FOR LONG-TERM PAVEMENT PERFORMANCE DATA ANALYSIS

STRATEGIC PLAN

November 9, 1999

EXPECTATIONS

It is anticipated that this plan will be used to:

1. Guide development of LTPP analysis problems by the TRB ETG on Data Analysis.

2. Guide selection of LTPP analysis problems by the TRB LTPP Committee.

3. Support the programming of national-level LTPP analysis by sponsors.

4. Guide the formulation of LTPP analysis project statements.

5. Support assessment of progress in analysis of the LTPP data.

6. Communicate products anticipated from LTPP analysis.



ANALYSIS OBJECTIVES

The objectives of the national-level analysis effort are as follows. Each objective is

important to the achievement of the overall goal.

1. Improve traffic characterization and prediction.

2. Improve materials characterization.

3. Improve consideration of environmental effects in pavement design and performance

prediction.

4. Improve evaluation and use of pavement condition data in pavement management.

5. Evaluate existing and/or develop new pavement response and performance models

applicable to pavement design and performance prediction.

6. Provide guidance for maintenance and rehabilitation strategy selection and

performance prediction.

7. Quantify the performance impact of specific design features (presence or absence of

positive drainage, differing levels of pre-rehab surface preparation, etc.).

The specific LTPP analysis results leading to products expected to address these

objectives are shown in the chart on the following page.



PURPOSE AND GOAL

The purpose of this plan is to guide recommendations by the TRB LTPP Committee

concerning the national-level analysis of data collected within the Long-Term Pavement

Performance studies.

The goal for this plan is to develop knowledge, relationships, prototype performance

models and other findings to facilitate improved pavement treatment strategy selection

and reliable performance prediction.

The Committee will use this plan to help it determine whether the limited resources

available for LTPP data analysis are used in the most effective manner. The Committee

will evaluate newly proposed analyses, work currently in progress, and completed work

for compliance with this plan. The Committee understands that the Federal Highway

Administration intends to use this plan for similar purposes.

The Committee invites all agencies that are partners and participants in the LTTP studies

to adopt this plan. If so adopted, this plan will provide uniform guidance for nationallevel LTPP data analysis.

The Committee formally adopted this strategic plan at its meeting of November 8-9,

1999. The plan is now in effect, and will be kept current by the Committee from this date

forward to the completion of LTPP. The Committee will review the plan annually, and

will update it when necessary.


Traffic characterization and

prediction

1.

Materials characterization

2.

Determination of

environmental effects in

pavement design and

performance prediction

3.

Evaluation and use of

pavement condition data in

pavement management

4.

Development of pavement

response and performance

models applicable to

pavement design and

performance prediction

5.

Maintenance and

rehabilitation strategy

selection and performance

prediction

6.

ANALYSIS RESULTS LEADING TO PRODUCTS STRATEGIC OBJECTIVES

LONG-TERM PAVEMENT PERFORMANCE STRATEGIC PLAN OBJECTIVES AND PRODUCTS

PLAN GOAL: To develop knowledge, relationships and models to facilitate improved pavement design and reliable performance predictions.

Quantification of the

performance impact of

specific design features

(presence or absence of

positive drainage, differing

levels of pre-rehab surface

preparation, etc.)

7.

A. Guidelines for data

collection (hardware, software,

placement, calibration, data

collection frequency)

Some elements require work

beyond LTPP data analysis,

but analysis is needed to

provide some components.

B. Guidelines for applying

traffic loading and

classification data in

pavement design

C. Procedures for forecasting

and back-casting traffic

loading data

D. Quantitative information

on the impact of pavement

roughness on actual

(dynamic) loads applied to

the pavement

A. Quantitative information as

to the relative importance of

different material characteristics

in predicting pavement

performance

B. Relationships to enable

interchangeable use of

laboratory and field-derived

material parameters

C. Procedures for determining

as-built material properties

D. Quantitative information on

the performance impact of

different levels of material

variability and quality

E. Estimate material design

parameters from other materials

data (for example, Mr

 from

gradation and density)

F. Information as to the

relationship between

as-designed and as-built material

characteristics

Follows A

A. Quantitative information on

the impact of temperature and

moisture variations

(independent of frost

penetration) on pavement

performance

Related to IV-E

B. Quantitative information on

the impact of freeze-thaw cycles

on pavement performance.

Related to IV-E

C. Quantitative information on

the long-term changes in

pavement characteristics due

to environmental effects and

aging

Related to IV-E

D. Recommendations for

climatic data collection to

adequately predict pavement

performance

Depends on A and B

but not C

E. Region-specific guidelines

for considering environmental

effects in pavement modeling

Depends on A and B

but not C

C. Guidelines for the

selection of pavement design

features

B. Quantitative information on

the impact of design features on

pavement distress

A. Quantitative information

on the impact of design

features on measured

pavement responses

(deflections, load-transfer,

strains, etc.)

B. Guidance on the timing and

selection of pavement

maintenance and rehabilitation

options, and expected

performance life of each

Follows A

A. Quantitative information on

the performance of maintenance

and rehabilitation treatments,

including the effect of

pre-treatment condition

C. Calibrated relationships

(transfer functions) between

pavement response and

individual distress types

Closely related to A and B

B. Mechanistic-empirical

procedures for using commonly

collected pavement data to predict

specific distresses

Closely related to A and C

A. Guidelines for selection of

appropriate load-response

models for use in pavement

design as a function of the

acceptable level of risk and

model complexity

Closely related to B and C

E. Quantitative information on

variation in pavement

performance measures as a

function of environmental

factors

Related to III-A, B, and C

D. Criteria for applying

performance measures

(including variability) to

construction quality evaluation

C. Models relating functional

and structural performance

B. Improve measures of

pavement structural condition

for use in network-level

pavement management

A. Guidelines defining

measurements required to

compare performance of

different pavements, including

information on strengths and

limitations of each

recommended pavement

condition measure

3

2

1

3

2

1

1

1

1

1

1

1

1

2

2

1

2

2

2

2

1

1

1

1

2

3

2

1

Note: Explanatory comments are in bold italic text.

Sequence numbers denote the order in which Products should be addressed for a

given Objective. Products with the same sequence number can be addressed at the

same time.

Product Priorities

1

Critical

Very High

High

Sequence 2 3

C

VH

H

C

C

C

C

VH

VH

VH

VH

VH

VH

VH

VH

VH

VH

VH

VH

VH

VH

H

H H

H

H

H

H H

H

H