Digital　development　disparities,　technological　diversity,　and　regional　imbalances　have　led　to　a　shortage　of　tailored　carbon　reduction　strategies　for　the　transportation　sector.　Understanding　the　mechanisms　and　future　trajectories　of　transportation　carbon　emission　(TCE)　drivers　across　varying　digitization　levels　is　crucial.　To　address　this　issue,　we　propose　a　strategy　that　classifies　Chinese　provinces　into　four　distinct　digitization　regions　based　on　their　digital　development　characteristics.　First,　we　extend　the　STIRPAT-PLS　framework　to　analyze　the　historical　impacts　of　external　governance　and　internal　development　factors　on　TCE.　Second,　we　use　scenario　settings　and　Monte　Carlo　simulation　techniques　to　simulate　future　trends　of　TCE.　Third,　we　conduct　a　dynamic　sensitivity　analysis　to　assess　the　contributions　of　factors,　aiming　to　optimize　the　TCE　peaking　path.　Our　results　indicate　that　the　digitization　context　cannot　fully　explain　the　differences　in　TCE;　even　in　regions　with　similar　levels　of　digitization,　the　contributions　of　influencing　factors　vary　significantly.　Under　the　BAU　scenario,　existing　policies　and　technologies　may　be　insufficient　to　achieve　TCE　peaking　before　2030.　This　work　guides　achieving　carbon　peaking　in　China＇s　transportation　sector.　It　emphasizes　that　we　should　build　upon　the　digital　development　context　and　harness　the　positive　effects　of　different　influences　to　promote　context-specific　policy　implementation.　©　2024