The　accurate　depiction　and　understanding　of　the　influence　mechanism　of　residents＇　dependence　on　public　transport　(RDPT)　is　an　important　foundation　for　increasing　the　proportion　of　green　trips　and　alleviating　urban　traffic　congestion.　To　explore　the　influence　mechanism　of　RDPT,　this　paper　extends　the　theory　of　planned　behavior　(TPB)　by　introducing　objective　factors　of　attributes,　environment,　and　travel　characteristics.　The　agglomerative　nesting　clustering　algorithm　and　multiple　structural　equation　modeling　(SEM)　are　then　developed　to　identify　the　RDPT　levels　and　analyze　the　influence　relationships　between　the　integrated　influencing　factors　and　RDPT　based　on　travel　survey　data.　The　results　indicate　that　the　objective　variables　have　indirect　impacts　on　RDPT　by　influencing　psychological　variable　attitudes,　subjective　norms　and　perceived　control　and　travel　intention.　The　residents＇　self-selection　(RSS)　effects　of　different　clusters　are　all　detected　under　normal　conditions,　and　the　environment　on　RDPT　is　still　significant　after　controlling　for　this　effect.　The　findings　reflect　that　the　influence　mechanisms　of　the　three　SEMs　for　different　clusters　are　distinct,　unlike　those　of　the　baseline　model,　and　distinctive　observation　variables　have　dissimilar　explanatory　abilities　for　the　travel　intention　of　different　residents.　Therefore,　some　beneficial　policy　implications　are　proposed　for　residents,　especially　those　who　retain　low　and　relatively　low　public　transport　dependence　levels,　to　increase　public　transport　usage　while　reduce　the　car　usage　based　on　the　significant　findings.