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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2023. Enhancement of the Practice for Certification of Inertial Profiling Systems. Washington, DC: The National Academies Press. doi: 10.17226/27182.
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2023. Enhancement of the Practice for Certification of Inertial Profiling Systems. Washington, DC: The National Academies Press. doi: 10.17226/27182.
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2023. Enhancement of the Practice for Certification of Inertial Profiling Systems. Washington, DC: The National Academies Press. doi: 10.17226/27182.
×
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2023. Enhancement of the Practice for Certification of Inertial Profiling Systems. Washington, DC: The National Academies Press. doi: 10.17226/27182.
×
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2023. Enhancement of the Practice for Certification of Inertial Profiling Systems. Washington, DC: The National Academies Press. doi: 10.17226/27182.
×
Page 7
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2023. Enhancement of the Practice for Certification of Inertial Profiling Systems. Washington, DC: The National Academies Press. doi: 10.17226/27182.
×
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Suggested Citation:"Chapter 1 - Introduction." National Academies of Sciences, Engineering, and Medicine. 2023. Enhancement of the Practice for Certification of Inertial Profiling Systems. Washington, DC: The National Academies Press. doi: 10.17226/27182.
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Page 9

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3   Introduction Evolution and Improvements of Inertial Profiler Technologies The objective of this project is to review and update AASHTO R 56-14, Standard Practice for Certification of Inertial Profiling Systems. Since the 1990s, inertial profilers have been used by state DOTs and others to produce mea- surements of longitudinal pavement profiles, which can then be analyzed to produce various smoothness statistics such as IRI. These devices are used to measure “true” pavement profiles at highway speeds that are comparable to profiles measured with a rod-and-level, which is labor- intensive, slow, and requires lane closures (Simpson et al. 2002). A comparison of past and present inertial profiler technologies is shown in Figure 1, including a General Motors (GM) inertial profiler from 1964, a South Dakota inertial profiler from 1984, a rear-bumper-mounted Dynatest inertial profiler from 2015, and a front-bumper-mounted Ames inertial profiler from 2015. The Dynatest model depicted also includes 3D scanning equipment mounted above the rear of the vehicle. The central principle of design for inertial profilers has not changed since GM’s original design in the 1960s (Huft 1984). This design includes a single-axis accelerometer, a height sensor, and a distance measurement instrument (DMI) to perform surveys at highway speeds, as illustrated in Figure 2. One example of this design is the K. J. Law 690DNC Surface Dynamic Profilometer, one of the early commercial products based on the Spangler method (1987). Other variations of inertial profiler designs include the Swedish Road and Traffic Institute (VTI) Laser Road Surface Testers (Arnberg and Magnusson 1984) and the University of Michigan Transportation Research Institute (UMTRI)/FHWA Road Profiler (PRORUT) (Hagan and Sayers 1987). The accelerometer collects acceleration at the point of reference. Time-domain processing for the acceleration includes two rounds of high-pass filtering and integration to transform the acceleration first to speed, then to inertial elevation (ZRef(x)) (Karamihas 2021). The resulting inertial elevation values are combined with the laser height measurements (H(x)), followed by a high-pass filter and a low-pass filter, to produce the final road profiles (ZRoad(x)). The high-pass filter typically removes wavelengths longer than 300 ft (Karamihas et al. 1999). Each of these elements of the profile is depicted in Figure 3. The inertial profiler is designed to remove the host vehicle’s body/suspension motion from the measurements of the laser height sensor, producing a “true” profile within a range of wave- lengths of interest for the evaluation of roadway roughness, typically four to 100 ft (Karamihas et al. 1999). In other words, the gain value is one over the range of wavelength response, compared to a widely varying range of gains from the profilograph. C H A P T E R   1

4 Enhancement of the Practice for Certification of Inertial Profiling Systems (1) (2) (3) (4) Figure 1. The evolution of high-speed profiler technologies: (1) the GM inertial profiler design in 1964; (2) the South Dakota inertial profiler in 1984; (3) a rear-bumper-mounted inertial profiler in 2015; and (4) a front-bumper-mounted inertial profiler in 2015 (Wix and Schleppi 2018). Figure 2. Principle of the designs and signal processing for inertial profilers (Karamihas 2021).

