Vehicular　fog　computing　(VFC)　that　supports　inter-vehicular　task　offloading　emerges　as　a　promising　complement　to　handle　the　explosive　growth　of　computation-intensive　tasks　in　Intelligent　Transportation　Systems　(ITS).　Nonetheless,　as　the　fog　access　points　(F-APs)　in　crowed　areas　are　often　overloaded,　the　conventional　single　F-AP　VFC　may　become　incompetent　and　energy-inefficient.　To　tackle　the　issue,　a　novel　scheme　of　non-orthogonal　multiple　access　(NOMA)-enabled　multi-F-AP　VFC　with　partial　offloading　is　proposed　in　this　work.　However,　the　corresponding　energy　minimization　turns　out　to　be　a　highly　non-trivial　non-linear　mixed-integer　programming　problem.　To　this　end,　the　optimal　power　allocation　is　derived　by　exploiting　monotonicity　while　good　task　splitting　ratio　and　user　association　are　found　through　successive　convex　approximation　(SCA)-based　interior-point　method　and　game　theoretic　approach,　respectively.　Extensive　simulations　based　on　MATLAB　show　that,　in　the　considered　scenarios,　the　proposed　scheme　can　fulfill　a　more　balanced　offloading　and　better　exploit　the　available　computing　resources,　thereby　leading　to　an　approximately　30%　energy　consumption　reduction　compared　to　the　baselines.　IEEE