As the fusion of automotive industry and metaverse, vehicular metaverses establish a bridge between the physical space and virtual space, providing intelligent transportation services through the integration of various technologies, such as extended reality and real-time rendering technologies, to offer immersive metaverse services for Vehicular Metaverse Users (VMUs). In vehicular metaverses, VMUs update vehicle twins (VTs) deployed in RoadSide Units (RSUs) to obtain metaverse services. However, due to the mobility of vehicles and the limited service coverage of RSUs, VT migration is necessary to ensure continuous immersive experiences for VMUs. This process requires RSUs to contribute resources for enabling efficient migration, which leads to a resource trading problem between RSUs and VMUs. Moreover, a single RSU cannot support large-scale VT migration. To this end, we propose a blockchain-assisted game approach framework for reliable VT migration in vehicular metaverses. Based on the subject logic model, we first calculate the reputation values of RSUs considering the freshness of interaction between RSUs and VMUs. Then, a coalition game based on the reputation values of RSUs is formulated, and RSU coalitions are formed to jointly provide bandwidth resources for reliable and large-scale VT migration. Subsequently, the RSU coalition with the highest utility is selected. Finally, to incentivize VMUs to participate in VT migration, we propose a Stackelberg model between the selected coalition and VMUs. Numerical results demonstrate the reliability and effectiveness of the proposed schemes.

翻译：随着汽车工业与元宇宙的融合，车载元宇宙在物理空间与虚拟空间之间架起桥梁，通过集成扩展现实、实时渲染等技术提供智能交通服务，为车载元宇宙用户（VMUs）提供沉浸式体验。在车载元宇宙中，VMUs通过更新部署在路侧单元（RSUs）中的车辆孪生（VTs）来获取元宇宙服务。然而，由于车辆移动性及RSU服务范围的限制，VT迁移对于确保VMUs持续获得沉浸式体验至关重要。该过程需要RSUs贡献资源以实现高效迁移，从而引发RSUs与VMUs之间的资源交易问题。此外，单一RSU无法支持大规模VT迁移。为此，我们提出了一种基于区块链的博弈方法框架，用于车载元宇宙中可靠的VT迁移。基于主体逻辑模型，我们首先考虑RSUs与VMUs交互的新鲜度，计算RSUs的信誉值。随后，基于RSUs信誉值构建联盟博弈，形成RSU联盟以联合提供带宽资源，支持可靠的大规模VT迁移。继而选择效用最高的RSU联盟。最后，为激励VMUs参与VT迁移，我们提出了所选联盟与VMUs之间的Stackelberg模型。数值结果证明了所提方案的可靠性与有效性。