DIGITAL HIGHWAY MEASUREMENTS TURNER-FAIRBANK HIGHWAY RESEARCH CENTER David Gibson Milton (Pete)...

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

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 .

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

LIDARSIPD

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 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

12

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

13

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

14

CROSS-SECTIONAL SCANSE

LEV

AT

ION

IN

IN

CH

ES

OFFSET FROM CENTERLINE OF VEHICLE IN INCHESPOSITION OF GUARD RAIL

GUARD RAIL

15

Cross-Sectional ScansE

LEV

AT

ION

IN

IN

CH

ES

OFFSET FROM CENTERLINE OF VEHICLE IN INCHESCLEARANCES

EDGE OF CUT

16

Lane Attributes

LANE MARKINGS 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

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

21

SOP

22

Measuring vehicle wander in lane using DHM laser

Position of vehicle in lane

Edge of Pavement

PavementMarkings

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

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

30

31

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

33

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

34

Clay

Backfill

Old gas pipe

Tram rails

ExcavationUtility Detection Data Collection Site

35

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 Mort.Oskard@fhwa.dot.gov)

Coordinate with Florida DOT on pooled fund studies on data.

36

The End

----------

Questions at Breaks

37