2017 Speakers Bios

  • Session 1-0: Moderator by Li Ningyuan, MTO
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  • Session 1-1: Welcome from CDOT by Debra Perkins-Smith, CDOT
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  • Session 1-2: Keynotes: CDOT’s ROADX Program – Accelerating Technology on Colorado Highways by Peter Kozinski, CDOT
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  • Session 1-3: TPF-5(354) Pooled Fund Update by Dave Huft, SDDOT
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  • Session 1-4: TPF-5(299) Pooled Fund Update 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 a key member of the American Association of State Highway and Transportation Officials (AASHTO) Subcommittee on Materials 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.
    Mr. Mergenmeier is a Civil Engineering graduate from the University of Kansas, and a Registered Professional Engineer.
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  • Session 1-5: TPF-5(345) Pooled Fund Update by Kevin McGhee, VDOT
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    Abstract:
    Through a regional pooled fund, this program of research focuses on optimizing pavement surface texture characteristics. Phase II of the program continues to support the member’s effort to produce high-quality surface properties measurements but focuses on supporting the enhancing and adoption of emerging friction and macrotexture measurement technologies and the integration of these measurements into the next generation of pavement asset management systems. The program includes the following main broad activities: (1) equipment rodeos, (2) technology transfer, and (3) research on emerging topics. This presentation will provide an update on recent activities, as well as an overview of existing and expanding resources.

  • Session 2A-0: Moderator by Bob Orthmeyer, FHWA
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  • Session 2A-1: The Regulation (23 CFR 490) by Thomas Van, FHWA
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  • Session 2A-2: PM2 FHWA SOP Overview by Robert Rozycki, FHWA
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    Abstract:
    The Highway Performance Monitoring System (HPMS) pavement data item reporting requirements have been modified in response to the MAP-21 and FAST Act legislation. An overview and detailed description the new HPMS requirements will be given in support of the FHWA performance monitoring and management effort as they pertain to the final associated rulemaking effort. Data items primarily include IRI, rutting, faulting, and cracking along with various associated HPMS item requirements.

    While most States collect these data to some degree in their own systems, there are some new requirements in the data to be reported in the HPMS in support of high quality and nationally consistent performance measures. These will be presented with the HPMS-specific logistics of reporting these data.


  • Session 2A-3: Data Submission by Max Grogg, FHWA
    Bio:
    Mr. Max Grogg has worked for the Federal Highway Administration for over thirty years in various locations and positions. He is currently the Pavement Performance and Implementation Engineer in FHWA’s Office of Infrastructure. His main duties involve improving pavement performance data in the HPMS database and assisting states with performance management, pavement management, and asset management. Previously, Mr. Grogg was the Program Delivery Team Leader in the Iowa Division of Federal Highway. Mr. Grogg has worked with various state highway agencies around the country on pavement design, construction, maintenance, and management issues; destructive and nondestructive testing technologies, and the use of life-cycle cost analysis. Max has also been involved in the development and instruction of various pavement training courses. .
    Mr. Grogg obtained his BS in Civil Engineering from the University of Missouri-Rolla and an MS from the University of Illinois. He is a registered professional engineer in the State of Virginia.
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  • Session 2A-4: Data Quality Management Program by Bob Orthmeyer, FHWA
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  • Session 2B-0: 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 a key member of the American Association of State Highway and Transportation Officials (AASHTO) Subcommittee on Materials 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.
    Mr. Mergenmeier is a Civil Engineering graduate from the University of Kansas, and a Registered Professional Engineer.””

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  • Session 2B-1: Interstate Baseline by Pedro Serigos, AMEC
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    Abstract:
    Pavement roughness, in terms of the International Roughens Index (IRI), has been required by the Highway Performance Monitoring System (HPMS) since 1988, and it is now required by the MAP-21 and FAST ACT legislation. This presentation will review the IRI data submitted by the State Departments of Transportation (DOTs) to the HPMS over the period of 2013 to 2015. The IRI is considered not only one of the more reliably measured values within the HPMS, but also one where completeness has been observed as fairly stable over time, with approximately 47,000 miles of data provided in each of the referenced years. Accordingly, these data provided an opportunity to review the time-series trend in the HPMS IRI data.
    The average IRI has remained fairly constant for the three years in question, with the overall averages of 81 in/mile, 74 in/mile, and 79 in/mile for each of 2013, 2014, and 2015, respectively. These average values do not provide much indication of how the data truly change over time. A better picture is provided by distributions of the values, which illustrate that the data are fairly stable. Moreover, selected IRI data were reviewed to identify specific changes at a location and these also demonstrated the stability of the measure with an average increase in IRI of 0.85 in/mile from 2013 to 2014 and an average drop of 1.49 in/mile from 2014 to 2015.
    The IRI data in question were reviewed to identify the various factors that impact the values. Statistical analyses demonstrated that the IRI distributions were different for different types of terrain (level, rolling, mountainous), different climate zone, and different levels of population (urban vs rural). These analyses also suggested that the data collection conditions should be considered when trying to compare data from one area to another.

  • Session 2B-2: Data Collection for PM2 by Michael Richardson, Mandli
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  • Session 2B-3: FHWA Support/Guidance/Training by Bob Orthmeyer, FHWA
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  • Session 2B-4: Panel Discussion by All FHWA workshop speakers, FHWA
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  • Session 3-0: Moderator by Richard Wix, ARRB
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    Knowing the condition of the pavement surface can help a road agency manage its road network from both a performance and safety perspective. One such parameter is macro-texture, which is a property of the pavement surface that can affect skid resistance and also plays an important role in dispersing water in the wheel paths, thus reducing the potential for hydro-planning.
    Automated 3-dimensional (3D) data collection systems, which have primarily been used for the detection of pavement defects and transverse profile measurement, also have the ability to measure other pavement condition parameters and features. One such parameter is pavement macro-texture.
    A validation exercise was undertaken by the Australian Road Research Board to assess how well the outputs from the 3D system matched those from a ground truth texture measuring device over a series of test sites. This paper presents the results of the validation and provides additional information into how this 3D technology is able to measure pavement macro-texture.

  • Session 3-1: Relativity of Pavement Condition Rating Methods and Needs for International Standardization by Li Ningyuan, MTO
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    Abstract:
    This presentation will focus on distress data classification collection and evaluation using International Roughness Index (IRI), Surface Distress Index (SDI) and other overall Pavement Condition Indices (PCI). It will identify a few technical issues with measuring and rating pavement conditions, including individual distresses and performance indices commonly used in pavement management. Then presentation will then explore a number of fundamental problems relating to pavement evaluation and maintenance management, ranging from pavement condition data collection to pavement maintenance investment program. Finally, the presentation discusses accountability of pavement condition rating methods and comparability of the current pavement condition evaluation results, which lead to the needs for developing a universal conversion that can compare different pavement condition rating systems to a standardized ranking system. An example of using different road condition rating methods to demonstrate the issues and needs for a standard rating system, including engineering specification and validation of pavement performance indices. To ensure quality of the automated pavement condition assessment, a series of comparative measurements in the field were conducted to verify whether each of the stages has been accurately processed, such as pavement distress detection, classification, condition evaluation and reporting.

