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Automated Pavement CrackingAutomated Pavement Cracking Analysis from 2D to 3D
Ch ll d O t itiChallenges and Opportunities
Kelvin C P WangKelvin C.P. Wang
University of Arkansas & WayLink Systems
2010 Pavement Evaluation Conference
Hotel Roanoke & Conference Center (Doubletree), VA,Hotel Roanoke & Conference Center (Doubletree), VA,
Oct 26, 2010, Roanoke, Virginia
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The Team of 15-Year Effort Weiguo Gong Terry Tracy Dr. Jacqueline Zhiqiong Hou (now Arkansas
highways)D K i D H ll Dr. Kevin D Hall
Dr. Vu NguyenDanny X Xiao Danny X. Xiao
Dr. Jiang Yangsheng Ryan Reynolds Daniel Byram Jesus Ryan Reynolds, Daniel Byram, Jesus
Martinez Others Others
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Classics of Pavement Data Collection
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Problems Pavement Surface Data Critical in the entire pavement engineering p g g
spectrum Partly Responsible for current standing of
the discipline Challenges Automation not possible for a large portion
of pavement surface characteristics in broad d fi itidefinition
Precision & Bias: not possible to establishResult: wasted resources & frustration Result: wasted resources & frustration
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Opportunities Computing and Sensor Technology Very advanced and low cost of entryy y Similar sensor principles applied in other
industries Usefulness of Actual Representation of
Pavement Surface: 3D As good as actual pavements at the defined
resolution All current requirements for surface data:
possible in the digital domain
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Surface Characteristics in Broad Definition Profiles: transverse and longitudinalProfiles: transverse and longitudinal Texture: macro-texture and safety Friction Friction Surface distresses: cracking, rutting
(trans profile) patching faulting(trans. profile), patching, faulting, various other surface defects (LTPP Distress Manual AASHTODistress Manual, AASHTO Interim/Provisional Standards)
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A Big IfA Big IfWh t h if t lWhat happens if an actual pavement as far as eye can see p ycan be virtually stored in a computer at 1 mm resolutioncomputer at 1-mm resolution with necessary/required spatial resolution & positioning accuracy?accuracy?
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Methodologies for 3D Surface Data Acquisition
St i i b d Stereovision based on photogrammetric principle: tested, powerful, & accurate
LIDAR: powerful, long-range LIDAR: powerful, long range Line laser imaging: high-resolution
& speed& speed
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Photogrammetric Stereovision
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LIDAR
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Line Laser Imaging
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Obvious Choice of Using Line Laser for 3D Surface Data
Wid l d i f t i d Widely used in manufacturing, and food industry on conveyer belts
Easy on energy consumption Mature laser and filtering Mature laser and filtering
technologiesSt bl Stable
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Latest Developmentsp 3D Line Laser Solution: PaveVision3D Capture x, y, & z dimensions of pavement Capture x, y, & z dimensions of pavement
surface Resolution: 1-mm for x, y, and z Resolution: 1 mm for x, y, and z
Two Data Streams2D 8 bit G I t 1 2D 8-bit Gray Images at 1mm
3D Height Points at 1mm
Power Consumption: <1000 watts for all computing, sensor, lasers, & electronics
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3D Profile Rate Fixed 1-mm Resolution: transverse
and height directionsand height directions Resolution in the longitudinal
direction: proportional to driving speedspeed 6,000 profiles per second
T 1 l ti t 15MPH True 1-mm resolution at 15MPH
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Sensor Positions
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Sensor Positions
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Sensor Positions
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DHDV with PaveVision3D
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DHDV with PaveVision3D
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Rack Dimensions
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Demos
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Software Solutions & Precision/Bias/ Near Term Rutting Cracking Macro-texture Rutting, Cracking, Macro-texture
Mid-Term True 1-mm resolution in all 3 directions at
60MPH Ultimate Goals Most Surface Characteristics as Broadly Most Surface Characteristics as Broadly
Defined: Fully Automated and in Real-Time at Needed Precision & Bias LevelsTime at Needed Precision & Bias Levels
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Thank You !Thank You !
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