation will review the continued development of a texture evaluation system to corelate pavement texture to pavement friction measurements.
Pavement core data samples from several contributing state agencies have been evaluated and compared to correlating pavement friction data to develop a method of using laser-based data sampling to generate a relationship between pavement texture and pavement friction values. A method of evaluating texture characteristics at high speeds would prove to be very useful in the pavement performance and safety industry where traditional skid testing and friction testing on large roadway networks isn’t cost effective or feasible.

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Highway safety depends on significant factors, especially pavement friction and macrotexture. According to the Federal Highway Administration inadequate frictional properties can result in serious injuries, particularly on high-speed roadways. Research shows macrotexture improves wet friction by facilitating water drainage from tire-pavement surfaces and a significant association between higher macrotexture and lower crash rates. This research investigates the use of Artificial Neural Network (ANN), which may allow a more comprehensive assessment of pavement safety, for developing a macrotexture prediction model by using aggregate properties, mix volumetrics, and construction parameters. A variety of mix type characteristics, including open-graded friction course (OGFC), dense-graded (DGAC) and gap-graded (i.e., Stone Matrix Asphalt), with higher and lower macrotexture values were evaluated as contributors of macrotexture. The study analyzed the use of the available aggregate properties, binder content (Pb), and mix volumetrics to predict expected field macrotexture, within a year of construction, in five states in the United States. The ANN model includes 21 predictor variables in the input layer, a single hidden layer (Composition of linear and non-linear functions), and one output as the predicted macrotexture. Subsequently, the average method was constructed through 100 iterations, with 33 percent holdback proportion on dataset to explore the best model which resulted in the most appropriate goodness-of-fit for almost 80 percent. A sensitivity analysis validates the significance of predictor trends.

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According to the 2021 ASCE infrastructure report card, 43% of the road network in the United States is in poor or mediocre condition. This would jeopardize road safety and increase crashes and fatalities that incur social and economic costs. Among the leading causes of vehicle crashes is insufficient pavement friction. Therefore, highway agencies usually monitor highway network to for pavement friction change to intervene when necessary. Pavement surface texture influences pavement friction characteristics, and is typically monitored at a network level using laser systems. However, these systems are expensive, require high technical knowledge to maintain and operate, and may be prone to data collection errors such as noise. Hence, texture measurements have been limited. With the emergence of image-based 3D reconstruction methods, known as photogrammetry, an effective network-level monitoring could be achieved. Photogrammetry relies on cost-efficient 2D images that could be captured using smartphones, DSLR cameras, or drones. To date, most of the high-resolution pavement texture using image-based methods has been limited to small-scale pavement sections. In this work, obtaining texture information at a network level is proposed, while addressing the aforementioned limitations. The challenges of photogrammetry such as scaling, georeferencing, 3D geometry inaccuracies, and automatic texture extraction and calculation will be discussed.

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New profiling systems overcome the ‘low speed problem’ with traditional inertial profilers, allowing valid profile and roughness (IRI) to be collected on all roads regardless of traffic conditions, signals, and stop signs. Research has found that ride quality is the single most important characteristic to road users. Learn how new technology allows DOT, county, and municipal agencies to be informed of end-user perception of the condition of every segment in the network.

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In Sweden road profiling surveys are conducted yearly on roughly 80 000 kilometres of road in combination with mobile mapping surveys. The surveys are performed with two different types of systems, where one of them has capabilities of mapping asphalt cracking. In this presentation a brief description of the survey program and the method of data collection will be given. The main topic is sharing the experiences of the analysis and reporting of cracking data from the four years the survey program has been running, along with findings from the yearly verification tests and procedures.
Within the survey contract development and testing has been performed on an extended analysis of the parameters ravelling and patching, with several tests performed on different types of asphalts and conditions. The findings of these tests are presented and discussed as a further insight on the possibilities of automated mapping of surface distresses.