  • Session 3-2: Evaluation of Changes in IRI along Center of Lane to Assess the Effect of Environmental Factors on IRI by Rohan W. Perera, SME
    Bio:
    Dr. Perera is a Senior Consultant with SME in Michigan. He has been working in the pavements field for 25 years. His experiences include: pavement roughness and profile data analysis, pavement design, pavement evaluation, pavement management, and non-destructive testing of pavements. He has also provided technical assistance to the LTPP program on profile related activities, including acceptance testing of new profilers and organizing and analyzing data from profiler comparison studies.
    Abstract:
    The profilers used to collect data for the Long Term Pavement Performance (LTPP) Program have been collecting profile data along the center of the lane in addition to collecting data along the wheelpaths since December 1996. The change in the profile along the center of the lane in a flexible pavement is expected to be mainly affected by environmental effects. A study was performed to evaluate changes in IRI along the center of the lane at test sections in the LTPP SPS-1 experiment that dealt with evaluation of selected structural factors on the performance of flexible pavements to identify subgrade and climatic factors that influence IRI changes along the center of the lane. In addition, the change in the center of the lane IRI was compared with the change in Mean IRI at test sections. This results from this study are summarized in this presentation.
  • Session 3-3: Guidance for Predicting and Mitigating Hydroplaning by Gerardo Flintsch, Virginia Tech
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    This presentation would address the development of a comprehensive hydroplaning risk assessment tool that can be used by transportation agencies to help reduce the potential of hydroplaning. The tool treats hydroplaning as a multidisciplinary and multi-scale problem, integrating the most appropriate surface water drainage, tire, vehicle, and fluid dynamic models to predict the hydroplaning risk for new and existing roads.

  • Session 3-4: New Dynatest Rapid Pavement Tester by Salil Gokhale, Dynatest
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    Abstract:
    Traditional structural testing is slow in speed (2km/hour) and consequently most pavements are not tested. Pavements in cities represent 30% of a total of 24 million kilometers globally, with structural tests being rarely carried out. A compact and reliable Rolling Weight Deflectometer which would be able to test at 80 km/h and that at the same time is easy to maneuver in cities without creating congestions nor safety concerns would change this situation.
    The Rapid Pavement Tester, RPT, is the new Dynatest product, now under its last development phase, that will start offering high speed deflection measurements in 2018. The RPT integrates the RWD into a new platform to collect simultaneously structural and functional data.
    Using image recognition and a normalized cross-correlation algorithm, the RPT identifies very accurately the same spot on the road scanned by subsequent lasers. This allows the effects of the beam translation and rotation as well as the texture of the pavement to be removed.
    The Dynatest RWD is based on a relatively short beam without any significant bending and the data will need to be averaged over less distance which will result in shorter distance between data points. The short beam also allows for a short truck that is easy to maneuver in a city landscape. The performance of the Raptor has been tested towards repeatability and load scalability with success, and the its ability to reproduce the true pavement response has been verified by in-pavement sensors. Shadow testing using the FWD and the Raptor is ongoing.

  • Session 4-0: Moderator by Eric Prieve, CDOT
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  • Session 4-1: Urban Profiling: Measurements and Indexes by Steven karamihas, UMTRI
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  • Session 4-2: Transverse Profile Calibration, Certification, and Verification; its use in Rutting, Crowning & Cross Slope by John Ferris, Virginia Tech
    Bio:
    John B. Ferris investigates improvements to ground vehicle system performance by studying their interactions with terrain surfaces. Specifically, his research focuses on chassis design and development, vehicle dynamics, terrain topology (high-fidelity measurement, calibration, verification, characterization, statistical analysis, and stochastic modelling), driver-vehicle interactions, virtual proving ground development, vehicle performance (ride, handling, reliability, mobility), and automated vehicle development. He began this work in 1990 for Chrysler, then DaimlerChrysler and ZF Lemförder, before joining the Virginia Tech faculty in 2005 as an Associate Professor. He has participated in dozens of sponsored research projects totalling over $11 million, publishing 28 peer reviewed journal papers and 42 conference papers. His contributions as founder and director of the Vehicle Terrain Performance Laboratory are detailed on the lab website: www.me.vt.edu/VTPL.
    Abstract:
    The objective of this project is for all interested parties to be empowered with the information necessary to assess Transverse Pavement Profiler (TPP) capabilities with respect to the requirements of their applications. This proposal is driven by the ultimate application of the tools resulting from this project: the ability of transportation agencies to specify, monitor, and evaluate pavement testing programs that include transverse pavement profiles.
    In the most general terms then, the capabilities of a Transverse Pavement Profiler (TPP) must be properly matched with the requirements of various applications. The terms capabilities and requirements imply that clear definitions of precision and accuracy of (highway speed) transverse pavement profile measurements are needed. It is therefore proposed that the TPP capabilities are captured in a Capability Statement (CS) and the application requirements are captured in a Requirements Statement (RS), each containing statements of accuracy and precision in the same format for efficient comparison.

