Vehicular　ad　hoc　networks　(VANETs)　have　an　important　role　in　urban　management　and　planning.　The　effective　integration　of　vehicle　information　in　VANETs　is　critical　to　traffic　analysis,　large-scale　vehicle　route　planning　and　intelligent　transportation　scheduling.　However,　given　the　limitations　in　the　precision　of　the　output　information　of　a　single　sensor　and　the　difficulty　of　information　sharing　among　various　sensors　in　a　highly　dynamic　VANET,　effectively　performing　data　aggregation　in　VANETs　remains　a　challenge.　Moreover,　current　studies　have　mainly　focused　on　data　aggregation　in　large-scale　environments　but　have　rarely　discussed　the　issue　of　intra-cluster　data　aggregation　in　VANETs.　In　this　study,　we　propose　a　multi-player　game　theory　algorithm　for　intra-cluster　data　aggregation　in　VANETs　by　analyzing　the　competitive　and　cooperative　relationships　among　sensor　nodes.　Several　sensor-centric　metrics　are　proposed　to　measure　the　data　redundancy　and　stability　of　a　cluster.　We　then　study　the　utility　function　to　achieve　efficient　intra-cluster　data　aggregation　by　considering　both　data　redundancy　and　cluster　stability.　In　particular,　we　prove　the　existence　of　a　unique　Nash　equilibrium　in　the　game　model,　and　conduct　extensive　experiments　to　validate　the　proposed　algorithm.　Results　demonstrate　that　the　proposed　algorithm　has　advantages　over　typical　data　aggregation　algorithms　in　both　accuracy　and　efficiency.