To　understand　the　evolutionary　law　of　heterogeneous　traffic　flows　in　intelligent　network,　based　on　the　improved　NaSch　model,　the　simulation　experiments　are　conducted　respectively　for　the　early,　middle　and　late　stages　of　intelligent　network　connectivity,　and　the　basic　diagram　of　traffic　flow　is　obtained　via　numerical　simulation　to　analyze　the　intrinsic　connection　between　the　capacity　and　the　penetration　rate　of　connected　vehicles.　Through　Markov　chain,　the　orderly　arrangement　of　connected　vehicles　is　proved　to　improve　the　road　capacity,　and　random　simulation　experiments　verify　the　theoretical　derivation.　The　relative　entropy　in　terms　of　vehicle　arrangement　is　introduced　to　quantify　the　order　of　heterogeneous　traffic　flow,　and　clarify　the　essence　of　the　connected　and　autonomous　vehicle　(CAV)　improving　traffic　conditions.　The　results　show　that:　the　capacity　increases　with　the　penetration　of　CAV;　in　the　early　stage,　the　increase　of　penetration　has　a　little　effect　on　the　capacity　improvement　with　the　maximum　of　23.5%,　while　in　the　middle　and　late　stages,　it　improves　the　capacity　by　125.0%;　under　certain　traffic　density,　CAV　penetration　positively　correlates　with　traffic,　and　the　relative　entropy　negatively　correlates　with　traffic;　when　CAVs　are　in　a　separated　state,　the　relative　entropy　is　low　and　the　improvement　in　the　randomly　mixed　capacity　reduces　with　increasing　CAV　penetration　.　©　2022　Authors.　All　rights　reserved.