The　rapid　growth　in　vehicle　data　fosters　the　development　of　vehicular　computational　offloading.　By　exploiting　the　superiority　of　non-orthogonal　multiple　access　(NOMA)　in　the　offloading　process,　NOMA-enabled　vehicular　computation　offloading　enables　collaborative　transmissions　of　multiple　fog　nodes　and　is　promising　for　distributed　wireless　communications　environments.　Nonetheless,　to　the　best　of　our　knowledge,　the　problem　of　task　allocation　and　resource　allocation　in　NOMA-enabled　multipoint　collaborative　offloading　in　Vehicular　Fog　Computing　(VFC)　still　remains　open.　With　this　consideration,　the　NOMA-enabled　vehicular　fog　computing　problem　is　investigated　in　this　work,　as　well　as　an　energy-efficient　NOMA-enabled　vehicular　computing　offloading　scheme　is　proposed.　The　scheme　combines　task　vehicles,　main　fog　access　points　(F-APs),　idle　vehicles,　and　auxiliary　F-APs　to　collaborate　on　tasks.　However,　the　corresponding　optimization　problem　turns　out　to　be　a　non-convex　issue.　To　this　end,　through　in-depth　mathematical　analysis,　the　monotonicity　of　NOMA　power　allocation　is　discussed　to　find　the　optimal　power　allocation　coefficient.　Furthermore,　an　interior-point　method　based　on　successive　convex　approximation　(SCA)　is　proposed　to　obtain　the　sub-optimal　solution　of　task　division　and　bandwidth　allocation.　Simulations　are　conducted　to　validate　our　analysis　and　corroborate　the　effectiveness　of　the　proposed　scheme.