Automated Highway Pavement Management System …shinozuka.eng.uci.edu/Remote_Sensing_2003/Howard Chung.pdf · UC Irvine, Civil & Environmental Engineering 3 Motivation DOT agencies

G-AMPIS®

Integrated Sensing and Inspection of Highway Surface Distress

Howard Chung and Masanobu Shinozuka

Department of Civil and Environmental EngineeringUniversity of California, Irvine, CA 92697-2175

Workshop on Application of Remote Sensing Technologiesfor Disaster Response, Irvine, CA

September 12, 2003

2UC Irvine, Civil & Environmental Engineering

Contents

MotivationLiterature ReviewProposed ResearchPreliminary ResultSummaryFuture Plan


MotivationDOT agencies spent huge efforts & money in inspection, planning,maintenance and repair of the highways’ pavement.

Traditional man-made inspection and documentation methods make this work cumbersome and inefficient.

Traditional documentation of surveyed records is hard to be retrieved, reviewed, and updated by DOT agencies and transportation engineers.

AMPIS* is built to systematically and automated carry out highway surface distress inspection and management in situ.

GIS and image technology-based AMPIS is developed for better implementation of Pavement Management System (PMS).

*AMPIS: Automated Management of Pavement Inspection System


Literature Review

PMS - Department of the Army, Technical Manual of Pavement Maintenance Management (-1982)

Existing highway surface distress surveying methods (1990-). Mobile and automated.

Pavement distress detection using video image processing (1995-) http://www.gietech.com


Pavement Management System

US-Army’s PMS (1982) has five (5) main components:

PMS


Network IdentificationExample of Southern California Area

Los Angeles County, CALos Angeles County, CA

Orange County, CAOrange County, CA

In LAC & OC, the total length of highways is more than 5,750 Miles


Network IdentificationExample of Southern California Area


Pavement Condition Inspection

Detect structural integrity

Structural capacity Roughness Distress

Ratings

Main purposes of pavement condition inspection

expensive and time-consuming process

most of them is evaluated subject to

Professional’s Judgement


Worksheet of Distress Detection

Source: Dept of Army, Technical Manual of Pavement Maintenance & Management, 1982


Existing Surface Distress Surveying MethodsEconomic AnalysisGPS (Com)Automated

DetectionGIS/ESRISystem Name

YESNONOYES/YESUSACE

NoNOYESYES/NOSamsung SDS

NoYES (Trimble)NOYES/YESIMS-Terracon

NoYES (Applanix)YESYES/NORoadWare

NoNoYESNO/NOGIE Tech.

NoYES (Omnistar)YESYES/NOFugro Waylink

NoYES (Applanix)NOYES/YESMandli

YESYES (Trimble)YESYES/YESG-AMPIS


Proposed Research

Developed AMPIS’ components and analysis modules.

Develop sophisticated video image processing, correlational analysis techniques (2D signal processing).

Build up GPS, GIS and GUI interfaces

Create interface for economic analysis plug-ins.


AMPIS Blueprint; Components & Relationships

Acquisition Identification

2 - Pavement Condition Inspection

AutomatedDistress

Detection

Distress Rating

Previous surveys results

comparisonMosaicking

Images preprocessing

GPS Data

Frame Grabbing

5 - Data Management

4 - Economic Analysis

1 - Network Identification 3 - Maintenance

& Repair Determination

GIS


Network Identification

(x1,y1) (x2,y2)

(x3,y3) (x4,y4)(x5,y5)

GPS Receiver

GIS Maps


Acquisition ProcessGPS Positioning ProcessDigital/Video Camera

V(t)=55 MPH

1 2 6 7

X,Y

3 4 515 fps


Automated Pavement Inspection

2 - Geo-Referencing

3 –Distress Detection1- Acquisition process


Geo-Referencing


Distress Detection

Original Image Reclassify Thinning

Image analysis are programed by using Arc-Objects® and Visual Basic for Applications (VBA) in Arc-GIS®


Example of Crack Pattern

Alligator Cracks Longitudinal/Transverse Cracks

Block Crack Patch Crack


Pavement Distress Indices (PDI’s)

Crack i(x, y)

(i)(x’, y’)

(1) (2)

(3)

(4) (5)

(6)

(7)

(8)

aCracking area: Ac

)()2

',2

'(

)()''(tan

)(

)(:

1

iCrackofLocationyyxxXX

iCrackofnOrientatioxxyy

iCrackofWidthAveragelAw

analysisspatialbyObtainediCrackofLengthl

cc

i

i

ci

i

++=

−−

=

=

−αb

×=

+++==

∑

∑

0

8321

0

...

A

wlI

abllll

A

lI

ii

i

w

ii

l

8 cracks in an image after thinning and vectorizing

PDI:

(Image Area: A0=a x b)


Case Study & ResultsNetwork Theme

Aldrich Park


Pavement Crack Detection in ArcGIS

Base Layer

Crack Layer

Width Layer

Result Table


Graphical User Interface (GUI)


Distress Rating Report by AMPISVisualization by GIS-Theme Map


Visualization by 3-D GIS-Theme Map


Summary

AMPIS utilizing video image processing & ArcGIS capability is more innovative comparing with current distress detection methods.Proposed pavement distress indices facilitate an automated 1st stage pavement inspection by visualizing distress severity in GIS framework1st stage strategically screens locations of distressed pavement that require the 2nd stage inspection to be carried out by using more sophisticated but costly NDT methods.


