Prior　negative　congestion　experiences　can　influence　public　acceptance　of　congestion　charging　policies;　however,　this　area　remains　underexplored　in　both　academic　and　practical　contexts.　This　study　investigates　this　issue　by　integrating　the　norm　activation　model　(NAM)　and　the　theory　of　planned　behavior　(TPB),　focusing　on　public　acceptance　of　tradable　credits　schemes　(TCS).　Specifically,　acceptance　is　measured　via　attitudes　toward　TCS　and　behavioral　intentions　to　reduce　car　use　under　TCS.　Using　latent　profile　analysis,　426　participants　were　categorized　into　three　distinct　groups　based　on　their　prior　negative　congestion　experiences.　The　findings　indicate　that　those　with　high　reactions　exhibit　stronger　behavioral　intentions　to　reduce　car　use.　Chain　mediation　analysis　demonstrates　that　prior　negative　congestion　experiences　causally　impact　these　behavioral　intentions.　Moderated　mediation　analysis　further　reveals　that　such　experiences　(e.g.,　anxiety　and　bodily　reactions)　moderate　behavioral　intentions　under　TCS.　High　levels　of　anxiety　and　bodily　reactions　weaken　the　impact　of　personal　norms　on　attitudes　toward　TCS,　suggesting　that　individuals　with　intense　reactions　to　congestion　are　more　likely　to　directly　support　TCS.　Conversely,　enhancing　personal　norms　among　individuals　with　lower　anxiety　or　bodily　reactions　tend　to　increase　their　support　for　TCS.　Furthermore,　personal　norms　are　found　to　be　more　influential　than　social　norms,　offering　greater　explanatory　power.