National Academy of Sciences | 150 Year Anniversary

Questions? Call 800-624-6242

| Items in cart [0]

The National Academies Press

Rights & Permissions

topleft topright

NCHRP Synthesis 401: Quality Management of Pavement Condition Data Collection (2009)
National Cooperative Highway Research Program Synthesis Program (NCHRPSYN)

Citation Manager

Flintsch, Gerardo W, McGhee, Kevin Kenneth, Transportation Research Board. "Pavement Condition Indicators." NCHRP Synthesis 401: Quality Management of Pavement Condition Data Collection. Washington, DC: The National Academies Press, 2009.

Please select a format:

BibTeX EndNote RefMan


Page
15
bottomleft bottomright
Page
15
Front Matter (R1-R9)
Summary (1-4)
Scope and Organization (5-5)
Background (6-9)
In-House versus Service Provider Collected Data (10-12)
Issues Associated with Location Referencing (13-14)
Pavement Condition Indicators (15-15)
Time-History Data Collection Issues (16-16)
New Demands Imposed by Changing Business Practices (17-17)
Summary (18-19)
Background on Quality Management Concepts and Processes (20-20)
Quality Management Plans (21-21)
Data Management Activities (22-22)
Reference Values/Ground Truth (23-23)
Sources of Variability in Pavement Condition Data Collection (24-26)
Effects of Network Size on Quality Management (27-28)
Summary (29-29)
Quality Control (30-36)
Quality Acceptance (37-40)
Independent Verification (41-41)
Summary (42-42)
Maryland (43-44)
Virginia (45-46)
Oklahoma (47-47)
British Columbia (48-48)
Summary (49-50)
Summary of Findings (51-52)
Issues Identified (53-53)
Suggestions for Future Research (54-54)
Glossary (55-56)
References (57-60)
Appendix A - State and Provincial Agency Survey Questionnaire (61-71)
Appendix B - Service Providers Survey Questionnaire (72-76)
Appendix C - Tabular Results of the State and Provincial Agency Survey (77-103)
Appendix D - Example of Pavement Condition Data Collection Request for Proposal - Louisiana Department of Transportation and Development (104-132)
Appendix E - Example of Pavement Condition Data Collection Request for Proposal (Oklahoma DOT) (133-144)
Abbreviations used without definitions in TRB publications (145-145)

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 15
15 method, which may work well for use within an agency Pavement Distress. The LTPP Distress Identification Man- or department, but may not be suitable for sharing the data ual (19) is widely recognized for providing a good reference with other agencies or departments (which may use differ- for project- and research-level distress data collection. ent referencing methods). The main advantage of this type of referencing is that it facilitates section identification and The distresses collected by the various agencies responding is familiar to most users and operators. A disadvantage is that to the survey are summarized in Figure 9. Rutting was the only markers may move (e.g., as a result of realignments), poten- universally collected distress closely followed by transverse tially changing the size and location of individual pavement cracking and fatigue cracking. Most agencies also collect data segments. These changes may cause inconsistencies from on longitudinal cracking and some collect bleeding and flush- year to year. ing. In general, the asphalt pavement distresses most frequently collected (rutting, fatigue, and transverse cracking) are con- Whereas many location referencing methods can be used sistent with those used in the hot-mix asphalt mix design successfully for pavement condition data collection, it is and structural design of pavements [e.g., in NCHRP 1-37A important that they are implemented using smart business MEPDG (27 )]. practices to ensure the quality of the collected data. More than one-third of the agencies surveyed (38%) reported problems After the various types of cracking, the most commonly with location referencing, many of which involved ensuring measured portland cement concrete (PCC) pavement distresses system consistency between departments within the same collected are faulting and spalling. This selection reflects the agency. Other problems listed included those associated with typical concern with the condition of concrete pavement at conversion from linear referencing systems to other systems the joints. (e.g., spatial coordinates), time-history updates, and inter- departmental standardization. Smoothness PAVEMENT CONDITION INDICATORS Pavement smoothness is typically considered the pavement Pavement Distresses condition indicator that best reflects the public's perception of the overall condition of a pavement section. It affects ride The types and number of distresses surveyed varies signifi- quality, operation cost (e.g., fuel consumption, tire wear, and cantly from agency to agency. This variation is the result of vehicle durability), and vehicle dynamics. Smoothness is historical practices, use of different materials and pavement computed by measuring the vertical deviations of the road designs, and variations in the environmental conditions. surface along a longitudinal line of travel in the wheel path, Although there have been efforts to standardize the defini- which is known as the "profile." The profile is typically deter- tions and measuring procedures for the various distresses by mined using laser-based measuring systems (high-speed or ASTM International and AASHTO, the use of national (or light-weight profilers). international) standards for distress data collection is still not a common practice. Recent steps include the publication of These profilers measure the pavement profile directly using the ASTM Standard E1778, Standard Terminology Related to lasers to record the distance from the vehicle to the pavement Question: What pavement distress data does your agency collect? Rutting 100% Transverse Cracking 93% Fatigue Cracking 89% Longitudinal Cracking 88% Map/Block Cracking 77% Raveling 64% Faulting 64% Spalling 54% Bleeding/Flushing 54% Edge Cracking 46% Other 36% Punch-outs 32% Shattered Slab 30% Durability Cracking 27% Pumping 21% 0% 20% 40% 60% 80% 100% FIGURE 9 Types of distress data collected.