RPUG 2018 Speakers’ Bios and Abstracts

  • Session 1.0: Welcome, Keynotes, TPF Updates & Vendors Introduction (Moderator) by Brian Schleppi, RPUG
    Bio:

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  • Session 1.1: Welcome from SDDOT by Dave Huft, SDDOT
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  • Session 1.2: Keynotes: History of RPUG/40 Years On The Road To Progressively Better Data by Brian Schleppi-Richard Wix, RPUG
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  • Session 1.3: TPF-5(354) Pooled Fund Updates by Dave Huft, SDDOT
    Bio:
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  • Session 1.4: TPF-5(299) 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), 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.
    Abstract:
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  • Session 1.5: TPF-5(345) Pavement Surface Properties Consortium by Kevin McGhee, VDOT
    Bio:
    Kevin has been with the Virginia Transportation Research Council since 1992. As Associate Research Director, he leads one of the premier research programs in the country, a program that includes the study of pavement materials and performance, design, construction quality management, recycling/reclaiming, and system preservation. As a researcher, Kevin led research on construction quality assurance, acceptance, and payment practices. He has also studied concrete pavement repair, application of advanced composites, bridge and pavement management, pavement preservation, and general traveled surface properties.

    Kevin has been privileged to know and work with many nationally and internationally recognized experts on traveled surface characteristics. Association with and service to this community has included six-year terms as chair for ASTM’s Committee E-17 on Vehicle-Pavement Interaction and the Transportation Research Board’s Committee on Surface Properties – Vehicle Interaction (AFD90).

    He received his bachelor’s degree from Virginia Tech and a master’s degree from the University of Virginia.

    Kevin attended his first RPUG 25 years ago this year – 1993 in Harrisburg, Pennsylvania.
    Abstract:
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  • Session 2.0: Network Pavement Surface Measurements under the FAST Act (Moderator) by Luis Rodriguez, FHWA
    Bio:

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  • Session 2.1: Introduction to FHWA DQMP by Luis Rodriguez, FHWA
    Bio:
    Luis is a Senior Pavement and Materials Engineer with the FHWA Resource Center – Pavement & Materials Technical Service Team. He provides technical assistant in the areas of pavement management, pavement preservation, life cycle cost analysis, and transportation asset management. He has been with FHWA since 1985. He is a registered Professional Engineer in the State of Georgia.
    Abstract:
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  • Session 2.2: CTDOT’s Experiences on DQMP by John Henault, CTDOT
    Bio:
    John currently supervises the Pavement Management Unit at the Connecticut Department of Transportation and has worked for the Department for 24 years. In addition to his current responsibilities, he has new roles and responsibilities associated with the implementation of the Data Quality Management Plan.
    Abstract:
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  • Session 2.3: SDDOT’s Experiences on DQMP by Ken Marks, SDDOT
    Bio:
    Kenneth E. Marks, Engineering Supervisor for SDDOT
    Currently supervises and does engineering analysis for the traffic monitoring, pavement condition, and state highway system inventory activities. The pavement condition activity also includes falling weight deflectometer testing and pavement condition activity which includes the pavement profiler operation for identifying pavement distresses of pavements, pavement roughness, extent of pavement rutting and faulting, and highway videolog.
    Years with SDDOT: 31 years
    Abstract:
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  • Session 2.4: RPUG survey results on DQMP by Luis Rodriguez, FHWA
    Bio:
    Luis is a Senior Pavement and Materials Engineer with the FHWA Resource Center – Pavement & Materials Technical Service Team. He provides technical assistant in the areas of pavement management, pavement preservation, life cycle cost analysis, and transportation asset management. He has been with FHWA since 1985. He is a registered Professional Engineer in the State of Georgia.
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  • Session 2.5: Qs-&-As by Luis Rodriguez, FHWA
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  • Session 3.0: Texture and Friction (I) (Moderator) by James Greene, FDOT
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  • Session 3.1: Exploring Pavement Texture and Surface Friction Using Soft Computing Techniques by Guanghui Yang, OSU
    Bio:
    Dr. Gary (Guangwei) Yang is a post-doctoral research fellow at the Oklahoma State University. Ha has published 12 research papers in peer reviewed journals as lead-author or co-author. He has about 10 years of experience in transportation engineering including railway, highway, and airport. His research interests include pavement management, pavement condition evaluation, big data analysis in transportation, and soil-structure interaction. He has contributed in several research projects focus on pavement surface characteristics evaluation using the 3D laser imaging technology supported by the ODOT or FHWA.
    Abstract:
    Accurate evaluation of pavement friction promises significant safety benefits to highway agencies. It is long desired to develop friction prediction models using pavement surface and aggregate textural properties.
    In this study, forty-five pavement sites, constructed using six common types of preventive maintenance (PM) treatments and eight typical sources of aggregates in Oklahoma, are selected as the field test beds. The state-of-the-art 3D laser imaging technology, high speed texture profiler, and Grip Tester, are used in parallel in the field to collect 1-mm 3D surface data, macro-texture profiles and pavement friction data respectively, while the portable ultra-high resolution 3D texture scanner is utilized in the laboratory to acquire both macro- and micro-texture characteristics before and after the Micro-Deval polishing process.
    Thirty-one 3D aggregate parameters in four categories (textural, feature, height, and material ratio & volume parameters) are investigated to characterize the texture attributes of aggregates, while mean profile depth (MPD) values are calculated for pavement surfaces. Multivariate analysis is performed to examine the most influencing factors for pavement skid resistance. Eight texture parameters have showed statistical significance on pavement friction.
    Secondly, a novel Deep Residual Network tailored for pavement friction prediction, named Friction-ResNets, is developed using pavement surface texture profiles as the inputs. 33,600 pairs of friction and their corresponding texture profiles are collected and prepared from 49 High Friction Surface Treatment (HFST) sites and their abutting sections in 12 states. Friction-ResNet consists of eleven convolution layers, one average pooling layer, and one fully-connected layer. The testing results show that Friction-ResNets can achieve a classification accuracy of 91.3%, outperforming commonly used machine learning methods.
    This study could assist in selecting the most effective PM treatments, and proper aggregates with desired texture for optimized skid resistance. It also demonstrates the feasibility of replacing the contact based friction evaluation method with non-contact texture measurements.

