To　evaluate　the　driving　behavior　of　unmanned　vehicles,　the　testing　of　driving　algorithms　using　urban　road　images　is　necessary.　In　this　article,　we　propose　a　framework　using　generative　adversarial　networks　(GANs)　with　structural　information　for　image　style　transfer:　StructureGAN　and　GradientGAN.　Different　types　of　urban　image　transfers　are　generated　using　the　proposed　framework,　such　as　day　to　night,　sunny　to　foggy,　and　summer　to　winter　transfers.　The　proposed　method　can　well　maintain　the　integrity　of　foreground　objects　and　the　image　structural　information.　Artifacts　such　as　image　distortion　and　foreground　disappearance　are　eliminated.　The　experiments　with　the　baseline　methods　indicate　the　effectiveness　of　the　proposed　framework,　which　can　produce　transferred　images　with　high　quality.