Protocols for Network-Level Macrotexture Measurement (2021) / Chapter Skim
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42 The project included three equipment comparison experiments. The first experiment evaluated the main available technologies in terms of repeatability and reproducibility.
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Data Collection 43 Figure 21. Virginia Smart Road sections and surface types.
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44 Protocols for Network-Level Macrotexture Measurement Figure 22. Virginia Smart Road pavement surfaces.
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Data Collection 45 (a) HVS site at VTTI (b)
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46 Protocols for Network-Level Macrotexture Measurement Pavement profiles were analyzed for their effect on vehicle/road interactions by representing key characteristics in pavement surfaces as parameters. The software package for Device 12 is capable of calculating a wide array of these parameters from a given measured profile (Table 9)
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Data Collection 47 Device ID Description Laser Type Sample Distance Vertical Resolution 7 WDM TM2 Line Laser 1 mm (Transverse) 1 mm (Longitudinal)
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48 Protocols for Network-Level Macrotexture Measurement 3.1.3 High-Speed Equipment Highspeed data were collected using five vehicles, each fitted with laser triangulation sensors capable of collecting pavement macrotexture information at the rates shown in Table 12. All data were gathered in the left wheelpath of the "uphill" lane (the lane runs from east to west)
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Data Collection 49 Three sets of tests were completed at high speed as summarized in Table 13. The first test, "High Speed," was aimed at studying the overall repeatability and agreement of the various devices.
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50 Protocols for Network-Level Macrotexture Measurement sections, and remained at that speed for the duration of the test. The speeds listed in Table 13 were used in the constantspeed test.
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Data Collection 51 3.2.1 Location and Procedures The comparison was conducted on September 24–26, 2018, at the Minnesota DOT MnROAD facility in Albertville, Minnesota. To facilitate the alignment and processing of the data, the research team marked each section with reflective tape (Figure 29)
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52 Protocols for Network-Level Macrotexture Measurement Figure 30. Surfaces tested at MnROAD.
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Data Collection 53 3.2.3 High-Speed Equipment The devices included in the comparison experiment are listed in Table 15. Figure 32 includes some pictures taken during the experiment.
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54 Protocols for Network-Level Macrotexture Measurement 3.3.1 Equipment Used Table 16 summarizes the equipment used for the comparison. Two highspeed profilers were included, one with a singlespot laser and the other with a line laser.
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Data Collection 55 High-Speed Measurements Highspeed texturemeasurement systems from Ames and SSI were included in this experi ment. A single, highspeed line laser was mounted in three different configurations: longitudinal (LLL)
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56 Protocols for Network-Level Macrotexture Measurement DGF1: Dense-graded HMA (20-year old HMA surface)
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Data Collection 57 on each RELLIS section with a thin red line stripe over its 100 m length. The pictures given in Figure 35 show these line stripes.
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58 Protocols for Network-Level Macrotexture Measurement pavement surface is not valuable in an analysis of accuracy, as the true value of macrotexture is unknown (Izeppi et al.
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Data Collection 59 Reference LAPS Measurements Plates were first scanned with the laser line parallel to the grooves in the plates; however, this proved challenging for the device on some plates, as the abrupt changes from peak to slope and vice versa caused specular reflections that resulted in outlier data that overestimated plate depths estimated by the caliper measurements. Final reference measurements were made by sliding the laser line along the length of the plate with the line perpendicular to the grooves (see Figure 37)
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60 Protocols for Network-Level Macrotexture Measurement (a)
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Data Collection 61 could not be used, as the starting points and end points did not align with repeatable waveform locations. This resulted in incorrect mean line and regression determination, which affected the calculated MPD.
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62 Protocols for Network-Level Macrotexture Measurement 3.4.1 Surfaces Studied The surfaces selected were the continuous surfaces from the Smart Road Bridge to Pavement Section C As transitions between different surface types may have adverse effects on any given device's various measurements, the first and last 1 m of each section were removed from the pavement dataset.
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Data Collection 63 for small variations in vehicle travel speed, data are corrected (The Highways Agency 1999) to a constant equivalent SCRIM reading at 50 km/hr (SR50)
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