digital highway measurements turner-fairbank highway research center david gibson milton (pete)...
TRANSCRIPT
DIGITAL HIGHWAY MEASUREMENTS
TURNER-FAIRBANK HIGHWAY RESEARCH CENTER
David Gibson
Milton (Pete) Mills
Morton Oskard
ADVANCED RESEARCH PROJECT 1
Long-Term Measurement Needs
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Vision
Build a foundation to capture geometrics at required levels of accuracy not currently provided by the state of the practice With State of the art sensors With data fusion With advanced analyses .
Introduce a set of highway metrics for entire right of way, (beyond simply highway geometrics) to capture health condition accurately and objectively With State of the art sensors With data fusion With advanced analyses .
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Vehicle and Phase I Sensors
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Sound Intensity Pressure Device (SIPD)
Ground Penetrating Radar (GPR)
LIDAR
Infrared Sign Retro-Reflectivity (IR)
Downward facing
Camera for
Pavements
Potential Sensors
IR
GPR
LIDARSIPD
Camera 5
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Horizontal Alignment
PC = Point of Curvature, PT = Point of Tangency 7
Vertical Alignment
DETAIL
11 MILES
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Super-Elevation
Comparison with rod and level data over 2 miles
Rod and Level Data (Blue)
High Accuracy INU data (Orange)
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PennDOT Route 851: FHWA R&D Driving Simulator
PA Route 8513.2 Miles
1010
Highway Geometrics for driving simulator collected in April 2004
VDOT Application Safety Improvement
LEESBURG11
Highway Geometrics for IHSDM in April 2004
VA Route 9 From Leesburg to West Virginia Border -- 12 Miles
West VirginiaBorder
Data Types
Vertical & Horizontal alignments including: PC, PT, Curve information
Super Elevation Pavement Surface Condition Lane Definition ( Markings and Edge ) Roadside hardware Linear and XYZ Referencing of data
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Preliminary Results of Va. Rt.9 Safety Improvement Study
Algorithms modified to handle stop and go conditions
Geometry of site extracted Segmentation of alignments in progress Data found very repeatable Coverage of DGPS found intermittent
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Elevation View
Differential GPS superimposed in blue - Arrows indicate blocked Reception
PR
OJE
CT
ELE
VA
TIO
N I
N F
EE
T
PROJECT LONGITUDE IN FEET
HEAVY FOLIAGE
VALLEYS
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CROSS-SECTIONAL SCANSE
LEV
AT
ION
IN
IN
CH
ES
OFFSET FROM CENTERLINE OF VEHICLE IN INCHESPOSITION OF GUARD RAIL
GUARD RAIL
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Cross-Sectional ScansE
LEV
AT
ION
IN
IN
CH
ES
OFFSET FROM CENTERLINE OF VEHICLE IN INCHESCLEARANCES
EDGE OF CUT
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Lane Attributes
LANE MARKINGS LANE WIDTH
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Comparisons of DHM to DGPS and SOP.
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COMPARING DHM TO NDGPS AND SOP
SOP (State-Of-Practice)
NDGPS (National Differential GPS)Color-Coded by no. of satellites received:
3 4&5 6&7 8 9
DHM
19SEQUENCE OF SLIDES SHOWING CONTINUOUS HORIZONTAL ALIGNMENT DATA (1 of 9 )
COMPARING DHM TO NDGPS AND SOP
20SEQUENCE OF SLIDES SHOWING CONTINUOUS HORIZONTAL ALIGNMENT DATA ( 7 of 9 )
GPS Reception
No. of Satellites:• 3• 4 & 5• 6 & 7• 8• 9
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SOP
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Measuring vehicle wander in lane using DHM laser
Position of vehicle in lane
Edge of Pavement
PavementMarkings
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Scanning Laser + INU
Pavement Markings and Edge of Pavement features fused with Trajectory
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Multiple lanes
Six-Points Cross-Sections of two-lane Rural Road -- resolution = 2 feet.25
Cross-Sections
26SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS
Cross-Sections
27SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS
Cross-Sections
SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS28
Visualization
3-D Rendering of Roadway in AUTOCAD2929
What is next ? Optimize data reduction
process Reduce Data Study Ground Truth -
Manual survey using static scanning laser
Satellite imaging using VGIN Error & Statistical Analysis Validation & Accuracy Report
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Preparations for GPR Field Trial
Mounting step frequency GPRhardware prior to the field trial
Pavement core location - coring was carried out at
selected locations in advance
32Horizontal slice at 18
cm depth
Manhole
Utility Detection Data –Collected Previously
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x [m]
y [m
]
Z = 110cm
0 2 4 6 8 10 12 14 16 18 20
0
1
2
3
4
Horizontal slice at 110 cm depth
Power cable
Utility Detection Data
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Clay
Backfill
Old gas pipe
Tram rails
ExcavationUtility Detection Data Collection Site
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Conclusion It is possible to capture geometrics and
roadway surface and structure data at high levels of accuracy using State of the art sensors, data fusion and advanced analysis procedures
These results are significantly more accurate then the state of the practice
These results would benefit from being fused with aerial surveillance data
Pooled fund study to provide one or more prototype DHM vans for use by participating states (Contact [email protected])
Coordinate with Florida DOT on pooled fund studies on data.
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The End
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Questions at Breaks
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