Data　collection　is　key　issue　in　vehicular　networks　since　it　is　vital　for　supporting　many　applications　in　vehicular　environments.　With　the　explosive　growth　of　sensing　data　in　urban　area,　however,　strategies　for　efficient　collection　of　big　data　in　vehicular　networks　are　still　far　from　being　well　studied.　In　this　paper,　we　focus　on　studying　this　issue　and　accordingly　propose　a　Software　Defined　Vehicular　Networks　(SDVN)　architecture.　On　this　architecture,　a　predictive　data　collection　algorithm　is　proposed.　In　this　algorithm,　packet　delivery　is　fulfilled　by　cooperative　cellular　and　ad　hoc　network　interfaces,　in　which　collections　of　big　data　always　adopts　ad　hoc　based　multi-hop　relaying　whenever　applicable　to　forward　packets　to　Road　Side　Units　(RSUs).　Cellular　networks　are　used　for　data　uploading　only　when　no　multi-hop　relaying　opportunity　is　available.　Our　proposed　SDVN　architecture　enables　such　efficient　cooperative　communications,　in　which　predictive　routing　decisions　are　made　based　on　real-time　network　status　other　than　empirical　knowledge.　Simulation　results　demonstrate　that　our　algorithm　outperforms　existing　algorithms　in　terms　of　packet　delivery　ratio　and　transmit　efficiency.