Design of a Long Term Pavement Monitoring System for the Canadian Strategic Highway Research Program
Prepared for: Canadian Strategic Highway Research Program (C­SHRP)

Prepared by:
Dale .M. Nesbitt,

Decision Focus Inc.

and

Gordon A. Sparks,

Clayton, Sparks and Associates

August, 1990

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This document was produced under the auspices of the Canadian Strategic Highway Research Program (C­SHRP). C­SHRP was initiated in 1987 as a cooperative effort of the federal, provincial and territorial governments of Canada. Financial support for C­SHRP and for this project provided through the respective departments of transportation of the sponsors.

C­SHRP was created to systematically extract the benefit of work conducted in the United States of American within the Strategic Highway Research Program ( 1 986­1 993). This report details the data analysis plan for the Canadian Long Term Pavement Performance (C­LTPP) project. C­LTPP is one of several research projects undertaken in Canada intended to be complementary to the much larger Long Term Pavement Performance (LTPP) studies of the U.S. program.

Management for C­SHRP and this project has been provided through the offices of the Transportation Association of Canada in Ottawa.

Disclaimer

The contents of this document reflect the views of the author and not necessarily the views or opinions of the Canadian Strategic Highway Research Program, the Transportation Association of Canada or its sponsors.

TABLE OF CONTENTS

EXECUTIVE SUMMARY

1.0 THE SHRP REGRESSION APPROACH UPON WHICH SHRP­LTPP IS BASED WILL NOT MEET CANADIAN LTPP NEEDS

2.0 SMALL SAMPLE SIZE PROBLEMS WILL SYSTEMATICALLY BESET LONG TERM PAVEMENT PERFORMANCE MONITORING . .

3.0 THE SHRP STATISTICAL DESIGN IS SUSCEPTIBLE TO STATISTICAL BIAS

4.0 UNCERTAINTY IS INTRINSIC NO MATTER HOW MUCH MONITORING IS INITIATED

5.0 REGRESSION COMPLETELY IGNORES PRESENTLY EXISTING INFORMATION, CONVENTIONAL WISDOM, AND PRACTICE

6.0 FUNDING AGENCIES ARE UNLIKELY TO WAIT PATENTLY FOR TEN OR FIFTEEN YEARS FOR LONG TERM MONITORING RESULTS

7.0 LONG TERM PAVEMENT MONITORING MUST BE TIED TO A PAVEMENT "BOTTOM LINE"

8.0 C­LTPP RECOGNIZES THAT PAVEMENT DESIGN AND MAINTENANCE ARE FUNDAMENTALLY DECENTRALIZED DECISIONS

9.0 USER COSTS AND BENEFITS LIE AT THE HEART OF PAVEMENT MONITORING AND MANAGEMENT

SECTION 1

OVERVIEW OF THE PAVEMENT MONITORING PROGRAM AND ITS CONTRIBUTION TO PAVEMENT DESIGN AND ASSET MAINTENANCE

1.0 OBJECTIVES OF THE REPORT

1.1 RELATIONSHIP OF OUR FINDINGS TO THE STRATEGIC HIGHWAY RESEARCH PROGRAM LONG TERM PAVEMENT PERFORMANCE MONITORING PROGRAM

1.2 KEY OBJECTIVE: TO SUPPORT IMPROVED PAVEMENT CONSTRUCTION AND MAINTENANCE DECISIONS

1.3 SMALL SAMPLE SIZE PROBLEMS WILL BESET THE CANADIAN LONG TERM PAVEMENT PERFORMANCE PROGRAM (C­LTPP)

1.4 LONG TERM PAVEMENT PERFORMANCE MONITORING MUST BE DESIGNED TO SUPPORT BETTER PAVEMENT DESIGN AND MAINTENANCE DECISIONS

SECTION 2

TECHNICAL DISCUSSION OF THE PAVEMENT MANAGEMENT PROBLEM

2.1 THE CLASSICAL STATISTICAL (REGRESSION) APPROACH TO DEVELOPING PAVEMENT DETERIORATION FUNCTION AND INPUT PARAMETERS

2.1.1 Methodology

2.1.2 Numerical Example

2.1.3 Pitfalls with Regression Analysis

 

2.2 A BETTER WAY­BAYESIAN STATISTICAL METHODS

 

2.3 THE BAYESIAN STATISTICAL APPROACH TO PAVEMENT MONITORING

2.3.1 Mathematical Development

2.3.2 Representing Prior Knowledge Using a Prior Probability Distribution

2.3.3 Numerical Example

2.3.4 Concluding Comments on Bayesian Statistical Methods

SECTION 3

CAPITALIZING ON THE BENEFITS OF LONG TERM PAVEMENT PERFORMANCE MONITORING: INJECTION OF INTERIM AND FINAL RESULTS INTO PAVEMENT MANAGEMENT DECISION SYSTEMS

3.1 USE OF INTERIM RESULTS FROM PAVEMENT MONITORING BY DETERMINISTIC PAVEMENT MANAGEMENT SYSTEMS

3.2 SEMI­MARKOVIAN PROBABILISTIC PAVEMENT MANAGEMENT APPROACH

SECTION 4

RECOMMENDED CONFIGURATION OF AN INTEGRATED PAVEMENT MONITORING, PERFORMANCE PREDICTION, AND PAVEMENT MANAGEMENT SYSTEM

4.1 PAVEMENT MONITORING, PERFORMANCE PREDICTION, AND PAVEMENT MANAGEMENT

4.2 RECOMMENDED GAMEPLAN FOR CANADIAN SHRP LONG TERM PAVEMENT PERFORMANCE PROGRAM

PHASE I: ASSEMBLING AND PROCESSING C­LTPP INFORMATION USING BAYESIAN STATISTICAL METHODS

Task I.1. Paper Design of Bayesian Module

Task I.2. Selection of Tentative Commercial Statistical Package

Task I.3. Detailed Paper Design of Bayesian Statistical Module

Task I.4. Implementation and Testing of Bayesian Statistical Module

Task I.5. Interface of Bayesian Statistical Module with Selected Commercial Statistical Package

Task I.6. Incorporate Modifications to Deal with Data Complexities

Task I.7. Assembly of Hypothetical Data Base to Test Statistical Package with Bayesian Statistical Module

Task I.8. Preparation of User Documentation and Training Program

PHASE II: AUTOMATED DELIVERY OF C­LTPP RESULTS TO PROVINCIAL AND FEDERAL GOVERNMENT AGENCIES

Task II.1. Implement Automated Output to Support Deterministic Pavement Deterioration Functions

Task II.2. Implement Automated Output to Support Semi­Markovian Probabilistic Pavement Deterioration Functions

Task II.3. Implement Remote Access Procedure for Provincial and/or State Government Agencies to Access Pavement Deterioration Information.

PHASE III: OPERATION IN CONJUNCTION WITH INTEGRATED, PROBABILISTIC PAVEMENT DESIGN AND MANAGEMENT CAPABILITY

Task III.1. Acquire Semi­Markovian Module for Section­ Specific Pavement Management

Task III.2. Incorporate User Cost Calculation Capability

Task III.3. Interconnect Multiple Section Modules intoDistrict and System Pavement Management Systems

Task III.4. Design Advanced Graphical and Report Writing Capability

Task III.5. Develop Pavement Management "Principles" Consistent with the Best Available Data and Semi­Markovian Pavement Management System

Task III.6. Develop Training Program for Initial and Ongoing Training of Users

Task III.7. Implement and Manage Effective User's Group

4.3 THE PAYOFF­EXPLICIT QUANTIFICATION OF THE VALUE OF INFORMATION

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