将软件定义网络(SDN)与车载自组织网(VANET)结合，提出基于SDN的VANET，以SDN的灵活性匹配VANET的动态性，解决VANET中精确即时定位及可靠实时通信关键问题，重点拟对其中的节点定位、信道接入以及网络层参数优化等方面展开研究。具体内容为：1)提出信号子空间投影与网格化计算相结合的定位算法。针对不同类别车辆进行单基站指纹匹配定位和协作式多车迭代定位，以获取全网车辆的精确即时定位数据；2)提出基于动态多协议序列的信道接入机制。构建虚拟节点，再将粗粒度的路边节点序列候选集分配与细粒度的车辆节点交互分配相结合，通过描绘序列子集图谱，实现不同类型及优先级虚拟节点的动态多协议序列分配；3)提出多目标网络层参数优化方法。采用“链路段”的方式，通过度量参量矩阵描述网络属性，从车辆移动性及数据多样性构建时延目标函数，从流表规则操作最优化构建网络开销目标函数，实现网络资源的优化重配置。

Vehicular Ad-hoc Network (VANET) based on software defined networks (SDN) is proposed through combining SDN with VANET. The flexibility of SDN can match the dynamic attribute of VANET, which will be the crucial innovation of VANET. It is a challenge to deal with instant accurate localization and reliable real-time communication due to the characters of VANET. So in this research, localization algorithm, mechanism of channel access and network-layer parameters optimization will be investigated. The main contents are as follows: 1) A localization algorithm combined signal subspace projection and gridding computation is proposed. For difficult type of vehicles, single-base-station fingerprint matching localization and cooperative multi-vehicles iterative localization are used to obtain the instant accurate localization data of the whole vehicles. 2) A mechanism of channel access based on dynamic multi-protocol-sequences is proposed. Through creating virtual nodes, coarse-grained sequence candidate set distribution among RSUs and fine-grained interactive allocation of sequences among vehicles are used to depict the sequences subset mapping. So the virtual nodes with different types and priority will be distributed dynamically with multi-protocol sequences. 3) A method of network-layer multi-objective parameter optimization is proposed for optimal network reconfiguration. To achieve this goal, the property of network is depicted by metric matrices with “communication link section”. And then, the objective function of network delay is constructed according to the mobility of vehicles and diversity of data services. In addition, the objective function of network overhead is also constructed according to the optimization of flow table operation rules.