As　large　passenger　flow　commonly　arises　in　metropolitan　metro　stations　during　peak　hours,　most　of　bottleneck　congestion　appears　in　the　entrance　halls　of　metro　stations.　Previous　research　work　on　mitigating　metro　congestion　mostly　focus　on　optimizing　single　facility　and　lack　a　comprehensive　analysis　on　how　congestion　arises.　We　propose　a　system　dynamics　based　framework　for　optimizing　the　aisle　length　and　mitigating　bottleneck　congestion　in　the　entrance　halls.　We　first　define　the　key　bottleneck　region　(KBR)　of　metro　stations　consisting　of　security　check　area,　automatic　fare　gate　area,　and　the　area　between　them.　Then　we　propose　a　system　dynamics　model　for　simulating　passenger　flows　in　KBR　by　determining　the　boundary　and　using　a　causal　analysis　of　a　KBR　system.　Finally　we　conduct　a　case　study　on　the　optimization　of　aisle　length,　based　on　the　field　observation　data　from　three　metro　stations　of　Beijing,　China.　The　results　reveal　that　the　minimum　aisle　length　of　commuter　metro　stations　for　acceptable　system＇s　passing　efficiency　is　6m,　and　suggest　the　optimized　aisle　length　for　three　different　commuter　metro　stations.　Our　study　provides　a　feasible　and　effective　approach　to　alleviate　passenger　flow　bottleneck　without　changing　the　number　of　facilities,　and　can　improve　the　efficiency　of　metro　stations　effectively.