A study was initiated by FAA to validate the CFME friction coefficient using the smart sensor technology. With the smart tire sensors, tire-pavement contact behavior, such as contact pressure distributions, as well as frictional and lateral forces, can be identified based on the combination of sensor measurements. By interpreting sensor measurements based on the developed sensor model and extracted sensor signal cycle, valid tire-pavement contact parameters (pavement friction coefficient) can be derived in field tests.

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Continuous tire-pavement friction and macrotexture have been established as key contributors to road safety. Research published by Virginia Polytechnic Institute and State University and Federal Highway Administration [Characterizing Road Safety Performance using Pavement Friction, Flintsch et al] verified a strong statistical relationship between higher friction and macrotexture and lower crash rates. The continuous tire-pavement friction and macrotexture in this research and previously published research used SCRIM® data collected in the left wheel path to establish these relationships. Thus, there is an open question as to whether the data being collected in the left wheel path is significantly different from the data collected in the right wheel path. This presentation compares continuous tire-pavement friction and macrotexture data collected in both the left and right wheel paths. To compare left and right wheel path data, WDM USA surveyed Kentucky Transportation Cabinet (KYTC)-maintained roads using the SCRIM®, collecting continuous tire-pavement friction, macrotexture, roughness, and road geometry features (e.g. direction of turn, curve radius, grade, cross-slope) data, summarized at 0.005-mile increments. Additional network features included in the analysis such as AADT and lane count were provided by KYTC. Comparisons of left and right wheel path data were performed in a variety of geometry and network settings, and analyzed using a combination of parametric, and non-parametric analyses, including standard normal distribution outlier detection, Mann-Whitney U tests, and ANOVA.

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To date, the use of traditional vehicle mounted inertial road profilers have a limited ability to measure longitudinal profile data for IRI calculations while traveling at both high and slow speeds, while braking and accelerating, while turning, and resuming from a stop. This presentation will cover testing and implementation of an All Speed Profiler capable of measuring and reporting IRI at all speeds (0 MPH -75+ MPH) and various driving habits. This system will be useful for measuring IRI found during normal driving patterns while traversing urban traffic conditions: braking, accelerating, turning, slow movement, periods of stopped traffic, periods of stop and go traffic, etc…
Test data collected with the All Speed Profiler has shown a high level of confidence when compared to data collected from a walking profiler, matching >94% accuracy and repeatability. Testing performed includes procedures outlined in the provisional AASHTO R56 “Standard Practice for Certification of Inertial Profiling Systems”, as well as a variety of simulated urban traffic driving conditions and habits. The Pathway Services Inc. All Speed Profiler system can be installed on a typical consumer host vehicle and can be operated in normal driving conditions on highways and roads, on all common asphalt and concrete pavement types.

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This presentation reviews standard methods of checking inertial profilers for measurement errors, including: the block test, the bounce test, repeatability testing, and comparison to a reference profile. The presentation demonstrates the effect of some common error types that have appeared in production profilers recently, such as signal loss, signal delay, sensor noise, and gain errors using sensor signals measured by the FHWA Urban and Low-Speed Profiler. The effect of these errors on the bounce test (IRI, look of the trace), IRI of measured profiles, and cross correlation are demonstrated. An example is provided that demonstrates the need to conduct repeatability testing at two measurement speeds to catch some types of errors. Testing at two speeds is recommended for control section measurements.

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The launch of the Illinois Department of Transportation’s ICART track presents a convenient and controlled environment for certifying inertial profiler systems, significantly shaping the advancement and refinement of industry standards. Beyond providing a dedicated space away from public roadways for testing, this track plays a vital role in driving the evolution of recognized norms within the transportation sector.

Recognizing the pivotal role of this facility, Mandli Communications extensively utilizes it for testing and certifying our 3D inertial profilers to adhere to AASHTO R 56 standards. This certification is imperative for meeting third-party certification requirements essential for adhering to state contract requirements. With multiple asphalt friction sections and a concrete lane, the ICART track allows for a comprehensive representation of road surfaces during certification processes. Certifications encompass assessments of repeatability of IRI, accuracy of the systems, block and bounce tests, and the confirmation of faulting values.

