[　Objective]　To　improve　the　existing　intelligent　compaction　quality　evaluation　methods　and　indicators　for　asphalt　pavement.　[　Method]　An　intelligent　compaction　system　for　asphalt　pavement　was　constructed　by　using　acceleration　sensing　and　positioning　systems.　A　longitudinal　zoning　compaction　scheme　suitable　for　asphalt　pavement　was　proposed.　Based　on　the　vibration　compaction　values　obtained　with　analysis　and　calculation　on　acceleration　signals,　a　relation　model　between　vibration　compaction　values　and　asphalt　pavement　compaction　degrees　was　established.　The　standard　deviation　rate,　nearest　neighbor　index,　and　coefficient　of　variation　indicators　were　proposed　to　comprehensively　evaluate　the　asphalt　pavement　compaction　quality.　[Result]　With　the　increase　of　compaction　times,　the　variation　amplitude　of　vibration　compaction　mean　value　gradually　decreases.　The　asphalt　pavement　maximum　compaction　times　can　refer　to　the　variation　on　vibration　compaction　value.　There　is　a　good　correlation　between　vibration　compaction　value　and　compaction　degree　of　asphalt　pavement,　with　a　correlation　coefficient　of　0.　72.　[Conclusion]　The　standard　deviation　rate　considers　the　differences　between　vibration　compaction　value　of　unqualified　area　and　target　value.　The　nearest　neighbor　index　considers　the　dispersion　degree　of　unqualified　area,　and　the　coefficient　of　variation　considers　the　variation　amplitude　of　unqualified　area.　They　are　respectively　applicable　to　evaluate　the　compaction　quality　of　asphalt　pavement　compaction　degree,　uniformity　degree,　and　stability　degree,　optimizing　the　existing　intelligent　compaction　quality　evaluation　methods　for　asphalt　pavement.　©The　Author(s)　2025.