Introduction 5   Improvements in sensor technologies, signal processing, and filter designs have improved the performance of inertial profilers since the 1990s. These improvements result in improved accu- racy and repeatability, as evidenced by the reduction in percent error in profile measurements from 1993 to 2015, shown in Figure 4 (Wix and Schleppi 2018). Line lasers have been used to reduce aliasing in measurements from what may be observed with spot lasers on open-graded asphalt pavements, longitudinally tined pavements, and diamond ground pavements (Simpson et al. 2002). High-performance zero-phase shift filtering also helps obtain faster roll-off and prevent phase shift effects (Karamihas 2021). The phase shift is the time delay or advance of the computed profile with respect to each wavelength’s input. Inertial profiler certification has also improved, moving from a profile elevation basis to a cross-correlation-based method to prevent masking the impact of long-wavelength content on (1) (2) (3) Figure 3. An example of computed profiles: (1) elevations from height sensor signals, (2) elevations from accelerometer signals, and (3) complete profile (Karamihas et al. 1999).

6 Enhancement of the Practice for Certification of Inertial Profiling Systems Figure 4. Improvement of accuracy of inertial profilers from 1993 to 2015 (Wix and Schleppi 2018).

Introduction 7   profiles (Karamihas and Gillespie 2002). Reference profilers have also improved, with shorter sampling intervals and better footprints to produce more accurate and repeatable profiles (Karamihas and Perera 2014). A recent development in reference profilers includes autonomous technologies providing self-propelled, remote-controlled systems (Scott 2015, Toom 2015). Profiler technologies continue to evolve with improvements in location referencing, including the use of improved DMI, control area network (CAN) buses, and global positioning systems (GPSes) (Karamihas 2015). Manufacturers have further developed methods to measure pro- files at lower speeds, with some applications reported to achieve data collection in stop-and-go environments (Schaefer 2022). Implementation of laser scanning methods to extract wheel track profiles from three-dimensional pavement surface elevation data may further help remove the impacts of vehicle wander on profile measurement (Laurent and Talbot 2020). Recent advancements in DMI tracking use technologies to reduce DMI calibration errors and trigger errors from reflective surfaces. The DMI error is a significant cause of failures for AASHTO R 56-14 certification. One example of such a system uses a combination of (a) OBD-II port on a host vehicle that uses a CAN bus diagnostics interface, (b) high-accuracy kinematic GPS measurements during profiling for compensating data with DMI, (c) static GPS reference locations as subsection marking of long profiles, and (d) improved software to integrate the above data to reduce DMI drifts and improve the distance accuracy (Ames Engineering 2022). When such technologies are used for network-type profile measurements, they may significantly impact the data quality and network-class profiler certification requirements. Another potential improvement in profile measurements is specific to the collection in urban environments and at low speeds, as documented in NCHRP Research Report 914: Measuring, Characterizing, and Reporting Pavement Roughness of Low-Speed and Urban Roads (Karamihas et al. 2019). Manufacturers have developed error suppression techniques under situations requir- ing excessive speed changes, including acceleration/deceleration, braking, and stop-and-go. Other improvements currently under consideration include augmented sensors (three-axis inertial measurement unit [IMU] and GPS) and the Kalman smoothing filter; however, these may signi- ficantly increase the equipment cost (Karamihas 2021). One manufacturer claims the ability to measure a profile from 0 to 100 mph using four sets of beam laser-accelerometers, GPS-DMI track- ing, and error suppression (Schaefer 2022). However, further independent investigation is needed to validate this claim. In recent years, 3D scanning technologies have been used to produce pavement profiles (Laurent and Talbot 2020). An example of such 3D systems includes two scanning lasers and cameras mounted at the rear of the vehicle with an IMU to provide dynamic correction of the vehicle motions (Laurent and Talbot 2020). These data have been used to detect pavement rut depth, surface distresses, and edge drop-offs. Recently, pavement profiles along wheel tracks have been extracted from the data to evaluate ride quality, including the estimation of IRI. Though the three-dimensional technologies are not included in the current AASHTO R 56-14, several three-dimensional systems were certified by a non-state agency based on AASHTO R 56-14 in 2020 (Laurent and Talbot 2020). MAP-21/FAST Performance Measure Requirements MAP-21 (2012) and FAST (2015) require state DOTs to establish performance measures for pavement and bridge conditions. FHWA released the final rule 23 CFR Part 490, “National Performance Management Measures: Assessing Pavement Condition for the National Highway Performance Program and Bridge Condition for the National Highway Performance Program,” in 2017. Under this rule, state DOTs are required to establish performance targets for both

