Vehicular metaverse, which is treated as the future continuum between automotive industry and metaverse, is envisioned as a blended immersive domain as the digital twins of intelligent transportation systems. Vehicles access the vehicular metaverses by their own Vehicle Twins (VTs) (e.g., avatars) that resource-limited vehicles offload the tasks of building VTs to their nearby RoadSide Units (RSUs). However, due to the limited coverage of RSUs and the mobility of vehicles, VTs have to be migrated from one RSU to other RSUs to ensure uninterrupted metaverse services for users within vehicles. This process requires the next RSUs to contribute sufficient bandwidth resources for VT migrations under asymmetric information. To this end, in this paper, we design an efficient incentive mechanism framework for VT migrations. We first propose a novel metric named Age of Migration Task (AoMT) to quantify the task freshness of the VT migration. AoMT measures the time elapsed from the first collected sensing data of the freshest avatar migration task to the last successfully processed data at the next RSU. To incentivize the contribution of bandwidth resources among the next RSUs, we propose an AoMT-based contract model, where the optimal contract is derived to maximize the expected utility of the RSU that provides metaverse services. Numerical results demonstrate the efficiency of the proposed incentive mechanism for VT migrations.

翻译：车辆元宇宙被视为汽车工业与元宇宙之间的未来连续体，被构想为智能交通系统数字孪生的一种融合沉浸式领域。车辆通过自身的车辆孪生（VTs）（例如，虚拟化身）接入车辆元宇宙，资源受限的车辆将构建VTs的任务卸载到其附近的路边单元（RSUs）。然而，由于RSUs覆盖范围有限以及车辆的移动性，VTs必须从一个RSU迁移到其他RSU，以确保车内用户获得不间断的元宇宙服务。这一过程要求下一个RSU在信息不对称的情况下贡献足够的带宽资源用于VT迁移。为此，本文设计了一个高效的VT迁移激励框架。我们首先提出一种名为迁移任务年龄（AoMT）的新指标，用于量化VT迁移的任务新鲜度。AoMT衡量从最新虚拟化身迁移任务首次收集传感数据到下一个RSU成功处理最后一个数据所经过的时间。为了激励候选RSU间的带宽资源贡献，我们提出了一种基于AoMT的契约模型，推导出最优契约以最大化提供元宇宙服务的RSU的期望效用。数值结果证明了所提VT迁移激励机制的有效性。