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  • Session 3.2: Aggregate Micro-texture Analysis based on Morphometric Parameters by Sareh Kouchaki (Yaxiong Robin Huang), UT Austin
    Bio:
    Dr. Robin Huang is the owner of HyMIT LLC for pavement sensor technology development and manufacture, and a research fellow at the Center for Transportation Research, the University of Texas at Austin. He has accomplished numerous projects for pavement condition data collection. From 2006 to 2017, he had worked for TxDOT to develop 2D and 3D imaging systems for automated rutting and distress inspection. He also led high-resolution 3D system development for surface texture, faulting, and aggregate feature measurement. He currently is researching new technologies for road profiler, high speed deflection measurement, and 3D chip seal quality inspection.
    Abstract:
    Poor skid resistance of pavement surface is a major contributing factor in roadway accidents. The skid resistance of pavement is closely related to the micro-texture of pavement surface which is set by micro-texture of aggregates used in pavement. Aggregates with rough micro-texture provide greater surface area between the tire and the pavement, hence improving the magnitude of the adhesion component of frictional force. Given the high amount of aggregate used in pavement mixtures and the link between the aggregate micro-texture with skid resistance, it is of great importance the aggregate texture properties to be studied. Several methods have been developed for quantifying the aggregate micro-texture. Recent advances in computer and sensing technologies are motivating new developments in aggregate texture characterization. From geometric point of view, the aggregate micro-texture can be differentiated by the density and sharpness of summits on the surface of aggregates particles. In this study, a new approach for detection of aggregate micro-texture summits is described. A high resolution optical microscope was used to acquire the surface morphology of different aggregate particles. Based on the conducted measurements, a three-dimensional digital surface model was generated, and a filtration approach was applied to separate the surface texture into two ranges: micro-texture and macro-texture. Initially, the surface micro-texture of aggregates was investigated based on commonly used texture characteristics; arithmetic mean height and root mean square. Then, the applicability of the new approach utilizing morphometric feature integration was practiced by quantifying the density of summits and their sharpness. Finally, the results of the developed aggregate morphometric parameters were assessed to show their consistency with other evaluated texture parameters.

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  • Session 3.3: Improved Resolution Skid Testing by John Andrews, MD SHA
    Bio:
    John graduated from the Johns Hopkins University with a Physics degree and a minor in Electrical Engineering. He spent most of his working life designing, manufacturing, or managing activities in the fields of instrumentation, automated machinery, and heavy machinery. For semi-retirement, 19 years ago he changed direction again and joined the Maryland State Highway Administration with responsibility for the collection of highway condition data. His section has two multi-parameter survey vehicles, two skid testing units, an inertial profilers, two FWD’s with GPR, and a coring rig to deploy for this purpose. More recently, he has taken responsibility for bridge deck inspection as well.

    He has also been a member of several national groups involved in improving the quality of highway data collection, the equipment utilized, and the development of related AASHTO standards.
    Abstract:
    Traditionally the SKID TEST has been performed using a protocol specified in ASTM -E-274. This specifies a test that takes approximately 2.5 seconds to complete which at 40 MPH requires roughly 150 feet to complete and consumes over 40 gal. of water. (and considerable tire rubber).
    Several years ago, a NON-LOCK skid test was proposed that consumed considerably less resources and could be performed much more rapidly therefore providing better resolution. While this test performed quite well and had excellent general correlation with the traditional test (R2 above .99), The test-test correlation was not as tight because it is a different test. This raised some concern amongst our pavement managers.
    As a result, we have adopted an interim test that locks the wheel, but only for 0.5 seconds counting stabilization time instead of the 1.2 to 1.4 seconds typically required for the ASTM-274 test.
    Applying this new test has given some new data on critical areas such as ramps and curves that was missed by past protocols.
    This presentation will cover the process to get where we are in Maryland, test specifics, and an early examination of selected first year data.

