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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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Presentation on theme: "DIGITAL HIGHWAY MEASUREMENTS TURNER-FAIRBANK HIGHWAY RESEARCH CENTER David Gibson Milton (Pete) Mills Morton Oskard ADVANCED RESEARCH PROJECT 1."— Presentation transcript:

1 DIGITAL HIGHWAY MEASUREMENTS TURNER-FAIRBANK HIGHWAY RESEARCH CENTER David Gibson Milton (Pete) Mills Morton Oskard ADVANCED RESEARCH PROJECT 1

2 Long-Term Measurement Needs 2

3 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

4 Vehicle and Phase I Sensors 4

5  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

6 6

7 Horizontal Alignment PC = Point of Curvature, PT = Point of Tangency 7

8 Vertical Alignment DETAIL 11 MILES 8

9 Super-Elevation Comparison with rod and level data over 2 miles Rod and Level Data (Blue) High Accuracy INU data (Orange) 9

10 PennDOT Route 851: FHWA R&D Driving Simulator PA Route Miles n Highway Geometrics for driving simulator collected in April 2004

11 VDOT Application Safety Improvement LEESBURG 11 n Highway Geometrics for IHSDM in April 2004 n VA Route 9 From Leesburg to West Virginia Border Miles West Virginia Border

12 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

13 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

14 Elevation View Differential GPS superimposed in blue - Arrows indicate blocked Reception PROJECT ELEVATION IN FEET PROJECT LONGITUDE IN FEET HEAVY FOLIAGE VALLEYS 14

15 CROSS-SECTIONAL SCANS ELEVATION IN INCHES OFFSET FROM CENTERLINE OF VEHICLE IN INCHES POSITION OF GUARD RAIL GUARD RAIL 15

16 Cross-Sectional Scans ELEVATION IN INCHES OFFSET FROM CENTERLINE OF VEHICLE IN INCHES CLEARANCES EDGE OF CUT 16

17 Lane Attributes n LANE MARKINGS n LANE WIDTH 17

18 Comparisons of DHM to DGPS and SOP. 18

19 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 )

20 COMPARING DHM TO NDGPS AND SOP 20 SEQUENCE OF SLIDES SHOWING CONTINUOUS HORIZONTAL ALIGNMENT DATA ( 7 of 9 )

21 GPS Reception No. of Satellites: 3 4 & 5 6 &

22 SOP 22

23 Measuring vehicle wander in lane using DHM laser Position of vehicle in lane Edge of Pavement Pavement Markings 23

24 Scanning Laser + INU Pavement Markings and Edge of Pavement features fused with Trajectory 24

25 Multiple lanes Six-Points Cross-Sections of two-lane Rural Road -- resolution = 2 feet. 25

26 Cross-Sections 26 SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS

27 Cross-Sections 27 SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS

28 Cross-Sections SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS 28

29 Visualization 3-D Rendering of Roadway in AUTOCAD

30 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

31 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

32 32 Horizontal slice at 18 cm depth Manhole Utility Detection Data – Collected Previously

33 33 Horizontal slice at 110 cm depth Power cable Utility Detection Data

34 34 Clay Backfill Old gas pipe Tram rails Excavation Utility Detection Data Collection Site

35 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 n Coordinate with Florida DOT on pooled fund studies on data.

36 36 The End Questions at Breaks

37 37


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