  • Session 4-3: FDOT Profiler Certification by James Greene, FDOT
    Bio:
    James Greene started his career as a consultant with the US Air Force and then the Florida Department of
    Transportation where he led a team that performed statewide FWD testing. He joined FDOT in 2008 where he managed
    the Accelerated Pavement Testing program. He currently leads the Pavement Condition Survey group. This group is
    responsible for conducting smoothness acceptance testing of all new flexible pavements and collecting pavement
    condition data for the state highway system.
    Abstract:
    To better achieve smooth pavements, the Florida Department of Transportation (FDOT) in partnership with the paving industry has formed a smoothness task team to promote good construction practices and to develop and implement data driven profile-based construction smoothness specifications. The long-term success of profiler-based specifications rely in part on the implementation of an FDOT profiler certification program to verify the accuracy and repeatability of test equipment to measure a longitudinal surface elevation profile. To realize this goal, a certification test track was recently constructed at Williston Municipal Airport in Levy County. The test track is approximately 3,700 feet long and includes both dense (FC-12.5) and open-graded (FC-5) asphalt surfaces. Design and construction consisted of targeting International Roughness Index (IRI) zones that reflect FDOT’s current specification and requirements set forth in AASHTO R-56. To aid the development of Florida’s profiler certification requirements, multiple reference profiles were compared, including units from Texas Transportation Institute (TTI) and International Cybernetics Corporation (ICC). In addition, FDOT’s network and project level inertial profilers were tested and the influence of laser type (single spot versus Roline) was determined. IRI Filtered repeatability values for reference profiles show good reproducibility between each unit. However, each reference profiler device failed to meet required AASHTO R56 standards on the smooth segments of the certification track. IRI filtered accuracy and repeatability indicated little difference between the Roline and single dot laser on the dense graded surface but were significantly different on the open graded surface.
  • Session 4-4: Real-time Smoothness Technology by Dave Merritt, Transtec Group
    Bio:
    David Merritt is a Director with The Transtec Group of Austin, Texas, a firm specializing in pavement research and engineering. One of his areas of specialty is pavement surface characteristics, encompassing smoothness, friction, and texture, and tire-pavement noise. He received his Bachelor’s degree from Northern Arizona University and Master’s degree from The University of Texas at Austin and is a registered Professional Engineer in the State of Texas.
    Abstract:
    Real-Time Smoothness (RTS) technology is a tool for helping to improve the as-constructed smoothness of concrete pavements. RTS technology measures the profile of a concrete pavement slab behind the paver, providing real-time feedback on smoothness during the actual paving operation. This allows contractors to diagnose potential issues in the paving operation that affect smoothness in order to make equipment/process changes immediately, rather than waiting for feedback after the hardened pavement is profiled. This real-time feedback also gives the contractor the opportunity to correct localized roughness in the profile while the concrete is still plastic, minimizing more costly corrections later. In 2014 FHWA initiated an RTS equipment loan program as part of the implementation of SHRP2 technologies. This equipment loan program offered agencies and contractors the opportunity to evaluate commercially-available RTS systems to determine the benefits for improving initial smoothness. The project team from the Concrete Pavement Technology Center facilitated these equipment loans, collecting and analyzing profile data from a wide variety of concrete paving projects throughout the U.S. over a three-year period. Analysis of this data, coupled with observations during paving operations, and discussions with contractors, have provided tremendous insight into the benefits, limitations, and overall usefulness of RTS technology. This presentation summarizes some of the key lessons learned from the equipment loan program and provides recommendations for the use of this technology to improve initial concrete pavement smoothness.
  • Session 5-0: Moderator by Brian Schleppi, Ohio DOT
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  • Session 5-1: Pavement Macrotexture: State of the art and Practice by Vincent Bongioanni, Virginia Tech
    Bio:
    Major Vincent Bongioanni is an active duty Air Force Officer on assignment to Virginia Tech, working toward a Ph.D in Civil Engineering. He served two tours of duty in Afghanistan and other various locations in support of Operation Enduring Freedom. 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 geotechnical engineering concentration. He served for two years Airfield Pavement Evaluation Team Chief, performing numerous evaluations across the globe. Most recently, he served as an Assistant Professor of Civil Engineering at the US Air Force Academy.
    Abstract:
