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

Long-Term Measurement Needs 2

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

Vehicle and Phase I Sensors 4

 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

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

Vertical Alignment DETAIL 11 MILES 8

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

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

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

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

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

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

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

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

Lane Attributes n LANE MARKINGS n LANE WIDTH 17

Comparisons of DHM to DGPS and SOP. 18

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 )

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

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

SOP 22

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

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

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

Cross-Sections 26 SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS

Cross-Sections 27 SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS

Cross-Sections SEQUENCE OF SLIDES SHOWING CROSS-SECTIONS 28

Visualization 3-D Rendering of Roadway in AUTOCAD

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

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

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

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 The End Questions at Breaks

37