This　paper　presents　a　solution　to　improve　the　evacuation　efficiency　of　the　sorting　robot　and　the　chances　to　preserve　more　assets　in　an　emergency.　We　propose　a　danger　potential　field　model　for　the　intelligent　sorting　warehouse,　which　takes　the　number　of　AGVs　between　the　grid　and　the　exit　into　account.　By　taking　the　danger　map　calculated　by　the　model　as　prior　knowledge,　the　paper　combines　it　with　Deep　Q　Network　to　obtain　an　effective　evacuation　scheduling　strategy.　Finally,　comparing　the　performance　of　the　strategy　with　the　performance　of　traditional　automata　and　danger　potential　field　in　a　visual　simulator　based　on　the　real　sorting　warehouse　using　Pygame,　the　effectiveness　and　practicability　of　the　model　in　the　paper　is　verified.　©　2020　ACM.