    Pavement texture characteristics are key indicators of several critical tire/pavement interactions. Chief among these are the wet weather friction and vehicle splash and spray, due to safety risks posed. Also important are interactions that affect society (such as road noise) or have economic impacts such as rolling resistance and tire wear. The presentation will review the methods for gathering macrotexture data, as well as the parameters used to characterize it. It will also summarize a recent survey of current practice.
  • Session 5-2: 3D Texture Measurement by Richard Wix, ARRB
    Bio:
    Richard joined the Australian Road Research Board (ARRB) in 1990 and presently holds the position of Acting Lead, Strategic Enablers Group with oversight of the Advanced Technologies LAB, the hub of ARRB’s intellectual outreach in the research and project delivery environment.
    During his time at ARRB, Richard has been involved in the collection of functional and structural pavement condition data across large scale road networks for Australian and New Zealand road agencies. He has also been involved in identifying and integrating new technologies into road survey platforms to help road agencies improve the management of their road networks.
    Richard has a good understanding of the pavement condition data having worked closely with several road agencies in Australia and overseas. Richard is also a member of several international groups that help him keep up to date with the latest developments in automated pavement data collection around the world.
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  • Session 5-3: Exploring Pavement Texture and Surface Friction Using Soft Computing Techniques by Jashua Q. Li, OSU
    Bio:
    Dr. Qiang “Joshua” Li, is currently an Assistant Professor at Oklahoma State University and has been a project engineer at Applied Pavement Technology Inc. Dr. Li has more than 15 years of experience in pavement design, automated condition evaluation, roadway safety analysis, and asset management.
    Abstract:
    Pavement friction and texture characteristics are important aspects of road surface safety. Extensive studies have been conducted during the past decades, while their relationship has not been fully understood. This paper implements two soft computing techniques to investigate the application of pavement texture data for skid resistance and pavement safety analysis. First, pavement texture and friction data are collected in parallel at various locations via an ultra-high resolution 3D laser scanner and a Dynamic Friction Tester (DFT). The texture data are separated by wavelength into macro- and micro-scales using a pre-designed Butterworth Filter. Subsequently, discrete wavelet transform is implemented to compute the Total Energy (TE) as the texture indicators at both scales. It is found that pavement micro-texture indicators are significant to surface friction at low speed while both macro- and micro-texture indicators are significant at high speed. Second, deep learning (DL), as the fastest-growing field in machine learning, has shown its potential in pavement engineering applications. 65 pairs of texture and friction data collection are performed at 49 High Friction Surface Treatment (HFST) sites in 12 states. Pavement macro-texture data is collected using the AMES high-speed profiler, while Grip Tester is used to continuously measure the longitudinal friction data operating around the critical slip ratio. Recursive auto-encoders and recurrent Boltzmann Machines (RBM) are discussed and applied to predict surface friction based on pavement macro-texture data. 80% of the data sets is used for training, while the remaining 20% for validation. It is anticipated that the work in this study could assist in developing non-contact texture measurement techniques for pavement safety evaluation.
  • Session 5-4: Pavement Friction Management 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, the National Sustainable Pavements 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:
    In 2010, the FHWA initiated a study to develop and promote Pavement Friction Management (PFM) programs and investigate the benefits of using continuous friction measurement equipment (CFME) as compared to conventional locked-wheel skid trailer (LWST) testing. The overall goal of the study is to reduce highway crashes and related fatalities through the development and demonstration of pro-active PFM programs. Such programs, when properly devised and effectively implemented, have the potential to significantly reduce the number (and seriousness) of crashes by decreasing pavement friction and texture related crashes.
    This presentation will summarize work completed as part of the FHWA program to include: (a) performing SCRIM and LWST friction testing in several US States, (b) collecting comprehensive friction, crash, and other data, (c) analyzing the data to identify appropriate investigatory friction and macrotexture levels, and (d) providing guidance for participating states on how to compile and analyze friction and crash data to further the development of a PFM program and implement it into practice.
  • Session 6-0: Moderator by John Andrews, MD SHA
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  • Session 6-1: No Fogline, No Problem by Scott Mathison, Pathway
    Bio:
    Mr. Mathison serves as Vice President of Operations for Pathway Services Inc. He has experience in the management of data collection and data processing of more than 3,000,000 lane miles of condition and asset data and currently oversees contracts with more than 20 state transportation departments.