This abstract looks to highlight the critical importance of ICART’s facilities in ensuring compliance with stringent certification requirements, ultimately enabling vendors to meet state contract requirements while maintaining high standards of performance.
The comprehensive nature of certifications conducted on the ICART track demonstrates its role in accurately assessing the capabilities of inertial profiler systems, thereby contributing to safer and more efficient transportation infrastructure.

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This presentation addresses practical considerations that have arisen recently when using cross correlation at profiler round-ups and at profiler certification testing. Particular emphasis is given to the reduction in cross correlation scores caused by errors in longitudinal distance measurement. The presentation reviews the details of a procedure for accounting for longitudinal distance measurement errors during cross correlation analysis, which was used in profiler round-ups in 2004, 2009, 2010, 2013, and 2015. The presentation also addresses the effect of high-pass filtering on cross correlation, and the link between cross correlation level and expected agreement in IRI.

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Shot blasting is a preservation technique for asphalt pavements that is usually applied to restore texture and friction. The improvement in friction and texture characteristics achieved with blasting is directly associated with the surface mix and the type of aggregate. Although some researchers have evaluated the initial friction and texture improvements obtained after shotblasting a surface and have calculated the temporal variation of friction and texture after the treatment, most of these studies were conducted on accelerated test track facilities. Hence, this study examines the changes in friction and texture following the application of shotblasting to five different asphalt pavements. The primary aim is to assess both the immediate impact and the lasting effects of the treatment. To achieve this, the pavements selected were in good surface condition when the treatment was applied. The pavements were then divided into two sections: one treated with shot-blasting, and the other serving as a control section with no modifications. Friction and texture measurements were taken at various time points after construction in both sections, providing data to quantify the impact and duration of the shotblasting treatment. In terms of friction, the longevity of the shotblasting appears to be 1.2 years, and for texture, the longevity was closer to 3 years. However, in one of the sites surface texture components were affected by a deicing operation conducted 1 year after shotblasting, which may have influenced, especially in terms of friction, the observed trend in the second and third year. The results of this study will inform the use of shotblasting as a surface treatment to improve skid resistance.

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The advancement of pavement imaging technologies, such as 3D laser systems, has revolutionized pavement condition surveys, shifting from manual to automated evaluation methods. State Departments of Transportation (DOTs), including GDOT, TxDOT, and Caltrans, have amassed extensive pavement image collections over several years. These images are pivotal for monitoring pavement distress, such as crack propagation and deterioration, but their effective utilization is hindered by challenges in accurately aligning multi-temporal images in consistent regions. It is impossible and difficult to achieve accurate and reliable pavement deterioration analysis if the consistent regions among different years cannot be ensured. This study introduces a novel three-stage coarse-to-fine methodology for Multi-Temporal Pavement Image Registration (PIR). This methodology efficiently aligns pavement images from different time periods, enabling consistent monitoring and analysis of pavement deterioration. Tested on a dataset from US-80 spanning 11 years with varied cracking patterns, the methodology demonstrates high efficiency and accuracy in registering images across multiple years, offering adaptable accuracy levels for various applications. This innovative approach aids transportation engineers in analyzing pavement deterioration using historical images, supports the Long-Term Pavement Performance (LTPP) program, and contributes to the calibration of the Mechanistic Empirical Pavement Design Guide (MEPDG) models. This presentation illustrates 1) the framework of the developed multi-temporal pavement image registration methodology, 2) preliminary results of registered multi-temporal pavement images on US-80 across 11 years, and 3) potential applications of multi-temporal pavement image registration results for more accurate pavement deterioration analysis and optimized pavement treatment decision-making.

