TRB Pubsindex
Text Size:

Title:

Statistical Analysis of Automated Versus Manual Pavement Condition Surveys
Cover of Statistical Analysis of Automated Versus Manual Pavement Condition Surveys

Accession Number:

01023792

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States
Order URL: http://www.trb.org/Main/Public/Blurbs/157377.aspx

Find a library where document is available


Order URL: http://worldcat.org/isbn/0309094151

Abstract:

The Alabama Department of Transportation (ALDOT) has used a vendor to perform automated pavement condition surveys for the Alabama pavement network since 1997. In 2002, ALDOT established a quality assurance (QA) program to check the accuracy of the automated pavement condition data. The QA program revealed significant discrepancies between manual and automatically collected data. ALDOT uses a composite pavement condition index called pavement condition rating (PCR) in its pavement management system. The equation for PCR was developed in 1985 for use with manual pavement condition surveys; however, ALDOT continues to use it with data from automated condition surveys. Since the PCR equation was developed for manual surveys, the discrepancies between the manual and automated data led ALDOT to question the continuity between its manual and automated pavement condition survey programs. A regression analysis was completed to look for any systematic error or general trends in the error between automated and manual data. Also, Monte Carlo simulation was used to determine which distress parameters most influence the PCR and whether they require more accuracy. The regression analysis showed the following general trends: automated data overreport outside wheelpath rut depth, underreport alligator severity Level 1 cracking, and overreport alligator severity Level 3 cracking. Through Monte Carlo simulation, it was determined that all severity levels of transverse cracking, block cracking, and alligator cracking data require greater accuracy.

Monograph Accession #:

01023790

Language:

English

Authors:

McQueen, Jason M
Timm, David H

Pagination:

pp 55-62

Publication Date:

2005

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 1940
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

0309094151

Media Type:

Print

Features:

Figures (7) ; References (9) ; Tables (4)

Uncontrolled Terms:

Subject Areas:

Data and Information Technology; Design; Highways; Pavements; I22: Design of Pavements, Railways and Guideways; I23: Properties of Road Surfaces

Files:

TRIS, TRB, ATRI

Created Date:

May 7 2006 5:02PM

More Articles from this Serial Issue: