Post on 25-Apr-2020
transcript
Factors affecting the reliability of data related to pavement profiles and surface characteristics
ENEA SOGNO and MICHELE MORIenea.sogno@sina.co.it
michele.mori@sina.co.it
Copenhagen, 2017.10.19
Pointing out some issues
The company
About longitudinal and transverse roughness
About macrotexture and skid rates
About surface distress (cracking, raveling, potholes)
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Summary
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Pointing out some issues
WHAT TYPE
Collecting data...
BASED ON CONTACT
Physical interaction between the structure and the machine is necessary
BASED ON LASER EMISSIONS
The interaction between the structure and the machine is evaluated from the shape and the
amplitude of source-to-target signals
PAVEMENT
Friction, deflection basins
PAVEMENT/ROAD
Profiles, contour marking strips, deflection basins, geometry
HOW TO USE
Skid rate, elastic modulus, roughness, rut depth, macrotexture, surface indicators, reflective power, carriageway/infrastructure dimensions and slopes
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
WHICH NEEDS
ROAD MANAGERS PUBLIC ADMINISTRATIONS
TECHNICAL SUPPORT
Usable information
ECONOMIC SOLUTIONS
Fit budget
WHICH EXPECTATIONS
Maintenance?
Safety?
To save money?
...in answer to
Data is the key, processing and post-processing make
the difference
Pointing out some issues
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
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Laser sensors @64 KHzShould we get any answers from that?
Pointing out some issues
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
At least, one: the need for data!
We do not need instruments and technologies to assess whether potholes or cracks exist upon the pavement surface. Cams are sufficient for that…
Right side view 45°
Left side view 45° Front view
Spherical cameras
Panoramic
view up to
324°
Pointing out some issues
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
We need surveys to assess the level of distress of the pavement surface in a quantitative and qualitative way through the analysis of key performance indicators.
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Reliable raw data => Effective KPIs
Pointing out some issues
The company
Sina S.p.A. is an Italian company which provides extended engineering services to infrastructure
managers worldwide. It belongs to the Gavio Group.
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
The experience with laser technologies
Technology Services and other
Shipbuilding
Engineering
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Surveying for evaluation and for comparison purposes implies the necessity of fully controlling each factor which makes the results different (i.e. trajectory, surface distress, speed, weather, …).
Road profiling with…
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
AASHTO requires at least 25mm long sampling for class 1 profilers!!
About longitudinal and transverse roughness
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Using the most accurate and repeatable technologies could help, but uncertainties will remain!
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Rep1 Rep2 Rep3 Rep4 Rep5 Rep6 Mean RMS CV
IRI_right 1,67 1,76 1,73 1,63 1,68 1,68 1,69 0,05 3%
IRI_left 1,08 1,03 1,06 1,00 1,00 1,03 1,03 0,03 3%
IRI_avg 1,37 1,40 1,40 1,32 1,34 1,36 1,36 0,03 2%
Selcom right versus left side => same dispersion, different mean values
NEW PAVEMENT NO CRACKS NOR RUTS
Something happens to profiles in the right wheel-path, is that due to pavement concerns or to the machine? The transverse position? All of
these factors?
Mostly controlling surveying conditions could be an improvement, but uncertainties will remain
once again!
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Completely scanning the road lane would finally lead to lowly-spaced longitudinal profiles that may help, and many times they do, but they’re not THE solution!
storage concerns
need for data quantity reduction
difficult evaluation of detailed results
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Avg per long profile
IRI_avg IRI_max St.dev. CV
Test site #1 1.52 2.90 0.36 23.44
Motorway
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Avg per long profile
IRI_avg IRI_max st.dev. CV
Test site #2 1.44 2.73 0.37 25.61
Motorway
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Avg per long profile
IRI_avg IRI_max st.dev. CV
Test site #3 2.32 7.93 1.56 56.82
Roadway
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
IRI_avg IRI_max st.dev. CV
Test site #1 1.52 2.90 0.36 23.44
Test site #2 1.44 2.73 0.37 25.61
Test site #3 2.32 7.93 1.56 56.82
Transverseposition
IRI_avg_#1 IRI_avg_#2 IRI_avg_#3
-1.9 2.07 1.91 1.96
-1.8 1.72 1.66 1.92-1.7 1.63 1.63 1.84-1.6 1.56 1.62 1.77
-1.5 1.58 1.63 1.76
-1.4 1.63 1.62 1.78-1.3 1.69 1.59 1.79-1.2 1.74 1.55 1.79
-1.1 1.77 1.48 1.77
-1 1.77 1.44 1.77-0.9 1.74 1.40 1.71-0.8 1.70 1.37 1.70
-0.7 1.65 1.34 1.71
-0.6 1.58 1.34 1.70-0.5 1.54 1.36 1.75-0.4 1.53 1.38 1.79
-0.3 1.53 1.41 1.81-0.2 1.54 1.43 1.81-0.1 1.55 1.44 1.820.1 1.29 1.26 1.61
0.2 1.25 1.24 1.550.3 1.26 1.26 1.550.4 1.25 1.26 1.610.5 1.24 1.26 1.65
0.6 1.23 1.25 1.680.7 1.24 1.27 1.78
0.8 1.30 1.31 1.950.9 1.34 1.34 2.10
1 1.36 1.36 2.181.1 1.37 1.38 2.18
1.2 1.37 1.38 2.09
1.3 1.38 1.39 2.04
1.4 1.38 1.41 1.961.5 1.38 1.43 2.00
1.6 1.44 1.50 2.43
1.7 1.49 1.54 4.25
1.8 1.59 1.56 7.601.9 1.92 1.66 12.15
Lower and more homogeneous IRI
values from sides to the center of the road lane
Different quality in test sites #1 and #2 compared to #3
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Localized repairs
About longitudinal and transverse roughness
We got lots of information on roughness and were able to make comparisons…but still have to decide how to use data!!
