In　the　bus　network,　key　bus　station　failure　can　interrupt　transfer　lines,　which　leads　to　the　low　effectiveness　of　the　whole　network,　especially　during　peak　hours.　Thus,　identifying　key　stations　in　the　bus　network　before　the　emergency　occurs　has　a　great　significance　to　improve　the　response　speed.　In　this　paper,　we　proposed　a　new　method　considering　station　hybrid　influence　and　passenger　flow　to　identify　key　stations　in　the　whole　bus　network.　This　method　aims　to　measure　the　influence　of　bus　stations　while　combining　the　topological　structure　of　the　bus　network　and　dynamic　bus　stations　passenger　flow.　The　influence　of　bus　stations　was　calculated　based　on　the　local　structure　of　the　network,　which　refines　from　finding　the　shortest　paths　with　high　computational　complexity.　To　evaluate　the　performance　of　the　method,　we　used　the　efficiency　of　the　network　and　vehicle　average　speed　at　the　station　to　examine　the　accuracy.　The　results　show　that　the　new　method　can　rank　the　influence　of　bus　stations　more　accurately　and　more　efficiently　than　other　complex　network　methods　such　as　degree,　H-index,　and　betweenness.　On　this　basis,　the　key　stations　of　the　bus　network　of　Beijing　in　China　are　identified　out　and　the　distribution　characteristics　of　the　key　bus　stations　are　analyzed.