Weigh-in-motion (WIM) technology has been widely used in highway traffic monitoring to support design and reconstruction of pavement structures. WIM systems are capable of continuously collecting vehicle size and weight data. However, collecting, storing, and processing the large amount of data requires is costly, which is a critical concern of many state highway agencies (SHAs) due to their budget limitations and resource constraints. To address this issue, adopting sampled data instead of complete/population data has been recommended in most SHAs. However, it has been recognized that a gap inevitably exists between data samples and population. Therefore, a balance between data needs in pavement design and cost in data supply should be obtained. This study comprehensively investigates the effect of different sampling schemes on data accuracy based on traffic information collected by WIM systems in Texas. Three criteria involving both mathematical implication and engineering context are developed for evaluation of sampled data accuracy. A relationship between typical sampling schemes and data accuracy is established. The results and suggestions can provide more cost-effective and efficient WIM data collection for SHAs.
Abstract