Asphalt mixture compaction based on motion sensing intelligent aggregate (MSIA)

Motion sensing intelligent aggregates (MSIAs) enable the real-time acquisition of asphalt mixture internal dynamic response data during pavement compaction, providing detailed information on aggregate motion within the compacted layer. These data support the development of an accurate evaluation feedback system for optimizing the field compaction strategy. Therefore, MSIAs can potentially promote the automation and high-quality development of road compaction construction. This paper aims to elucidate the current applications and prospects of MSIAs in pavement compaction research. Using bibliometric statistics of pavement compaction, research hotspots related to technical approaches, material composition, and methodological advances are systematically reviewed. Recommendations are proposed based on the summary of MSIA development, data analysis, and application in asphalt mixture compaction. Future research is needed to minimize size effect influences, develop prediction models, and advance array-arrangement designs of MSIAs that align with the complex conditions of asphalt mixture compaction. • Conducted systematic literature review of motion sensing intelligent aggregate (MSIA) applied in asphalt mixture compaction. • Material composition, technical approaches, and methodological developments in asphalt mixture compaction are reviewed. • Components, data acquisition, signal filtering, and application of MSIA are summarized and investigated. • Integration, array arrangement design, and compaction degree prediction models based on MSIA are required. • Prospects of using MSIA for feedback information acquisition in asphalt mixture intelligent compaction are discussed.