8 Enhancement of the Practice for Certification of Inertial Profiling Systems interstate and non-interstate highway pavements, including targets for IRI. To ensure uniformity among the state DOTs with respect to the performance target for IRI, profilers used to collect longitudinal profile data for computation of IRI must be capable of collecting repeatable and accurate profile data by meeting the system requirements documented in AASHTO M 328-14, Standard Specification for Inertial Profiler and the certification process in AASHTO R 56-14, Standard Practice for Certification of Inertial Profiling Systems. AASHTO M 328-14 defines the attributes required for an inertial profiling system. AASHTO R 56-14 describes a certifica- tion procedure for operators and test equipment used to measure a longitudinal surface elevation profile of a roadway based on an inertial reference system that is mounted on a data collection vehicle. AASHTO R 56-14 stipulates minimum requirements for accurate and repeatable profile measurements for construction quality control/quality assurance, acceptance, and network-level data collection. There is a concern from state DOTs that practices based on the current form of AASHTO R 56-14 do not adequately address the range of potential applications, including both project-level and network-level data collection. Development and Revisions of AASHTO R 56-14 The first generation of profiling standards was developed under a prior FHWA Expert Task Group (ETG) (Swanlund 2000). Among these standards was one for certification of inertial profilers. AASHTO PP 49-03 (2005), Standard Practice for Certification of Inertial Profiling Systems, was the first adopted standard for certification of inertial profilers. This standard practice was later updated and became the full standard practice AASHTO R 56 in 2010. The CPAR report (Karamihas 2005) provided recommended revisions to AASHTO R 56 (2010). AASHTO R 56-14 includes both static and dynamic performance measures of the system, which is important because profiler certification programs drive most improvements in profiler performance. One of the most critical elements of AASHTO R 56-14 is rating a profiler’s repeat- ability and accuracy based on cross-correlation. To facilitate the development of the inertial profiler certification process, an FHWA benchmark device was developed in 2007 for qualifying reference class devices (Karamihas and Perera 2014). The qualified reference class devices can then be used to qualify inertial profilers. A series of “rodeos” was conducted to qualify various commercially available reference class profilers and inertial profilers in 2009, 2010, 2013, and 2015 (Karamihas and Perera 2014, Karamihas 2015). AASHTO R 56-14 was considered primarily for construction acceptance applications. How- ever, it does include a few references to facilitate roughness levels that may be encountered in network-level profiling, such as: This practice describes a certification procedure for test equipment used to measure a longitudinal surface elevation profile of highways based on an inertial reference system that is mounted on a host vehicle. The minimum requirements stipulated herein are intended to focus on the need for accurate and repeatable profile measurements for construction quality control/quality assurance, acceptance, and network-level data collection. Report Organization This report is organized into five chapters. Chapter 1 (this chapter) introduces the project and its objectives and provides background information related to the scope of work being conducted. Chapter 2 describes existing certification practices, including the AASHTO R 56-14, and dis- cusses the practices in common use by state DOTs.

Introduction 9   Chapter 3 documents data obtained to evaluate certification practices and presents the analyses performed which justify the proposed revisions. Analyses encompassed data from multiple device “rodeos” and certification data from several state DOTs. Chapter 4 documents the proposed revisions and field test of the proposed revised AASHTO R 56 standard practice. Chapter 5 summarizes the research performed, identifies the primary technical findings, and provides recommendations for further work to be performed.

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Inertial profilers are used by state departments of transportation and others to produce an accurate and repeatable measure of the longitudinal pavement profile, which can be analyzed to produce various smoothness statistics such as the International Roughness Index.

NCHRP Research Report 1057: Enhancement of the Practice for Certification of Inertial Profiling Systems, from TRB's National Cooperative Highway Research Program, proposes revisions to AASHTO R 56-14 to enhance the practice for certification of inertial profiling systems.

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