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as a percentage of agencies collecting surface distress and Quality control includes those activities necessary to
smoothness. assess and adjust production processes to obtain the desired
level of quality of pavement condition data. Included are
checks on the equipment used to collect the data, the per-
SUMMARY sonnel responsible for the data collection, and the data col-
lection process itself conducted before, during, and after the
"Good" pavement condition data are very important in pro-
data collection.
viding effective pavement management. Pavement condition
data collection quality management is necessary to ensuring
Quality acceptance includes those activities conducted
that the collected data meet the requirements of the pavement
management system. This chapter presented the main data to verify that the collected pavement condition data meet
quality management concepts and principles as they apply to the quality requirements. Quality acceptance tools are used
pavement condition data collection. for testing both the pavement condition data that are col-
lected by the agency and those that are collected by a ser-
Effective data collection quality management programs vice provider. Common methods include testing of controls
provide a comprehensive, systematic approach to data collec- or verification sites, use of software to check for errors such
tion and processing. It is important that a complete pavement as incorrect asset data or ratings outside of an expected
condition data quality management system include a clearly range, and checking a certain percentage of data by quality
documented quality control plan, detailed quality acceptance assurance personnel.
procedures, and established guidelines to monitor the entire
process, with timelines, milestones, and evaluation criteria. The independent assurance testing aims at validating the
The Quality Management Plan is the "umbrella" document data for the user agency. For example, a procedure to verify
under which individual quality activities are conducted. the quality of the pavement data collection during production
Approximately one-third of the DOTs (35%) already have is the use of a sample or "control" section that is resurveyed
a formal plan and an additional 27% are in the process of or reanalyzed by an independent evaluator and the results
developing such a plan. compared with the production ratings.
The main techniques used for pavement data quality man- In general, sources of variability for pavement condition
agement are calibration of equipment and/or analysis criteria data collection can be related to equipment used, operation
before the data collection, testing of "control" segments before (including rater/operator training and skills), processing of
and during data collection, and software routines for checking the data collected, environmental conditions, and shape and
the reasonableness and completeness of the data. These tools condition of the pavement surface. All these potential sources
can be included in the quality control plans, quality acceptance have to be controlled (or at least accounted for) because they
procedures, or for independent assurance. will affect the quality of the data collected.
