Automated pavement condition surveys have progressed in the past few years. Mainly developed for superior road network needs, such as highway pavements, they are now very often used in the context of surveys and analysis for municipal network pavements. At this level, quality control of the data is of primary importance to obtain accurate and repeatable results that will allow trend detection and fill the needs of municipal pavement managers.
Profiler surveys to measure road roughness and laser scan technologies to determine cracking and rutting need a focus adapted to municipal networks. Special cases relative to this domain will be presented (acceleration and deceleration areas of survey vehicles, pedestrian crossings with interblock, railway crossings, speed bumps, surface defects related to snow-removal equipment, lateral obstacles and dirty surfaces). In the absence of adequate quality control of the data, each of these special cases introduces inaccurate global indicators for each segment, such as IRI (ASTM E950) and PCI (ASTM D6433).
This paper pinpoints the impact of these special cases in the computed values of the indices. In a few cases, IRI and PCI diverging for as much as 100 % have been noted between data before quality control and after quality control.
From these findings, a few approaches to supervise quality control are introduced for the data treatment phase. These approaches are complimentary to equipment specifications prescribed by municipalities
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