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Page 55
Suggested Citation:"Glossary." National Academies of Sciences, Engineering, and Medicine. 2009. Quality Management of Pavement Condition Data Collection. Washington, DC: The National Academies Press. doi: 10.17226/14325.
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Page 55
Page 56
Suggested Citation:"Glossary." National Academies of Sciences, Engineering, and Medicine. 2009. Quality Management of Pavement Condition Data Collection. Washington, DC: The National Academies Press. doi: 10.17226/14325.
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Page 56

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55 Acceptance plan: An agreed-upon method of evaluating the acceptability of the pavement condition data. Acceptance testing: The activities required to determine the degree of compliance of the pavement data collected with contract requirements. Accuracy: The degree to which a measurement, or the mean of a distribution of measurements, tends to coincide with the true population mean. When the true population mean is not known, as is the case with pavement data collection, the degree of agreement between the observed measure- ments and an accepted reference standard (ground truth) is typically used to quantify the accuracy of the measure- ments (16). Automated data collection: Process of collecting pavement condition data by the use of imaging technologies or other sensor equipment (6). Automated data processing: The reduction of pavement condition (surface distresses, such as cracking and patching, or pavement condition indices, such as IRI) from images or other sensors. The process is considered fully automated if the pavement condition (e.g., distresses) is identified and quantified through techniques that require either no or very minimal human intervention (e.g., using digital recognition software capable of recognizing and quantifying cracks on a pavement surface) (6). Bias: A systematic error, constant in direction, that causes a measurement, or the mean of a distribution of measure- ments, to be offset from the true population mean (16). Calibration: A systematic process to validate a specific measurement technique and equipment by comparing the measurements with a standard that is considered correct. This standard is commonly called “ground truth.” Adjust- ment to the equipment or technique may be required to match the “correct” measurement. Control site testing: The use of reference measurements on specific pavement sections (with well-defined locations) to assess the quality of a pavement condition data collection process. If the location of the session is not known to the data collection team, these are referred to as blind control sites or segments. Data processing: Covers all the activities that are conducted to convert the raw data collected in the field surveys to useful information. Ground truth: See “reference value.” Independent assurance: A management tool that requires a third party, not directly responsible for process control or acceptance, to provide an independent assessment of a product or service and/or the reliability of test results obtained from process control and acceptance testing (16). Manual data collection: Pavement condition data collection through processes where people are directly involved in the observation or measurement of pavement properties without the benefit of automated equipment (e.g., visual surveys and faultmeters) (6). Pavement condition: An evaluation of the degree of deteri- oration and/or quality of service of an existing pavement section at a particular point in time, either from an engi- neering or user (driver) perspective. The condition as it is perceived by the user is often referred to as functional con- dition. The estimated ability of the pavement to carry the load is referred to as structural condition. Pavement condition indicator: A measure of the condition of an existing pavement section at a particular point in time. This indicator may be a specific measure of a pave- ment condition characteristic (e.g., smoothens or cracking severity and/or extent) or an index defined for a single dis- tress (e.g., cracking), for multiple distresses (e.g., Pavement Condition Index), or for the overall pavement condition. Pavement performance: The history of pavement condi- tion indicators over time or with increasing axle load applications (16). Precision: The degree of agreement among a randomly selected series of measurements of a particular characteris- tic (or attribute) or the degree to which tests or measurements on identical samples tend to produce the same results (16). Quality: “The degree to which a set of inherent characteristics fulfill requirements” (17). These requirements could be features and characteristics of a product that are specified in a contract or identified and defined internally by the company/agency based on the customer expectations. The product could be a physical entity (e.g., a calculator) or a service (e.g., auto repair, or, as is the focus of this synthesis, data collection). Quality acceptance: Those planned and systematic actions necessary to verify that the data meet the quality require- ments before they are accepted and used to support pave- ment management decisions. These actions govern the acceptance of the pavement condition data collected using either a service provider or in-house resources. Quality acceptance is often referred to as quality assurance in the pavement engineering and management field. Quality assurance: The part of quality management focusing on increasing the ability to fulfill requirements. It includes all those planned and systematic actions necessary to provide confidence that a product or facility will perform satisfac- torily in service. Because this term is often used in practice to refer to quality acceptance activities, to avoid confusion it is not used in the remainder of the synthesis. Quality audits: A quality audit is the process of systematic examination of a quality system carried out by an internal or external quality auditor or an audit team. It is a key element in the ISO quality system standard to verify that the institu- tion has clearly defined internal quality monitoring proce- dures linked to effective action. GLOSSARY

Quality control: Those actions and considerations necessary to assess and adjust production processes so as to control the level of quality being produced in the end product. It is also called process control. For purposes of this synthesis, quality control activities are those used to control the data collection activities, either by a data collection ser- vice provider or a road agency collecting data in-house, so that quality pavement condition data can be obtained. Quality control plan: A document that describes the process to be followed for delivering the level of pavement condi- tion data quality required. This plan typically includes data quality objectives (precision, accuracy, completeness, etc.), organization and responsibility, sampling procedures, equipment requirements (calibration, verification, etc.), pro- cessing of the quality control data, statistical analysis to be conducted, reporting, documentation of potential problems, and remedial solutions. Quality management: The overarching system of policies and procedures that govern the performance of quality control and acceptance activities; that is, the totality of the effort to ensure quality in the pavement condition data. Quality system: The organizational structure, procedures, processes, and resources needed to implement quality management to meet the quality objectives. Reference value/ground truth: A measurement of a pave- ment characteristic (or attribute) that is considered to be the “correct” measurement for this characteristic. Repeatability: The variation in measurements taken by a single piece of equipment on the same road segment(s) and under the same conditions (over a short period of time) [adapted from Transportation Research Circular E-C037 (16)]. It is generally evaluated based on the stan- dard deviation of repeated values from different measure- 56 ments. Repeatability measures the ability of the equipment/ technology/raters to produce the same values on repeated measurements. Reproducibility: The ability of a technology or equipment to accurately reproduce or replicate measurements not in the same section [adapted from Transportation Research Circular E-C037 (16)]. The reproducibility of pavement condition measurements is typically measured as the stan- dard deviation of measurements taken with different equip- ment or using different technologies. It is a measure of how well two different devices/methods/raters are able to measure the same pavement condition value on the same road segment(s). Reproducibility relates to the agreement of test results with different operators, test devices, and/or testing conditions. Semi-automated data processing: Process of collecting pavement condition data using imaging technologies or other sensor equipment but involving significant human input during the processing and/or recording of the data. Time-history: A set of successive periodic measurements of pavement condition over time on the same roadway sec- tions. This time-history can be used to determine pavement performance. Validation: The process of verifying the soundness or effec- tiveness of a pavement data collection process thereby indicating official sanction. Verification: The process of determining or testing the truth or accuracy of pavement condition data collection by examining the data and/or providing objective evidence. Verification sampling and testing may be part of an inde- pendent assurance program (to verify quality control and acceptance testing) or part of a pavement condition data collection acceptance program.

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TRB’s National Cooperative Highway Research Program (NCHRP) Synthesis 401: Quality Management of Pavement Condition Data Collection explores the quality management practices being employed by public highway agencies for automated, semi-automated, and manual pavement data collection and delivery.

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