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  • Session 3.4: Using High Speed Macrotexture Profilers for Friction Modeling by Ahmad Alhasan, ISU
    Bio:
    Dr. Alhasan is an Associate research Scientist and adjunct assistant professor at the institute for transportation at Iowa State University. His research focuses on utilizing modern technologies; which includes laser profilers, remote sensing technologies, and intelligent compaction; and developing analysis tools to better model the uncertain reality. Moreover, Ahmad is developing new frameworks to design, control, and manage transportations assets under these uncertainties, using a probabilistic based approach.
    Abstract:
    Pavement frictional behavior impacts pavement performance in terms of vehicle safety, fuel consumption, and tire wear. Measuring pavement friction using a physical testing system can be challenging and is prone to variability due to the testing conditions and testing devices. In an effort to harmonize the skid resistance measurements, researchers and agencies have developed several calibration methods to devise a universal international friction index, which allows comparisons between different friction measurement methods and devices. Despite the efforts to describe and quantify the impact of varying conditions on pavement friction, which ultimately will allow for a better harmonization of friction measurements, there is a need to better understand the link between the surface texture and physical friction measurements. In this study, we will present an effort that utilizes the data acquired using a high-speed macrotexture profiler to derive sufficient texture characteristics which can be used for friction modeling. One simple texture statistic that can be used to characterize fractal surfaces’ power spectral density, which includes pavement surfaces, is the Hurst exponent. Four profiles were acquired on two asphalt concrete (AC) surfaces and two Portland cement concrete (PCC) surfaces. For each pavement section, thirty high resolution stationary scans were acquired to capture the macrotexture and parts of the microtexture. Using the data (i.e., high-speed macrotexture and high resolution scans) acquired on two sections, one AC surface and one PCC surface, mathematical active high pass filters were designed for the high-speed macrotexture profiles. The active high pass filters attenuate low frequencies as needed, and amplify the high frequency filter using a non-unity gain. The filters were tuned by maximizing the match between the Hurst exponent distributions from both data sources on each section. The designed filters were then used to validate the findings using the other two sections included in the study.
  • Session 4.0: PSC Topics (I) (Moderator) by Bob Orthemeyer, FHWA
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  • Session 4.1: 3D Moving Reference Method for Full Speed Road Profiler by Yaxiong Robin Huang, HyMIT LLC
    Bio:
    Dr. Robin Huang is the owner of HyMIT LLC for pavement sensor technology development and manufacture, and a research fellow at the Center for Transportation Research, the University of Texas at Austin. He has accomplished numerous projects for pavement condition data collection. From 2006 to 2017, he had worked for TxDOT to develop 2D and 3D imaging systems for automated rutting and distress inspection. He also led high-resolution 3D system development for surface texture, faulting, and aggregate feature measurement. He currently is researching new technologies for road profiler, high speed deflection measurement, and 3D chip seal quality inspection.
    Abstract:
    The inertial type road profiler is widely used around the world. However, the nature of inertial reference method makes such a profiler travel speed sensitive. For this reason, an inertial profiler is required to run at stable speed and is invalid at low speed and stop-and-go data collections. In over a decade, the industry has been looking for a road profiler which can provide speed independent results. A moving reference profiler uses a high-resolution line laser sensor and a special designed alignment algorithm. The sensor takes an 18-inch long, 2K data point micro surface profile segment in a single sample along the travel direction. When triggered in a desired arrangement in which the lagging sample profile largely overlaps with the leading one, the previous captured profile segment can be used as a reference to the lagging profile. The alignment algorithm compares two consecutive sample profiles and calculates vehicle motions. In this way, vehicle motion can be removed from sample data and true surface profile segment can be added along the survey path. In particular, a high power laser line sensor has been developed to further solve the problem caused by motion blurring at high speed. This sensor can sample quality data from different pavement surfaces with several microseconds exposure time. Field tests shows this profiler can provides repeatable IRI, texture MPD, and faulting data in a full speed range from 0 to 70 mph.
  • Session 4.2: Field Experiment for Accuracy Verification of Pavement Inspection in TRUE Project by Kazuya Tomiyama, Kitami Institute of Technology, Japan
    Bio:
    Dr. Kazuya Tomiyama is an associate professor of Kitami Institute of Technology, Japan. He received B.S. and M.S. degrees in civil engineering from Kitami Institute of Technology, Japan, in 2005 and 2007, respectively. He received a Doctor of Engineering from Kitami Institute of Technology, Japan, in 2010. He is a regular member of Japan Society of Civil Engineers and a member of International Committee on Pavement Technology (ICPT). His research interests include pavement surface properties and vehicle Interaction, road surface informatics, and psychological-physiology for road infrastructure evaluation.
    Abstract:
    The Road Bureau of Ministry of Land, Infrastructure, Transport and Tourism (MLIT), Japan issued a general guide for pavement inspection in 2016. The guide provides the standard procedures for inspection, diagnosis, treatment, and data recording during the service period of a pavement. In the procedure, the International Roughness Index (IRI) has been introduced as the index of surface roughness instead of the traditional standard deviation of profile elevation obtained with a profilograph. Accordingly, a lot of devices measuring IRI has been developed recently in Japan and has been applied in response to inspection purposes. As a result, the consistency of each measurement obtained with different devices on the same road surface has become a practical concern for providing a standard measure of roughness. In the light of this background, the specified non-profit organization Pavement Diagnosis Researchers Group (PDRG) in Japan has undertaken a project regarding the experiment to harmonize and compare Test methods for surface Roughness Under actual road Environment (TRUE Project) since 2014. The TRUE Project has so far conducted the experiments twice at Hokkaido, Japan in September 2014 and September 2016. Thirty-four devices participated in the first experiment and twenty-eight devices in the second, including high- and low- speed devices. The reference profiles were accurately measured by the same manner for both experiments by using hand-operated profiling devices. In this presentation, the overview of the inspection procedures introduced in Japan and the results of the first and second experiments of the TRUE Project are reported with a brief introduction of the activities of PDRG.
  • Session 4.3: Pavement Friction Management Support Program by Edgar de León Izeppi, Virginia Tech
    Bio:
    Dr. Edgar de León Izeppi: has worked in the areas of pavement management and transportation engineering for over 30 years. He is currently a Research Scientist at the Center for Sustainable Transportation Infrastructure at the Virginia Tech Transportation Institute (VTTI) working for the Pavement Surface Properties Consortium and other multidisciplinary research projects that address end-result and performance oriented specifications. He has performed extensive data collection for pavement structural and functional performance, as well as pavement life cycle cost analysis, pavement design and geometric design. He is also engaged in the FHWA Pavement Friction Management (PFM) Support Program, the Guidance to Predict and Mitigate Dynamic Hydroplaning on Roadways, and the Protocol for Network-Level Macrotexture Measurement.
    Abstract:
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  • Session 4.4: Guidance to Predict and Mitigate Hydroplaning NCHRP 15-55 by Gerardo Flintsch, Virginia Tech
    Bio:
    Gerardo Flintsch is a professor with the Via Department of Civil and Environmental Engineering at Virginia Tech where he directs the Center for Sustainable Transportation Infrastructure of the Virginia Tech Transportation Institute. He currently serves as chair of the TRB standing committee on General and Emerging Pavement Design and as associate editor of the International Journal of Pavement Engineering. Flintsch is also the vice-president and technical director of FM Consultants and provides consulting services for international organizations, private companies and government organizations.

