The　skid　resistance　of　asphalt　pavement　is　affected　by　the　surface　macrotexture　depth,　especially　when　there　is　water　on　the　pavement.　Pavements　with　appropriate　macrotexture　can　effectively　ensure　the　traffic　safety.　However,　previous　research　on　characterisation　methods　still　cannot　properly　reflect　the　three-dimensional　(3D)　information　of　pavement　macrotexture,　such　as　3D　features　or　distribution　density　of　texture.　In　this　study,　a　3D　laser　scanner　is　used　to　collect　the　data　of　asphalt　pavement　texture,　which　will　be　used　to　reconstruct　the　3D　pavement　model　in　the　next　step.　Thereafter,　the　model　is　evenly　meshed　by　a　large　number　of　micro　elements.　Based　on　the　volume　of　elements,　a　method　is　proposed　to　characterise　the　3D　features　of　pavement　macrotexture;　the　3D　characteristics　of　macrotexture　can　also　be　analysed　quantitatively.　Compared　with　four　types　of　gradation　of　asphalt　pavement,　the　results　show　that　the　proposed　method　can　accurately　represent　the　3D　macrostructure　of　asphalt　pavement　surface.