As　one　of　the　most　promising　solutions,　edge　caching　is　emerging　to　reduce　the　content　retrieval　latency　and　relieve　the　huge　burden　on　the　backhaul　links　in　the　6th　generation　(6G)　millimeter　wave　(mmWave)　intelligent　vehicular　networks.　In　this　paper,　we　first　formulate　the　optimization　problem　in　terms　of　request　hit　probability　and　investigate　two　crucial　factors,　which　impact　the　effectiveness　of　cache　placement　in　device-to-device　(D2D)　enabled　mmWave　vehicular　networks.　Then,　the　general　mathematical　expressions　for　optimization　of　the　request　hit　probability　with　the　constraints　of　caching　capacity　are　derived.　Moreover,　a　group　caching　scheme　(GCS)　is　proposed　to　obtain　the　sub-optimal　results　by　utilizing　relaxation　method　and　Karush-Kuhn-Tucker　(KKT)　conditions.　Inspired　from　the　Matern　hard-core　processes　and　by　exploiting　the　spatially　correlated　characteristics　of　users　distribution,　hard-cored　based　caching　algorithm　(HCCA)　is　proposed　to　avoid　the　simultaneous　caching　for　a　particular　file.　In　addition,　a　joint　caching　and　scheduling　strategy　is　investigated　which　maximizes　the　number　of　concurrent　transmissions　by　D2D　enabled　vehicle　pairs　matching　and　antennas　adjustment.　Comprehensive　simulations　validate　our　theoretical　analysis　and　demonstrate　that　the　proposed　scheme　can　achieve　higher　performance　in　terms　of　request　hit　probability　and　the　number　of　concurrent　transmissions　compared　to　the　existing　methods.　Consequently,　the　proposed　caching　scheme　has　great　potential　in　future　intelligent　vehicular　applications.