Electric　vehicles　(EVs),　as　popular　transportation　carriers　and　flexible　electric　loads,　couple　both　the　power　distribution　networks　and　transportation　networks.　The　pricing　schemes　of　fast　charging　stations　significantly　affects　the　EVs’　on-tirp　charging　behaviors　and　the　operations　of　coupled　power　and　transportation　networks.　This　interdisciplinary　paper　proposes　an　optimal　dynamic　pricing　method　for　fast　charging　stations　to　boost　charging　network　operator’　(CNO’s)　profits　and　avoid　excessive　charging　costs　of　EVs.　Time-varying　traffic　flow　and　charging　demands　are　generated　by　a　dynamic　traffic　assignment　simulation,　where　a　boundedly　rational　dynamic　user　equilibrium　model　is　presented　to　capture　the　cost　sensitivity　of　EVs　and　gasoline　vehicle　users.　Additionally,　a　market　regulator　supervises　the　CNO’s　pricing,　balancing　the　interests　of　the　CNO　and　users　via　a　regulation　constraint.　To　address　the　optimal　dynamic　pricing　issue,　we　propose　a　three-level　Stackelberg　game　involving　the　distribution　network　operator,　CNO,　and　users.　The　existence　of　a　game　equilibrium　is　assured　by　the　fixed-point　theory.　A　Gauss-Seidel　iteration　algorithm　with　inertia　weight　is　designed　to　solve　the　pricing　problem.　The　numerical　results　have　corroborated　the　effectiveness　of　the　proposed　method,　illuminating　the　effects　of　bounded　rationality　and　market　regulation　on　the　CNO’s　profits　and　users’　travel　costs.　IEEE