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DIGITAL HIGHWAY MEASUREMENTS TURNER-FAIRBANK HIGHWAY RESEARCH CENTER David Gibson Milton (Pete) Mills Morton Oskard ADVANCED RESEARCH PROJECT 1
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Long-Term Measurement Needs 2
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Vision n Build a foundation to capture geometrics at required levels of accuracy not currently provided by the state of the practice u With State of the art sensors u With data fusion u With advanced analyses. n Introduce a set of highway metrics for entire right of way, (beyond simply highway geometrics) to capture health condition accurately and objectively u With State of the art sensors u With data fusion u With advanced analyses. 3
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Vehicle and Phase I Sensors 4
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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 LIDAR SIPD Camera 5
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Horizontal Alignment PC = Point of Curvature, PT = Point of Tangency 7
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Vertical Alignment DETAIL 11 MILES 8
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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) 9
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PennDOT Route 851: FHWA R&D Driving Simulator PA Route 851 3.2 Miles n Highway Geometrics for driving simulator collected in April 2004
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VDOT Application Safety Improvement LEESBURG 11 n Highway Geometrics for IHSDM in April 2004 n VA Route 9 From Leesburg to West Virginia Border -- 12 Miles West Virginia Border
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Data Types n Vertical & Horizontal alignments including: PC, PT, Curve information n Super Elevation n Pavement Surface Condition n Lane Definition ( Markings and Edge ) n Roadside hardware n Linear and XYZ Referencing of data 12
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Preliminary Results of Va. Rt.9 Safety Improvement Study n Algorithms modified to handle stop and go conditions n Geometry of site extracted n Segmentation of alignments in progress n Data found very repeatable n Coverage of DGPS found intermittent 13
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Elevation View Differential GPS superimposed in blue - Arrows indicate blocked Reception PROJECT ELEVATION IN FEET PROJECT LONGITUDE IN FEET HEAVY FOLIAGE VALLEYS 14
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CROSS-SECTIONAL SCANS ELEVATION IN INCHES OFFSET FROM CENTERLINE OF VEHICLE IN INCHES POSITION OF GUARD RAIL GUARD RAIL 15
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Cross-Sectional Scans ELEVATION IN INCHES OFFSET FROM CENTERLINE OF VEHICLE IN INCHES CLEARANCES EDGE OF CUT 16
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Lane Attributes n LANE MARKINGS n LANE WIDTH 17
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Comparisons of DHM to DGPS and SOP. 18
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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 19 SEQUENCE OF SLIDES SHOWING CONTINUOUS HORIZONTAL ALIGNMENT DATA (1 of 9 )
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COMPARING DHM TO NDGPS AND SOP 20 SEQUENCE OF SLIDES SHOWING CONTINUOUS HORIZONTAL ALIGNMENT DATA ( 7 of 9 )
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GPS Reception No. of Satellites: 3 4 & 5 6 & 7 8 9 21
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SOP 22
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Measuring vehicle wander in lane using DHM laser Position of vehicle in lane Edge of Pavement Pavement Markings 23
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Scanning Laser + INU Pavement Markings and Edge of Pavement features fused with Trajectory 24
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Multiple lanes Six-Points Cross-Sections of two-lane Rural Road -- resolution = 2 feet. 25
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Cross-Sections 26 SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS
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Cross-Sections 27 SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS
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Cross-Sections SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS 28
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Visualization 3-D Rendering of Roadway in AUTOCAD
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What is next ? n Optimize data reduction process n Reduce Data n Study Ground Truth - u Manual survey using static scanning laser u Satellite imaging using VGIN n Error & Statistical Analysis n Validation & Accuracy Report 30
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31 Preparations for GPR Field Trial Mounting step frequency GPR hardware prior to the field trial Pavement core location - coring was carried out at selected locations in advance
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32 Horizontal slice at 18 cm depth Manhole Utility Detection Data – Collected Previously
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33 Horizontal slice at 110 cm depth Power cable Utility Detection Data
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34 Clay Backfill Old gas pipe Tram rails Excavation Utility Detection Data Collection Site
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35 Conclusion n 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 n These results are significantly more accurate then the state of the practice n These results would benefit from being fused with aerial surveillance data n Pooled fund study to provide one or more prototype DHM vans for use by participating states (Contact Mort.Oskard@fhwa.dot.gov) Mort.Oskard@fhwa.dot.gov n Coordinate with Florida DOT on pooled fund studies on data.
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36 The End ---------- Questions at Breaks
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