Quality Management of Pavement Condition Data Collection (2009) / Chapter Skim
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NETWORK- VERSUS PROJECT-LEVEL DATA COLLECTION Data collection for network-level decision making is generally different from data collection for project-level decision making in purpose, methods, and the actual data collected. Therefore, the quality requirements for the pavement condition data needed are also different.
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FIGURE 4 In-house versus contracted pavement condition data collection.
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Data Collection Outsourcing Rationale The factors considered by the agencies that responded to the survey for making the decision of whether or not to privatize the pavement condition data collection services are summarized in Figure 6. The main factor cited was costeffectiveness.
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The acceptance plan called for LADOTD personnel to evaluate the pavement images and condition data summary to look for discrepancies and the right-of-way images for quality assurance. Other examples are presented in the case studies reviewed in chapter five.
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Location referencing problems may affect the pavement condition data quality and the decisions supported by these data. For example, poor location data may make it difficult to overlap different pavement indicators (e.g., roughness and cracking)
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These changes may cause inconsistencies from year to year. Whereas many location referencing methods can be used successfully for pavement condition data collection, it is important that they are implemented using smart business practices to ensure the quality of the collected data.
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Quality time-series of pavement condition data are needed to develop reliable deterioration models, measure the impact of maintenance and rehabilitation treatments, develop multi-year work plans, and optimize the allocation of resources. Therefore, it is important that the new and legacy data are compatible or can be made compatible through an appropriate conversion.
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Pavement condition data quantity expectations generally vary according to: (1) the type of information required by the agency (and its intended use)
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. The implementation of mechanistic–empirical pavement analysis and design methodologies is expected to affect pavement management practices and, in particular, pavement condition data collection.
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• Network spatial and temporal coverage -- expectations for quality and quantity of pavement condition data generally vary according to the type of information required by the agency (and its intended use) , how often a particular piece of data is used, and the difficulty in obtaining that particular data.
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