Sparse signal recovery for WIM measurements from undersampled data through compressed sensing
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DOI: 10.1016/j.measurement.2019.107181
Abstract: Abstract This study presents a method to recover the signal components critical for weigh-in-motion (WIM) measurements using compressed sensing. Through a comparative study, the wavelet basis ‘bior2.4’ is selected to sparsely represent the measured signals.… read more here.
Keywords: sparse signal; wim measurements; compressed sensing; wim ... See more keywords
Mechanistic-Empirical Compatible Traffic Data Generation: Portable Weigh-in-Motion versus Cluster Analysis
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DOI: 10.1520/jte20190745
Abstract: Axle load distribution factors (ALDFs) are used as one of the primary traffic data inputs for mechanistic-empirical (ME) pavement design methods for predicting the impact of varying traffic loads on pavement performance with a higher… read more here.
Keywords: traffic; mechanistic empirical; wim; traffic data ... See more keywords