A　congestion　phenomenon　in　a　transit　station　could　lead　to　low　transfer　efficiency　as　well　as　a　hidden　danger.　Effective　management　of　congestion　phenomenon　shall　help　to　reduce　the　efficiency　decline　and　danger　risk.　However,　due　to　the　difficulty　in　acquiring　microcosmic　pedestrian　density,　existing　researches　lack　quantitative　indicators　to　reflect　congestion　degree.　This　paper　aims　to　solve　this　problem.　Firstly,　platform,　stair,　transfer　tunnel,　auto　fare　collection　(AFC)　machine,　and　security　check　machine　were　chosen　as　key　traffic　facilities　through　large　amounts　of　field　investigation.　Key　facilities　could　be　used　to　reflect　the　passenger　density　of　a　whole　station.　Secondly,　the　pedestrian　density　change　law　of　each　key　traffic　facility　was　analyzed　using　pedestrian　simulation,　and　the　load　degree　calculating　method　of　each　facility　was　defined,　respectively,　afterwards.　Taking　pedestrian　density　as　basic　data　and　gray　clustering　evaluation　as　algorithm,　an　index　called　Transit　Station　Congestion　Index　(TSCI)　was　constructed　to　reflect　the　congestion　degree　of　transit　stations.　Finally,　an　evaluation　demonstration　was　carried　out　with　five　typical　transit　transfer　stations　in　Beijing,　and　the　evaluation　results　show　that　TSCI　can　objectively　reflect　the　congestion　degree　of　transit　stations.