Autonomous　vehicle　path　planning　involves　finding　a　collision-free　and　kinematic-feasible　path　from　the　start　to　the　goal.　Evidently,　collision-free　and　kinematic-feasible　are　the　two　most　important　parts　of　the　path　planning　process.　In　this　paper,　we　propose　a　collision　checking　method　that　considers　dwarf　or　negative　obstacles,　which　can　improve　the　traversabil-ity　and　stability　under　the　promise　of　ensuring　collision-free,　and　we　use　a　kind　of　motion　primitives　which　considering　non-holonomic　constraints　for　path　planning　to　generate　a　kinematic-feasible　path.　Specifically,　some　existing　approaches　of　collision　checking　deal　with　lofty　and　dwarf　obstacles,　or　wide　and　narrow,　negative　obstacles　in　the　same　manner　that　require　the　entire　vehicle　body　to　steer　awayfrom　them.　However,　some　dwarf　obstacles　are　shorter　than　the　chassis　of　the　vehicle　while　some　negative　obstacles　are　narrower　than　the　vehicle　track.　In　those　cases,　overstriding　maneuvers　will　prove　much　more　efficient　and　reasonable.　Moreover,　dealing　with　these　obstacles　in　the　same　wayas　lofty　obstacles　can　dramatically　reduce　the　flexibility　and　disturb　the　stability　of　path　planning　under　clustered　environments,　especially　when　the　vehicle　moves　at　higher　speed.　This　paper　proposes　a　double　layer　collision　checking　(DLCC)　method　that　deals　with　lofty　and　dwarf　obstacles,　or　wide　and　narrow,　negative　obstacles　separately,　effectively　increasing　the　flexibility　under　the　complex　scenarios　where　dwarf　and　narrow　negative　obstacles　exist.　©　2019　IEEE.