What is the goal?
Analysis at the network level
Design
PMS
IRI_avg IRI_max St.dev. CV
Test site #1, 1.9 - 160mt 1.92 5.60 0.64 33.21
Test site #1, -1.9 - 160mt 2.07 4.41 0.60 29.01
Test site #1, 1.9 - 2mt 1.92 15.70 1.47 76.54
Test site #1, -1.9 - 2mt 2.07 16.93 1.51 73.10
2mt vs 160mt
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Remembering that…
Processing is the powerful instrument that
can really help to reduce uncertainties and
focus on the goal of the survey!
Raw data is 1 profile elevation each some
millimeters, processed data is 1 reference
value each some meters.
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
Only if the exact needs are well known, the available information can be properly read and
managed. For instance, we won’t take care of the spacing, if we’re looking for subgrade and/or
viscous AC rutting, but we will wisely consider the trajectory of the vehicle along the lane.
Then…
As well, we won’t take care of the transverse
position of long profiles, if we’re looking for
joints!
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
About longitudinal and transverse roughness
About 26 mt from PSD analysis
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Macrotexture and skid rates
Modern technologies allow data to be acquired each some millimeters again, even in the case of contact-based determinations such as the skid rate. But sometimes a lower and lower resolution may be convenient for technicians…
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Macrotexture and skid rates
Raw data each 10 cm, moving averages at 600mt
Evaluating homogeneous sections at the network analysis level can produce effective results both from contact-based and from profile-based determinations…
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Macrotexture and skid rates
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Macrotexture and skid rates
But, looking for more detailed information will bring to some differences due to the temperature and the speed at which SR and MPD were measured, the geometry of the site.
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Macrotexture and skid rates
Dealing with a patch and with a road network is quite different!
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Macrotexture and skid rates
…and surveying conditions count
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Surface distress (cracking, raveling, potholes)
Improved road surveying allows operators to analyse even cracks and punctual distress which exist on the pavement surface, providing a large multitude of data (widths, lengths, depths, areas).
Is it better to know how many cracks do we see in the picture above (and their characteristics) or the reason why
we can miss some of them?
Proficient synthesis, you’re welcome!
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Surface distress (cracking, raveling, potholes)
A good answer would be both!
Without knowing the quantity of cracks we won’t be able to make analyses…
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
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Surface distress (cracking, raveling, potholes)
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
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Surface distress (cracking, raveling, potholes)
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Surface distress (cracking, raveling, potholes)
But, without knowing factors which influence the results we won’t be able to improve the reliability
of our analyses!
Is it possible to miss that due to adverse weather conditions? Powder? Wrong resolution? Something else?
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Surface distress (cracking, raveling, potholes)
Looking for answers…from
tests
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Surface distress (cracking, raveling, potholes)
Dry
Wet
Intermediate 1
Half-wet
Intermediate 2
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Factors affecting the reliability of data related to pavement profiles and surface characteristics
Surface distress (cracking, raveling, potholes)
Dry
Wet
Intermediate 1
Half-wet
Intermediate 2
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Copenhagen, 19th October 2017
Thank you for your attention
Factors affecting the reliability of data related to pavement profiles and surface characteristics
Factors affecting the reliability of data related to pavement profiles and surface characteristics
ENEA SOGNO and MICHELE MORIenea.sogno@sina.co.it
michele.mori@sina.co.it
Copenhagen, 2017.10.19