As　electric　vehicles　(EVs)　rapidly　proliferate,　they　intensify　the　demands　on　coupled　power　and　transportation　networks　(CPTNs),　leading　to　operational　challenges　such　as　congestion　and　overload.　To　address　these　challenges　and　enhance　the　dynamic　performance　of　CPTNs,　this　paper　proposes　a　coordinated　expansion　planning　model　based　on　a　dynamic　modeling　method　to　support　the　upgrading　of　CPTNs　(in　distribution　lines,　distributed　generators,　chargers　and　roads).　The　spatial-temporal　evolution　and　interaction　of　power　flow　in　power　distribution　systems　and　traffic　flow　in　transportation　networks　is　incorporated　into　a　dynamic　network　equilibrium,　revealing　the　impact　of　network　expansion　on　system　performance.　Uniquely,　it　replaces　static　link　models　with　a　novel　point　queue　model　to　better　track　queuing　and　charging　dynamics　at　fast　charging　stations.　A　scenario　-based　bi-level　stochastic　optimization　model　is　formulated　to　determine　the　optimal　coordinated　expansion　strategies,　considering　the　diversity　of　electric　and　traffic　demand　scenarios.　The　optimization　problem　is　solved　using　a　designed　marginal　-cost　-based　particle　swarm　optimization　algorithm.　Case　studies　demonstrate　the　model＇s　effectiveness　in　alleviating　95.89%　traffic　congestion　and　reducing　4.75%　low　voltage　risk　and　28.86%　overload　risk,　marking　a　significant　advancement　in　CPTN　management.