The　high　proliferation　of　electric　vehicles　has　intensified　the　interdependency　between　traffic　networks　(TNs)　and　power　distribution　networks　(PDNs).　Accordingly,　this　article　proposes　a　decentralized　optimization　framework　for　the　multiarea　optimal　traffic-power　flow　(OTPF)　problem,　in　which　the　models　of　PDNs　and　TNs　are　established　separately　in　a　distributed　manner.　A　multistage　distributionally　robust　optimization　(MDRO)　model　is　formulated　for　PDNs　to　address　wind　power　uncertainty,　with　the　introduction　of　a　traffic　assignment　problem　to　describe　the　distribution　of　traffic　flows　in　TNs.　Furthermore,　an　improved　alternative　direction　method　of　multipliers　(I-ADMM)　algorithm　is　developed　to　solve　the　multiarea　OTPF　problem.　Numerical　results　from　a　three-area　traffic-power　coupled　system　demonstrate　that　the　proposed　MDRO　model　bears　a　cost　$89.50　lower　than　that　of　the　multistage　robust　optimization　model,　while　the　I-ADMM　algorithm　yields　a　solving　time　only　one-third　that　of　the　traditional　ADMM.