    Abstract:
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  • Session : RPUG Business Meeting by Brian Schleppi, RPUG
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  • Session 5.0: 3D and Condition Survey (Moderator) by Andy Mergenmeier, FHWA
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  • Session 5.1: Hardware And Software Improvements Using 1mm X 1mm Resolution 3D Road Surface Data by John Laurent, Pavemetrics
    Bio:
    He is a co-founder of Pavemetrics Systems inc. For the past 25+ years he worked at and with the National Optics Institute of Canada (INO) on developing 3D and laser imaging technologies that are now being used by 250+ government institutions and data collection companies around the world for the inspection of roads, rails, tunnels and airports. He is also the author of several papers and patents on the subject of using lasers, optics and image processing for inspection of transportation infrastructures.

    Abstract:
    The new LCMS-2 allows for a five times increase in the speed of acquisition of 3D transverse road profiles and an increase in the vertical resolution of the sensors. The increased performance of these sensors show improved results for crack detection. We will demonstrate the difference in crack detection results of the LCMS-2 versus the LCMS-1. Also we will present the detection results for new features such as rumble strip detection and the detection of man-holes and gutters found on municipal and urban roads.

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  • Session 5.2: Next-Gen High-Speed 3D Sensors and Cognition Based Intelligent Solutions for Condition and Safety Surveys: Status and Direction by Kelvin Wang, OSU
    Bio:
    NA
    Abstract:
    Many pavement data collection equipment devices are already high-speed and non-contact. However, contact based sensors such as deflection and friction devices are still commonly used. In addition, there remain many technical challenges for fully automated distress survey, specifically cracking survey, and for non-contact safety measurement devices that present needed performance characteristics to replace traditional contact-based sensors. This presentation discusses on-going research on two critical issues facing the pavement industry today: truly full automation for cracking survey with production-worthy precision and bias levels, and development and validation of safety measurement devices that are non-contact, high-speed, and without needing water with consistent, and repeatable results.

