Automated Evaluation and Optimization of Subgrade Construction Based on Intelligent Compaction

Real-time evaluation and optimization for compaction quality are necessary to implement automated subgrade construction. The compaction evaluation is followed by the modified compaction plan to ensure quality and enhance efficiency. This study proposes an intelligent hybrid methodology to automatically estimate the compaction quality and back-optimize the compaction procedure. A series of field tests are performed at the subgrade construction sites. Multiple operating conditions are considered, including varying vibration modes and compaction speeds. Referring to these data sets, the compaction quality is evaluated continuously, and the rolling parameters are dynamically optimized using the genetic algorithm. The compactness and homogeneity of the compacted soil are improved with the proposed intelligent methodology, providing an advanced solution to monitor and optimize the subgrade construction based on the currently available evaluation index.