The　proliferation　of　microgrids　and　the　rapid　electrification　of　transportation　have　intensified　competition　for　distribution-level　resources,　highlighting　the　need　for　effective　coordination　strategies　for　energy　sharing　and　electric　vehicle　(EV)　charging.　This　study　aims　to　tackle　the　complexities　of　optimizing　EV　charging　within　an　energy-sharing　market,　where　multiple　microgrids　engage　in　electricity　trading　and　compete　for　flexible　demand.　We　develop　a　robust　game-theoretic　framework　that　incorporates　two　critical　components:　a　generalized　Nash　equilibrium　game　model　and　a　nested　Stackelberg　game.　The　Nash　equilibrium　model　captures　the　interdependent　bidding　behaviors　of　microgrids,　while　the　Stackelberg　game　treats　EV　users　as　price-sensitive　followers,　who　adjust　their　charging　strategies　based　on　station-specific　tariffs　and　travel　costs.　The　two　models　are　integrated　into　a　bilevel　generalized　Nash-Stackelberg　formulation　that　holistically　represents　the　strategic　interactions　among　all　stakeholders.　To　solve　this　coupled　equilibrium,　we　utilize　a　fixed-point　scheme　embedded　in　a　modified　best-response　algorithm,　ensuring　convergence　to　the　joint　solution　of　the　inner　Nash　game　and　the　outer　Stackelberg　game.　Numerical　experiments　demonstrate　that　the　proposed　strategy　effectively　guides　EV　users　toward　economically　rational　charging　patterns,　balances　utilization　across　charging　stations,　and　enhances　overall　network　efficiency　and　microgrid　profitability　compared　to　conventional　decentralized　scheduling　methods.　These　results　underline　the　practical　value　of　the　framework　for　integrated　management　of　transportation　and　power　infrastructures.