    The first portion of the presentation focuses on the progress of the three-year old work based on Deep-Learning solutions for fully automated cracking survey. The second part illustrates a non-contact, 0.1mm 3D resolution sensor design that potentially can replace contact-and water-based friction devices.

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  • Session 5.3: Is that what I ordered? by Richard Wix, ARRB
    Bio:
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    Abstract:
    Ensuring the quality of data collected by automated pavement monitoring equipment meets user expectations is critical given the decisions that will be made using that data. For instance, a road agency may use the data to determine its works program or allocate its maintenance budget.
    The sheer volume of data produced by networks survey vehicles today, which typically have several systems integrated into a single survey platform, makes data quality checking an even more challenging task.
    This presentation investigates what steps can be taken, even before data collection begins, to ensure data quality and describes some tools and techniques that are available to assist vendors and service providers.

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  • Session 5.4: High Resolution Multi-Lane Road Surface Mapping Using 3d Laser Profilers For 3D Paving And Milling Projects by John Laurent, Pavemetrics
    Bio:
    He is a co-founder of Pavemetrics Systems inc. For the past 25+ years he worked at and with the National Optics Institute of Canada (INO) on developing 3D and laser imaging technologies that are now being used by 250+ government institutions and data collection companies around the world for the inspection of roads, rails, tunnels and airports. He is also the author of several papers and patents on the subject of using lasers, optics and image processing for inspection of transportation infrastructures.

    Abstract:
    DOTs require annual inspections of their roads and infrastructures in order to plan maintenance operations. Road surface defects (texture, cracks, rutting, IRI – smoothness) are important data that need to be measured and serve as input data to PMS (Pavement Management Systems) software. These defects are likely measured using 3D laser sensors that acquire the shape of the road surface in order to evaluate its condition. Once it is determined that the road condition has degraded to the point that it needs to be rehabilitated and resurfaced then a high precision survey of its surface is can be required by the engineers as an input to 3D CAD road design software that can then be output to control 3D pavers and millers using laser tracking total stations.

    What we propose is a way to reuse the 3D road surface condition data to create the road surface model so as to avoid having to do expensive manual road surface surveys that require road closures.
    This article proposes a totally new approach that provides a way to tag collected high resolution high accuracy transverse road profile data acquired by a LCMS system (Laser Crack Measuring System – Pavemetrics) combined with a highly accurate GNSS-INS system (Applanix POS-LV – Trimble) to measure both road surface condition and to generate a survey grade accuracy terrain map of any road surface.

    This presentation will describe how the information provided by the 3D LCMS system, DMI, Applanix POS-LV, GPS with local RTK corrections and post processing (POSPac-Trimble) software are used to generate the road surface models. The accuracy of the models created were evaluated comparing them to surveyed control points and determining the repeatability measurements of multiple runs.

    Results will show that using this method it is possible to generate much higher resolution survey grade road surface models that can be used for resurfacing applications using 3D paving and milling equipment from the original 3D data that was used to evaluate the actual condition of the road surface itself. This process results in significant productivity improvements, optimization of the quantity of material that needs to be carried in and out, lower survey costs, decreased traffic interruptions and improved safety of surveyors while improving the quality and resolution of the road surface models.

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  • Session 6.0: Texture and Friction (II) (Moderator) by Kevin McGhee, VDOT
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  • Session 6.1: Tire Pavement Interaction Noise and Correlation with Pavement Texture Parameters by Ricardo Burdisso, Virginia Tech
    Bio:
    Dr. Burdisso is currently a tenured professor in the Department of Mechanical Engineering at Virginia Tech. He has been involved in the research of passive and active sound and vibration control and structural acoustics since 1981. Dr. Burdisso has published 70 scientific papers in major peer-reviewed journals and authored/co-authored more than 130 technical articles in numerous international and national conferences. During his over 25 years of academic experience, Dr. Burdisso has been invited to be technical session organizers and chairs for many international and national conferences in sound and vibration field, including the First International Conference on Recent Advances in Active Control of Sound and Vibration (1991), International Gas Turbine Institute ASME TURBO EXPO (2002), and others. Dr. Burdisso has led 50 projects and research programs on noise control of turbo machinery, vibration isolators, microphone phased array measurements of aerodynamic noise, response of structures to sonic booms, and more recently in the design of quiet fans.

