Vehicular Cloud Computing (VCC) leverages the idle computing capacity of vehicles to execute end-users' offloaded tasks without requiring new computation infrastructure. Despite its conceptual appeal, VCC adoption is hindered by the lack of quantitative evidence demonstrating its profitability and environmental advantages in real-world scenarios. This paper tackles the fundamental question: Can VCC be both profitable and sustainable? We address this problem by proposing a management scheme for VCC that combines energy-aware task allocation with a game-theoretic revenue-sharing mechanism. Our framework is the first to jointly model latency, energy consumption, monetary incentives, and carbon emissions within urban mobility and 5G communication settings. The task allocation strategy maximizes the aggregate stakeholder utility while satisfying deadlines and minimizing energy costs. The payoffs are distributed via a coalitional game theory adapted to dynamic vehicular environments, to prevent disincentivizing participants with potentially negative contributions. Extensive simulations demonstrate that our approach supports low-latency task execution, enables effective monetization of vehicular resources, and reduces CO2 emissions by more than 99% compared to conventional edge infrastructures, making VCC a practical and sustainable alternative to edge computing.

翻译：车载云计算（VCC）利用车辆的闲置计算能力来执行终端用户卸载的任务，而无需新建计算基础设施。尽管其概念颇具吸引力，但由于缺乏定量证据证明其在真实场景中的盈利能力和环境优势，VCC的采用受到阻碍。本文解决了一个根本性问题：VCC能否同时具备盈利性和可持续性？我们通过提出一种结合了能量感知任务分配与博弈论收益共享机制的车载云管理方案来解决此问题。我们的框架首次在城市移动性和5G通信环境中，联合建模了延迟、能耗、货币激励和碳排放。任务分配策略在满足截止时间并最小化能源成本的同时，最大化利益相关者的总效用。收益分配通过一种适应动态车载环境的联盟博弈论进行，以防止对可能做出负面贡献的参与者产生负面激励。大量仿真实验表明，我们的方法支持低延迟任务执行，实现了车载资源的有效货币化，并且与传统的边缘基础设施相比，减少了超过99%的二氧化碳排放，使得车载云成为边缘计算的一个实用且可持续的替代方案。