Vehicular platooning is a well-known transportation technique that helps reduce fuel consumption, carbon emissions, and road congestion. When integrated with Connected and Autonomous Vehicle (CAV) technologies, platooning enhances the overall safety and efficiency of the transportation system. This article presents Platooning as a Service (PlaaS) platform, a decision-support framework to promote sustainable transportation through platooning. We have formulated this problem as a Stackelberg game, with the platoon service provider (PSP) as the leader and the service users as the followers. The PSP sets the pricing policy, and the follower responds by choosing the distance to be travelled with the platoon. The optimal service contract between the PSP and the follower vehicle is established with the Stackelberg equilibrium, which is derived using Karush-Kuhn-Tucker optimality conditions. Additionally, we have examined the impact of government subsidies on the PlaaS platform in reducing carbon emissions. Our model has been applied to a specific example problem to illustrate the benefits for both players. We have also derived managerial insights through sensitivity analysis, exploring the effect of different velocity levels, vehicle dimensions, government subsidies, and operational urgency on the utilities of the players and CO2 emissions. Our analysis shows that PSP gains a higher profit from high delay-cost vehicles performing time-critical operations with higher platoon velocity. However, the benefits related to fuel consumption are only realized at moderate platoon velocities.

翻译：车辆编队行驶是一种广为人知的交通技术，有助于降低燃料消耗、减少碳排放并缓解道路拥堵。当与网联自动驾驶车辆技术相结合时，编队行驶能进一步提升交通系统的整体安全性与运行效率。本文提出编队即服务平台（PlaaS），这是一个通过编队行驶促进可持续交通的决策支持框架。我们将该问题建模为Stackelberg博弈，其中编队服务提供商作为领导者，服务用户作为跟随者。服务提供商制定定价策略，跟随者则通过选择编队行驶距离予以响应。服务提供商与跟随车辆之间的最优服务契约通过Stackelberg均衡建立，该均衡采用Karush-Kuhn-Tucker最优性条件推导得出。此外，我们研究了政府补贴对PlaaS平台在减少碳排放方面的影响。通过具体案例问题验证了模型对博弈双方带来的效益。我们进一步通过敏感性分析获得管理启示，探讨了不同速度水平、车辆尺寸、政府补贴及运营紧迫性对博弈双方效用和二氧化碳排放的影响。分析表明：服务提供商可从执行时间敏感操作的高延误成本车辆在较高编队速度运行时获得更大利润，但燃料消耗相关的效益仅在中等编队速度下才能实现。