Vehicular　ad　hoc　networks　(VANETs)　have　become　an　essential　part　in　smart　transportation　systems　of　modern　cities.　However,　because　of　dynamicity　and　infrastructure-less　of　VANETs,　the　ever　increasing　number　of　network　security　issues　become　obstacles　for　the　realization　of　smart　cities.　Software-defined　VANETs　have　provided　a　reliable　way　to　manage　VANETs　dynamically　and　securely.　However,　the　traditionally　centralized　control　plane　makes　it　vulnerable　to　malicious　nodes　and　results　in　performance　degradation.　Therefore,　a　distributed　control　plane　is　necessary.　How　to　reach　a　consensus　among　multiple　controllers　under　complex　vehicular　environment　is　an　essential　problem.　In　this　paper,　we　propose　a　novel　blockchain-based　distributed　software-defined　VANET　framework　(block-SDV)　to　establish　a　secure　architecture　to　overcome　the　above　issues.　The　trust　features　of　blockchain　nodes,　the　number　of　consensus　nodes,　trust　features　of　each　vehicle,　and　the　computational　capability　of　the　blockchain　are　considered　in　a　joint　optimization　problem,　which　is　modeled　as　a　Markov　decision　process　with　state　space,　action　space　and　reward　function.　Since　it　is　difficult　to　be　solved　by　traditional　methods,　we　propose　a　novel　dueling　deep　Q-learning　(DDQL)　with　prioritized　experience　replay　approach.　Simulation　results　are　presented　to　show　the　effectiveness　of　the　proposed　block-SDV　framework.