    Abstract:
    Tire Pavement Interaction Noise (TPIN) is one of the main contributors to community noise pollution, especially in areas surrounding highly transited roads. To gain insight into TPIN, noise was collected for 43 tires with different treads and sizes, at multiple speeds, and on 27 types of pavements at the Virginia Tech SMART Road and US 460 road. The noise was recorded using an On Board Sound Intensity (OBSI) system. Compared to the conventional OBSI system, an optical sensor was added to the system to provide a once per revolution signal. Using the optical signal, the TPIN was separated into two components denoted as Tread-Pattern (TPN) and Non-Tread Pattern (NTPN) noise. TPN is related to the tread pattern geometry of the tire and is extracted from the noise data using the optical signal and order tracking analysis. The NTPN component depends on the tire material properties, tire size, and pavement texture. To correlate NTPN to the pavement texture, the profile for the pavements at the SMART and US 460 roads were measured using a scanning laser mounted on a Sideway-Force Coefficient Routine Investigation Machine (SCRIM). Noise and pavement profile spectral contents were correlated by computing the amplitude of their transfer function. Results show that the TPN is the same for a tire on different pavements while the NTPN is the same for different tires (same size) on the same pavement. NTPN is dominant in the 400-1600 Hz frequency range, independently of the pavement and its spectral shape is independent of vehicle speed. As expected, the presence of transversal grooves in the pavement surface is responsible for tonal content in the TPIN spectrum. Finally, the noise in a porous pavement showed significant reduction in levels and change in spectral content, i.e. shift towards lower frequencies of the dominant part of the spectrum.

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  • Session 6.2: Multi-length scale Modeling of Dry/ Wet Traction by Saied Teheri (Ricardo Burdisso), Virginia Tech
    Bio:
    NA
    Abstract:
    Because of its influence on vehicle mobility, handling, safety, and stability, tire is an important component of the vehicle. As such, understanding and developing models of the tire-road contact friction on dry and wet surfaces has been an important topic of research for decades. Although the dry surface contact friction has been studied and is relatively understood, wet friction is still not understood very well. Friction coefficient occurring at the contact interface is an important parameter required for the estimation of tire traction.
    The present work focuses on estimating the tractive effort at the tire – road contact interface, under dry and wet conditions by considering friction physics at lower scales. Two approaches have been considered, (1) an analytical approach using Hierarchical multiscale modeling, where the approach is broken down into three scales: macro (full tire), meso (tread block element) and micro (Surface roughness scale) and (2) FE (Finite Element) model. For the analytical approach, the frictional losses based on the different mechanism occurring at the micro scale is transferred to the meso scale where the frictional stresses are combined over all roughness length scale to obtain an effective friction coefficient. The friction coefficient thus obtained, for the specific boundary condition can be used in the macro scale to estimate the tractive effort. In case of the finite element approach, a multi-length scale thermo-mechanical tire pavement model is developed to estimate the wet/ dry traction of the tire. The hysteresis frictional losses at the contact interface is obtained considering a rubber block sliding over a rough pavement. The friction coefficient obtained from the rubber block simulation will then be used as an input for the full tire model to estimate the tractive effort. In addition, for the case of wet traction, fluid has been modeled at the contact interface using the ABAQUS CEL approach.
    To validate the models, the dynamic friction/wear tester and the ground robot sliding friction mechanism, developed by CenTiRe, will be used with a rotating rubber sample and a sliding rubber block, respectively. The traction forces obtained from the macro scale is validated using tire traction data that will be obtained using the tire-testing trailer developed by CenTiRe.

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  • Session 6.3: Where Does “Safety” Fit in Pavement Evaluation by Jerry Daleiden, ARRB Group
    Bio:
    Jerry has been involved in the design and research of pavements and their performance for almost 35 years. He has been responsible for the evaluation and/or design of numerous pavement projects around the world. These analyses range from projections of remaining life to design of rehabilitation alternatives to federally sponsored projects using various innovative technologies for pavement evaluation.

    Early in his career, Jerry was employed by the Texas State Department of Highways and Public Transportation, in the Highway Design Division, Pavement Design Section. He was responsible for assisting engineers in the district offices with questions pertaining to pave¬ments; their design, evaluation and rehabilitation.

    Most importantly, he has been happily married for 35 years and the proud parent of 6, with 8 grandchildren.
    Abstract:
    Technologies continue to advance for assisting with the evaluation of transportation infrastructure. One area in particular that has come under greater scrutiny is that of safety assessment. The transportation industry has conducted friction testing for decades, with many agencies historically using the locked-wheel trailers for this purpose. The concept represented the typical vehicular response to sudden braking before the widespread implementation of anti-lock braking systems (ABSs). In addition to these “locked wheel” devices not accurately representing today’s vehicles, they also provide a single average reading of friction over a long distance. This can result in inaccurate assessment of specific segments, such as: intersections, ramps and/or sharp curves.

    With the increased collection of surface texture data, agencies have attempted to study if texture data could somehow be correlated to a meaningful safety statistic. These studies have proven inconclusive, which might not be that surprising recognizing the challenges with historical testing noted above. With so many advances in technology however, safety appears to be one of the areas where we may be the furthest behind in our evaluations.

    Continuous friction measurement could serve to improve evaluations of safety and relationships to the other associated data collected. Continuous friction measurement operates under conditions similar to those of most currently equipped ABS vehicles. These devices can measure friction continuously around the critical slip ratio of a vehicle with ABS at highway speed across the entire length of a road.
    This presentation will explore the potential for more comprehensive pavement assessments. By combining continuous friction measurement with transverse and longitudinal profile, texture and image data collection the opportunity exists to gain a clearer understanding of the interaction of these critical performance metrics as well as the safety of our transportation infrastructure.