Future Plans

Integrate GPS with mobile personal computers in AMPIS to improve in-situ detection enginesTest AMPIS in the busy and currently running highway networks (speed 55mph required)Assess cost-effectiveness of AMPIS implementation relative to other systems for pavement distress detections. Extend economic analysis issue such as life cycle cost studies (LLC).


Acknowledgement

This research is supported by the National Science Foundation (NSF) through the Multidisciplinary Center for Earthquake Engineering Research (MCEER), and also by California State Department of Transportation (Caltrans).


References

M. Shinozuka, H. Chung, J. Liang, M. Ichitsubo, (2001), “System identification by Video Image Processing”, Proceedings of the 48th SPIE Symposium on Smart Structures and Materials, Newport Beach, March 4-8, 2001, CA.

M. Shinozuka, M. Ichitsubo, (2002), “A Study on Automation of Pavement Surface Distress Detection”, Technical Report, Kure National College of Technology, Printed in Japanese.

TM 5-623, Department of the Army, Technical Manual, Technical Maintenance Management, November, 1982.

K. C. Wang, (2000), “Design and Implementations of Automated Systems for Pavement Surface Distress Survey”, ASCE Journal of Infrastructure Systems, pp. 24-32.

Chung, H-C., Shinozuka, M., Soeller, T. and Girardello, R., (2003). “GIS-based AMPIS for Highway Surface Health Inspection and Management”, Submitted to ASCE Journal of Infrastructure Systems.

AMPIS Supplementary Slides


U.S. PCES System

Developed by Earth Technology CorporationLine-scan cameras technologiesNo more developed because they used their own processing boards and system level software

Journal of infrastructures system/March 2000


Swiss CREHOSDeveloped by Dr. Max MontiDesign and implement new pavement management system “in a complete and lasting way”

Laser and holographic technologies

No more developed



Illinois Automated Road Inspection System

By Professor Sidney GuralnickUses shadow Moiré methodNot well developedCheaper than other systems



Komatsu System

Japanese consortiumDoes not output the types of crackingOnly works during the nightAutomated pavement crack sealing

AHMCT web site


Swedish PAVUE System

Developed by Swedish National Road and Transportation Research InstituteHigh Speed & high resolution, but stores data on analog format

www.opq.sewww.ims-terracon.com


G.I.E. 3-D Approach

Developed by GIE Technologies (Canada)BIRIS laser sensorsVery rugged sensor

G.I.E. Technologies


MANDLI

Phoenix Scientific laser scanning tech.

Other

YESPicture database

NOAutomated detection

YES (Applanix)GPS

YESYES

GIS (ESRI)

RoadviewSoftware name

Digilog VX-PVehicle name

Mandli Communications, Inc.490 North Burr Oak AvenueOregon, WI 53575

www.mandli.com


FUGRO/WAYLINK

Other

YESPicture database

YES Automated detection

YES (OmniSTAR)GPS

YESNO

GIS (ESRI)

Distress Survey Analyzer

Software name

ADVantage/DHDVVehicle name

FUGRO-BRE, INC.8613 Cross Park DriveAustin, Texas 78754

www.bre.fugro.com

WayLink Systems Corporation700 Research Center Boulevard MS 24Fayetteville, AR 72701

www.waylink.com


G.I.E. Technologies

On-Board event Keyboard

Other

YES (optional)Picture database


YES (± 1 eter)GPS

NONO

GIS (ESRI)

LaserVISIONSystem (LVS)System Name

GIE Technologies.60, St-Jacques West Montreal, Quebec H2Y 1L5 Canada

www.gietech.com


ROADWARE

Crack classification and rating

Other

YESPicture database


YES (Applanix)GPS

YESNO

GIS (ESRI)

WisecraxSoftware name

ARAN 4900Vehicle name

RoadWare Group Inc.147 East River RoadParis, Ontario N3L 3T6 Canada

www.roadware.com


IMS-Terracon

Other

YESRoad Inventory

NO Automated detection

YES (Trimble)GPS

YESYES

GIS (ESRI)

Pave Pro ManagerSoftware name

Laser Road Surface Tester (RST)

Vehicle name

Infrastructure Management Services.3350 Salt Creek Lane, Suite 117 Arlington Heights, IL 60005 USA

www.ims-terracon.com


HANSHIN KOHSOKU

Hanshin Expressway Administration and Technology center4-5-7, Minami-Honmachi, Chuoh-kuOsaka 541-0054 Japan

www.tech-center.or.jp

Not a commercial offer

Other

NORoad Inventory


YES GPS

NONO

GIS (ESRI)

Intelligent Inspection VehicleVehicle name


Samsung SDS uniAMS

Samsung SDS America, Inc.85 West Tasman Dr. San Jose, CA 95134 USA

www.samsungsdsa.com

Other

NORoad Inventory


AASHTO,SHRP,LTPPProtocols

YESNO

GIS (ESRI)

uniSurveyuniPavement

Software name


USACE Micro PAVER

USACE Construction Engineering Research LaboratoryPO Box 9005 Champaign, IL 61826-9005 USA

www.cecer.army.mil/paver/Paver.htm

Other

YESRoad Inventory

NO Automated detection

Protocols

YESYES

GIS (ESRI)

Micro PAVER 5.0Software name

Documents

Automated Highway Pavement Management System …shinozuka.eng.uci.edu/Remote_Sensing_2003/Howard Chung.pdf · UC Irvine, Civil & Environmental Engineering 3 Motivation DOT agencies