The　edge　computing　of　internet　of　vehicles　is　confronted　with　some　challenges,　such　as　the　unbalanced　arrangement,　the　service　inflexible　and　the　time　delay　for　the　real-time　computing　of　roadside　nodes.　In　this　paper,　a　new　queuing　model　and　scheduling　algorithm　of　mobile　edge　computing　(MEC)　is　proposed　based　on　intelligent　vehicles　integrating　the　sensing,　computing　and　control　together.　The　GI/GI/1　task　queuing　model　is　firstly　set　up　for　the　distributed　services　of　vehicular　networks,　in　which　intelligent　vehicles　are　virtualized　into　virtual　vehicles.　Moreover,　according　to　the　Voronoi　allocation　algorithm,　the　tasks　generated　by　virtual　vehicles　are　allocated　and　bound　to　intelligent　vehicles.　The　optimal　scheduling　and　distributed　elastic　service　of　intelligent　vehicles　are　presented　to　solve　the　problem　of　unbalanced　distribution　of　tasks　in　edge　computing.　The　simulation　experiment　of　the　vehicle　pollutant　emission　illustrates　the　effectiveness　of　the　proposed　method.　©　2022　Science　Press.　All　rights　reserved.