    Mr. Mathison earned both his MBA and undergraduate degrees from the University of Oklahoma. He has since held many positions in information technology and has more than a 15 years of pavement management experience. He has also overseen the deployment and management of more than a petabyte of condition data nationwide.

    He’s been married for 15 years, has three kids and is the biggest home automation nerd in the room.

    Abstract:
    3D automated transverse profile data provides our industry with surface characteristics data that we could only dream of just a few years ago. With network-level collections producing TBs of data annually, much of this data is automated not just for collection, but for processing, QC, QA and reporting. Real-world environmental characteristics, such as narrow lanes, areas of shoving, erosion, curb/gutter, missing/failing lane markings can lead to difficulties for automated techniques to effectively QC and accurately report rutting data without human intervention or specifically-developed automated QA modules. This presentation will detail several techniques and methodologies utilized in statewide data collection projects to mitigate the effects of difficult, real-world scenarios for automated data collection and reporting.


  • Session 6-2: Deep Learning System for Automated Cracking Survey & Its Performance with Pixel Accuracy by Kelvin Wang, OSU
    Bio:
    Kelvin C.P. Wang is chair professor of civil engineering at Oklahoma State University (OSU). He has degrees from Jiaotong Universities in China, and Arizona State University. His professional career includes four years at Arizona DOT and then 24 years as a university faculty. The ASCE 2011 Frank M. Masters Transportation Engineering Award was given to Dr. Wang for his “”innovative research on automated pavement survey and data analysis technologies””. From early 2016, the team lead by Dr. Wang developed the Deep-Learning solution, CrackNet, for true fully automated system for cracking survey.

    Abstract:
    For decades, fully automated cracking surveys for highway and airfield pavements were not possible despite of enormous advances in hardware and software development on worldwide basis. Currently substantial amount of resources must be dedicated to manually editing results from the “automated’ processing to achieve needed precision and bias. The challenge in automation is to maintain acceptable levels of precision and bias at all times disregard pavement types and their surface conditions, and without substantial manual intervention. This presentation discusses the challenges and frustrations facing the industry for decades in obtaining pavement cracking information and their subsequent applications in both design and management activities. Progress in the recent decade from industry, users, and researchers is summarized. The presentation also illustrates the motivation in 2015 and early 2016 for the research team to change direction and embark on developing a completely different technical approach to automated survey of pavement cracking. The Deep-Learning (DL) methodology is based on decades old computerized concept of Artificial Neural Network (ANN) with substantial improvements to the network structure and vast increase of the network sizes, resulting in many recent successful applications with super-human capabilities. The presentation also discusses the recent trends in cracking and data standards including the FHWA led Pooled-Fund TPF 5(299) and various NCHRP and AASHTO efforts. The efforts from different agencies at national and state levels for pavement design and management all point to a consensus that fully automated cracking survey is needed and relevant standards should be made or modified to accommodate the automation. Based on the need of true automated pavement cracking survey and the potential capabilities of DL, since early 2016 a research team was assembled with over 10 staff and students in the US and China to start the DL work, and in the fall 2017 the team completed the initial development of a fully automated cracking survey solution. This presentation focuses on the background and system design of a DL based neural network targeting at true full automation.


