The National Academies Press

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From page 24... ... 24 Based on the literature review and survey of state highway agencies, the research team identified, summarized, and analyzed current and emerging measurement technologies for collecting macrotexture data at the network level. The team also identified and evaluated available parameters for characterizing macrotexture. Read the entire page →
From page 25... ... Macrotexture Measurement Technologies and Parameters 25 computed, the time required to completely drain the water from the cylinder is recorded and this value can be correlated to other macrotexture parameters. Outflow devices have the benefit of quantifying the benefit of subsurface interconnected voids from surfaces such as porous or pervious pavements and OGFC. Read the entire page →
From page 26... ... Commonly Used Single-Point Lasers Product Name Manufacturer Technology Laser Wavelength (nm) Maximum Sampling Rate (kHz) Read the entire page →
From page 27... ... Macrotexture Measurement Technologies and Parameters 27 The most common devices are HSLE systems that use the single-spot laser triangulation method. Under this approach, a single laser beam (generally smaller than 1 mm in diameter at its standoff distance in the center of its measurement range) Read the entire page →
From page 28... ... 28 Protocols for Network-Level Macrotexture Measurement Table 5 lists companies that employ the sensors listed in Table 4 to collect macrotexture data for state DOTs and private clients. It is noted that several companies have indicated preliminary use of laser systems to collect "3D" macrotexture profiles (the profiles are gathered at a nearcontinuous level in the transverse direction, but there is a gap between profiles in the longitudinal [travel] Read the entire page →
From page 29... ... Macrotexture Measurement Technologies and Parameters 29 2.2.1 Commonly Used Macrotexture Characterization Parameters Table 6 summarizes the most common macrotexture parameters and their constituents in use today. This section provides explanations of each parameter or group. Read the entire page →
From page 30... ... 30 Protocols for Network-Level Macrotexture Measurement from macrotexture data with known MTD values (i.e., from sand patch tests) for the pavement and vice versa. Read the entire page →
From page 31... ... Macrotexture Measurement Technologies and Parameters 31 TD Texture depth (TD) is typically a 3D parameter. Read the entire page →
From page 32... ... 32 Protocols for Network-Level Macrotexture Measurement One advantage of using the MTD3 is that the microtexture spectrum of pavement wavelengths (< 0.5 mm) can be captured given such a device's resolution. Read the entire page →
From page 33... ... Macrotexture Measurement Technologies and Parameters 33 stereo system was used to produce pavement profiles from 3D images that could be processed into various macrotexture parameters. The work included laboratory sampling of a pavement specimen using both a physical stylus with an in-line dial gauge and a profile gathered from the photography. Read the entire page →
From page 34... ... 34 Protocols for Network-Level Macrotexture Measurement decomposes a macrotexture profile to a limited number of profiles and then produces averaged frequency and amplitude profiles for correlation to pavement friction. The processing is labor intensive and, at least at this time, does not appear practical for implementation on network-level analysis. Read the entire page →
From page 35... ... Macrotexture Measurement Technologies and Parameters 35 ∫ ( ) Read the entire page →
From page 36... ... 36 Protocols for Network-Level Macrotexture Measurement Figure 14. Mean square roughness (1.02) Read the entire page →
From page 37... ... Macrotexture Measurement Technologies and Parameters 37 • Kurtosis (Rku) can generally be used to describe the peakedness of a macrotexture profile (i.e., how severe peaks and troughs are; hence the large value shown in Figure 16, given that the data has not been filtered) Read the entire page →
From page 38... ... 38 Protocols for Network-Level Macrotexture Measurement 2.3 Data Filtering and Correction A basic tenet of signal processing is that all data will have some noise masking the physical phenomenon measured. Non-contact macrotexture measurements are no different. Read the entire page →
From page 39... ... Macrotexture Measurement Technologies and Parameters 39 small segments of data. To correct this issue, a linear regression of the data is typically made, with the resulting equation of the line subtracted from the data to suppress the slope and bring the mean value of the profile to zero. Read the entire page →
From page 40... ... 40 Protocols for Network-Level Macrotexture Measurement Filtered data mean = 19.1, mean with dropout = 19.0. Read the entire page →
From page 41... ... Macrotexture Measurement Technologies and Parameters 41 outlier. For example, ISO 13473-1 (1997) Read the entire page →

From page 24...

... 24 Based on the literature review and survey of state highway agencies, the research team identified, summarized, and analyzed current and emerging measurement technologies for collecting macrotexture data at the network level. The team also identified and evaluated available parameters for characterizing macrotexture.