Variance-based global sensitivity analysis for rear-end crash investigation using deep learning.

Traffic accidents are rare events with inconsistent spatial and temporal dimensions; thus, accident injury severity (INJ-S) analysis faces a significant challenge in its classification and data stability. While classical statistical models have limitations in accurately modeling INJ-S, advanced machine learning methods have no apparent equations to prioritize/analyze different contributing factors to predict INJ-S levels. Also, the intercorrelations among the input factors could make the results of a typical sensitivity analysis misleading.

Effect of Nanoclay Particles on the Performance of High-Density Polyethylene-Modified Asphalt Concrete Mixture.

Utilizing polymers for asphalt concrete (AC) mixture modification has many drawbacks that hinder its wide implementations for roadway construction. Recently, research on employing complementary materials, such as nanomaterials, to balance negative impacts of polymers while enhancing the AC mixture's performance has received great attention. This study aimed to investigate the effect of incorporating nanoclay (NC) particles on the performance of a high-density polyethylene (HDPE)-modified AC mixture.