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  • Session 6.4: Mitigating Sand Patch Test Variability Using Laser Technology by Yorguo El Hachem (Feng Hong), UT Austin
    Bio:
    NA
    Abstract:
    The sand patch test is one of the most widespread pavement texture identification techniques used by highway agencies to characterize texture and evaluate friction in the aim of monitoring and improving road safety. The most effective key parameter of the sand patch test is the measured diameter because it reflects the intensity of the available texture. However, many factors lying within the sand patch test method affect the variability of the results including the site surface, the operator, and the replicates within a section. In this study, a field experiment was conducted to evaluate the factors leading to the diameter variability of the sand patch test whereby different pavement surfaces were evaluated by several operators with distinct trials per operator. An ANOVA was executed in order to evaluate the effect each experimental factor has on the measured diameter of the sand patch test. The findings indicate that the main contributor to diameter variability, apart from evidently changing the surface, is the operator conducting the sand patch test and inherently the variability of texture within the surface itself. Accordingly, the operator variability was assessed separately in a closed frame experiment while limiting the variance generated by other experimental factors. For this reason, 3D laser measurements were taken coinciding with sand patch tests to demonstrate the operators’ inconsistency and attempt to eliminate it. It is recommended to incorporate the Light Amplification by Stimulated Emission of Radiation (i.e. Laser) technology, such as the line laser scanner, to provide a precise measurement of the available surface texture and limit the biases inherent to the testing methodology.
  • Session 6.5: Developing Analytical Filters to Characterize the Impact of Curling and Warping on Ride Quality by Ahmad Alhasan, ISU
    Bio:
    Dr. Alhasan is an Associate research Scientist and adjunct assistant professor at the institute for transportation at Iowa State University. His research focuses on utilizing modern technologies; which includes laser profilers, remote sensing technologies, and intelligent compaction; and developing analysis tools to better model the uncertain reality. Moreover, Ahmad is developing new frameworks to design, control, and manage transportations assets under these uncertainties, using a probabilistic based approach.
    Abstract:
    Pavement ride quality impacts the road user experience, user cost, fuel consumption, and long term pavement performance. Previous studies have shown that curling and warping behavior could affect ride quality on jointed plain concrete pavements (JPCP). Curling and warping are environmental loads that induce slab curvature due to temperature and moisture variations across pavement depth. Slab curvature can be further magnified under repeated traffic loads and can ultimately lead to fatigue failures, including top-down and bottom-up transverse, longitudinal, and corner cracking. Previous studies have shown that Westergaard equations can accurately model the curling behavior. This study introduces a closed form solution of the Westergaard curling equation in the frequency domain. This transformation to the frequency domain allows for accurate assessment of the impact of curling on ride quality under various conditions. The developed analysis is implemented on three inertial profiles acquired for JPCP slabs. Moreover, the analytical solution in the frequency domain will be used to derive a ride quality filter for curling and warping impact. The filter can be used to extract the curling and warping trends from inertial profiles and asses their impact on ride quality more efficiently compared to processing in the original spatial domain.
  • Session 7.0: PSC Topics (II) (Moderator) by Chad Shive, KYTC
    Bio:

    Abstract:

  • Session 7.1: Evaluating Transverse Profile Measurements Using the Cross-Correlation Technique by Rohan Perera, SME
    Bio:
    Dr. Perera is a Senior Consultant with SME in Michigan. He has been working in the pavements field for over 25 years, and has worked on numerous research project dealing with pavement smoothness and roughness progression on pavements.
    Abstract:
    The Federal Highway Administration (FHWA) has purchased four Transverse Profile Measuring Systems (TPMS) from Ames Engineering. A TPMS has been installed on each of the four Ames Engineering High-Speed Survey Vehicles that currently collect profile and macrotexture data for the Long-Term Pavement Performance (LTPP) program. An evaluation was performed to assess the repeatability and the accuracy of the TPMS system. The reference transverse profile data for evaluating the accuracy of the TPMS was collected using a beam type device that was equipped with an accurate distance measurement instrument to measure transverse profile location and a high definition laser height measurement sensor. The repeatability of the transverse profile data collected by each device was evaluated using the cross-correlation method that is available in the Profiler Certification Module in the ProVAL software. The Repeatability Option in the Profiler Certification Module of the ProVAL software was used without any filtering performed on the data to evaluate the repeatability of transverse profile measurements. The ProVAL software also provided a convenient way to plot and compare transverse profile data sets. The accuracy of the transverse profile data was evaluated using the Accuracy Option in the Profiler Certification Module in ProVAL. The reference data and the transverse profile data collected by the TPMS were loaded into ProVAL and an Accuracy Cross-Correlation was computed without any filters applied to the data using the Profiler Certification Module in ProVAl.This presentation demonstrates how repeatability and accuracy of transverse profile data can be evaluated by using the cross-correlation technique that is utilized in the Profiler Certification Module in ProVAL.