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Chip seal application is a common practice for maintenance and preservation of deteriorated pavements. Chip seal application is mainly used to seal the fine cracks on a pavement surface and to prevent water intrusion into the pavement foundation, thereby extending the life span of the existing pavement. Although quality assurance (QA) is critical, there is no well- established agreement on quantitative QA procedures for Chip seal treatment. One of the practices used by many State highway agencies is to estimate the percent embedment (PE) by pulling some of the chips after construction, which is relying on visual examine. However, this practice does not guarantee representative samples and lacks consistency and objectivity because there are no specifications on how to measure PE from retrieved aggregates. Therefore, this study investigates the use of several image-based and laser-based assessment procedures to estimate and quantify the percent embedment (PE) as a quality assurance tool for chip seals. The analysis procedures included side-view image analysis for measuring PE, surface texture evaluation and its correlation to PE values, and image-texture analysis of overhead surface measurements to estimate PE. The analysis showed that the correlations between the different PE estimation methods are relatively weak, indicating the various methods provide different information and may relate to different characteristics

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This presentation will discuss the role of the Transportation Research Board’s (TRB’s) Standing Committee on Pavement Surface Characteristics and Vehicle Interaction Properties, AKP50, in the surface characteristics world. It will contain a brief overview of what TRB is and what this specific committee does and how it can be mutually beneficial with RPUG and the greater RPUG community. It will cover committee functions, responsibilities of friends and members of the committee, and the committee’s role in the research identification, funding, work, dissemination of results and implementation processes. In addition, it will go over recent committee member rotation, development of the committee’s new three-year Triennial Strategic Plan (TSP) and the focus areas and topics it intends to help advance. It will also highlight the current Research Needs Statements (RNSs) the committee has developed and is advancing for NCHRP or other project funding.

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This presentation will focus on comparing the performance (repeatability and accuracy) of different road condition indices (PCI, PASER, PSCI) when used to summarize detailed distress data (IRI, cracking, rutting, etc.,) that was automatically extracted from 1mm resolution 3D LCMS scans.
Brief descriptions of the road condition indices (PCI, PASER, PSCI) will be presented. The method used to automate the condition calculations from the standard LCMS outputs will also be exposed in detail.
In order to compare the results of the different methods, three 200m road segments of low, medium and high roughness (IRI) values were scanned three times each. No care was taken to start and stop the scans at exactly the same places so as to allow a few meters of variance between the scans. Each 200m road segment was further divided into 10 meter sections. Each 10m road section was processed in order to automatically extract all of the road surface characteristics from the LCMS data. Finally the different indices were used to summarize the same road condition data for each road section of each of the three scans of each 200m road segment. In conclusion it will be shown that there are significant differences in the results depending on what classification method is used even if each method is evaluating the exact same surface defects. Some methods will also be shown to demonstrate high variance between the results from the multiple runs of the same road segments.

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Currently, several transportation agencies implement smoothness specifications that include incentives and disincentives for contractors. In most cases the values and ranges for these incentives and disincentives are based on experience and judgment. It is important that agencies validate the value of paying bonuses by addressing the following questions: (a) Are smooth pavements really extending the life of the pavement and, if so, by how much?, (b) Is it financially worth it?, (c) Are rough pavements decreasing the life of the pavement and, if so, by how much?, and finally, (d) Is the agency penalizing the contractor adequately or excessively?
The complete integration of full lifecycle management of pavements from as-designed to as-constructed to as-maintained and operated can provide valuable information that will improve decision making and efficiency.
This abstract will present some examples of valuable information being produced by surveys and construction technology today, and which can benefit any transportation agency.
(1) The total cost over the life of the asset; (2) Evaluate the impact of the initial International; (3)roughness Index or smoothness on the pavement performance. (4) Evaluate the impact of new specifications or test procedures used in construction projects. (5) Assess the impact of different construction techniques on pavement performance. (6) Compare the performance of the different pavement types and mix types. The list above provides some examples of valuable information that can improve decision making and lead to significant savings for the agencies.

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Improving the Quality of Highway Profile Measurement – Pooled Fund Meeting
This meeting is for its members and all others interested in this field.