In　view　of　the　fact　that　the　point　cloud　3D　model　will　be　interfered　by　environmental　factors,　measurement　methods　and　other　random　factors　in　the　process　of　data　scanning　and　acquisition,　there　will　be　some　invalid　points,　outliers　and　internal　noise　points.　In　this　paper,　a　point　cloud　denoising　method　based　on　adaptive　density　clustering　and　statistical　filtering　is　proposed　to　process　vehicle　point　cloud　data.　which　can　effectively　preserve　vehicle　features　while　obtaining　optimal　denoising　effect.　Compared　with　the　existing　point　cloud　noise　processing　algorithms,　this　algorithm　can　remove　noise　better,　and　has　shorter　time-consuming　and　good　applicability.　©　Published　under　licence　by　IOP　Publishing　Ltd.