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  • Session 7.2: I-96 Case Study: Jointed Concrete Pavement Curling and Warp Presented in the Context of Pavement Asset Management System Data Analysis by Chris Byrum, SME
    Bio:
    Chris is geotechnical engineer specializing in soil-structure interaction analyses for bridge foundations, retaining walls, and pavements. He has been studying the warping and curling of jointed concrete pavements, and has been a Road Profile User since the early 1990s when He worked at the Michigan Department of Transportation. He has been with SME in Michigan since 1995. In the late 1990s He developed a method for quantifying pavement slab curvature using pavement surface profiles and applied the procedure to the FHWA LTPP GPS3 and GPS4 jointed concrete pavement profiles. This presentation will demonstrate His current procedure for detailed analysis of warp and curl using pavement surface profiles
    Abstract:
    This presentation describes a case study of jointed concrete pavement faulting, slab curling and warp
    performed on a 9,000-ft long interstate freeway test section, using data from a rapid travel non-contact
    inertial type roadway surface elevation profiler. The study presents the slab curvature and other profile
    index data for the long test section in the context of pavement asset management systems and using a 500-
    ft interval summary reporting basis. The test site was part of a previous MiDOT research study on causes
    of premature mid-panel transverse cracking. Pavement slabs at the site have a high magnitude of lockedin
    upward warp and the main truck lane has significant premature distress. For this study, thirty surface
    elevation profiles were obtained from the test section between 5AM and 1PM on a calm sunny day that
    experienced over 20 degrees Fahrenheit air temperature change during testing. A precise measurement
    and calculation of the change in slab shape (curling curvature) versus time of day is developed and
    matches closely with air temperature variation data obtained from a weather station near the test site. The
    slab curvature analysis procedure is described and consists of statistical analysis of variation of curvature
    for 3-point arcs between lengths of 1-ft and 8-ft obtained from profile elevation points within continuous
    slab segments in the profiles. The range of apparent locked-in warp curvature, the variation of warping
    magnitude along the length of the roadway and various other profile statistics are presented. The slab
    curvature changes caused by curling are compared to changes in International Roughness Index, IRI
    values for the test site showing a strong relation. The overall slab curvature trend measured at the test site
    is compared to an existing National database of slab curvature versus time of day measurements from
    outdoor jointed concrete pavement test sections across the USA.

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  • Session 7.3: Cracking Definitions through Consensus for the Future by Kelvin Wang, OSU
    Bio:
    NA
    Abstract:
    Various pavement cracking protocols are in existence such as the ASTM PCI definitions, LTPP distresses, recent AASHTO protocols, individual practices at many SHAs, and others. It is increasingly apparent to suppliers and users that a new set of cracking definitions are needed so that SHAs and national agencies such as FHWA can apply objective and comparable definitions for pavement engineering practices, and at the same time to accommodate the needs of implementing fully automated processing for cracking.

    The presentation illustrates initial work progress on NCHRP 01-57A including cracking protocol reviews as used at SHAs, and survey results of nearly 40 SHAs’ definitions related to their cracking data collection and processing. The presentation will also provide a recommendation of a set of cracking definitions that can meet the demands of pavement management and design, and also national requirements such as HPMS and performance measures rulemaking.

    Specifically, the study has the following objectives:
    • Develop standard, discrete definitions for common cracking types in flexible, rigid, and composite pavements
    • Reposition the roles of service providers and of SHAs for objective cracking measurements and continuing technological innovations by researchers and vendors
    • Facilitate comparable measurement and interpretation of pavement cracking
    • Have sufficient details to meet requirements for developing automated cracking software, for being compatible with existing and emerging image-based technologies
    • Develop primarily for network level surveys and help application of new technologies at the project level.

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  • Session 7.4: Protocols for Network Level Macrotexture NCHRP 10-98 (not permitted to be posted) by Vincent Bongioanni, Virginia Tech
    Bio:
    Major Vincent Bongioanni is an active duty Air Force Officer on assignment to Virginia Tech, as a Ph.D candidate in Civil Engineering. He received his Bachelor’s degree in Civil Engineering from the United States Air Force Academy and a Master of Science in Civil Engineering degree from the University of California, Berkley with a concentration in geotechnical engineering. He has served multiple tours of duty worldwide in support of Operation Enduring Freedom and as an Airfield Pavement Evaluation Team Chief. Most recently, he served as an Assistant Professor of Civil Engineering at the United States Air Force Academy.
    Abstract:
    NA
  • Session 8.0: Panel Discussion: Lessons-Learn from Implementing IRI Specifications (moderator) by John Senger, ILDOT
    Bio:

    Abstract:
    NA