  • Session 6-3: Why Didn’t the Pavement Distress Quality Assurance Plan Work by Douglas Frith, QES
    Bio:
    Doug Frith is Vice President of Quality Engineering Solutions, Inc. and a Principal Engineer with 32 years of highway engineering and construction experience. His primary emphasis has been in pavement engineering including research, evaluation, management, and design. He received Bachelor and Master of Civil Engineering Degrees from the University of Idaho. He is former member of the TRB Pavement Management Committee and a current member of the TRB Pavement Condition Evaluation Committee.

    For the past 18 years, Mr. Frith has been applying the modern technical developments in pavement management, maintenance, and design in the consulting field. He currently manages the Independent Validation and Verification efforts for over 22,000 miles of pavement management data for the Virginia DOT, and manages the daily Quality Assurance ratings of 19,000 miles of pavement for the North Carolina DOT.

    Abstract:
    A presentation of the independent distress verification and validation (IV&V) effort conducted for the Virginia Department of Transportation in 2016 and 2017 will consist of discussing the details of the data quality management plan being used, how and why some non-conforming data sets passed the IV&V checks when they should not have, and how this issue was remedied in 2017.

    In 2016, larger than normal data deliveries were provided for the secondary route pavements, resulting in nearly 3 times the number of QA samples typically collected. Although the initial deliverable passed all of the QA checks, it was later determined that portions of the data set did not include all of the longitudinal and transverse cracking that should have been reported. A detailed investigation ensued which resulted in changes to the existing IV&V process, which was then applied to the 2017 data.

  • Session 7-0: Moderator by Steve Karamihas, UMTRI
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  • Session 7-1: Relationship Between Repair Situation and Roughness Conditions by Koichi YAGI, Bump Recorder
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    Abstract:
    Road roughness data e.g. IRI is useful for the pavement maintenance management. But in fact, many road administrator faced difficulties how to use roughness data. Because of it spend much cost previously, so, they make decision without data. Recently, a convenient and low cost measurement method e.g. smartphone type was developed. It is removing one the obstacle of cost side. On the other hand, the operational difficulties are still remaining.
    In Japan, at Aizu-Wakamatu city, from before, the local government road administrators are doing regular patrol few times a week for human visual inspections and simple repairs. From January 2015, they are starting regular roughness measurement by using smartphone. It is measuring on this patrol, so it is not increasing man-hour cost. Previously, patrol result is hand writing on the notebook. From June 2016, they are starting to record site photo with GPS data and one word comment by using smartphone. As the result, there are roughness data and repair results.
    In this presentation, it is using both recording, relationship between repair situation and roughness conditions is discussed.


  • Session 7-2: Pavement Performance Measures: Reporting Versus Decision Making by Nima Kargah-Ostadi, Fugro
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    Abstract:
    The final rules for reporting pavement and bridge performance measures were published by the Federal Highway Administration (FHWA) in January 2017 and these rules became effective under the Fixing America’s Surface Transportation (FAST) Act in May 2017. While most highway agencies are in the process of determining how to meet these reporting requirements, the ultimate objective of performance management might be overlooked. Every highway agency has their own performance measures, which they use for network-level decision making to assist in generating the most cost-effective program of improvement projects. There is a gap between performance measures used for reporting existing condition versus the performance measures used for management decisions. This presentation is trying to address some of the challenging questions in closing this gap.
    Should the highway agencies change their performance evaluation methodology and protocols to match the federal rules, or should they establish a correlation between their performance indices and the federal reporting measures? There is a need to investigate how agency investment decisions are reflected in the performance measures reported to the FHWA. With the additional data available from higher resolution equipment, are we focused on information that is actually used in decision making, or are we losing the signal among the noise? How can the reporting requirements help advance the state of the practice in performance-based decision making? What limitations should agencies be cognizant of to avoid confusion?

  • Session 7-3: The Latest Development of TSD Deflection Technologies by Leif Grønskov, Greenwood
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  • Session 7-4: Open Panel Discussion: Profile Data Collection QA by DOT reps and, TBA
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