The demand for passenger and freight transportation has grown sharply over the last decades and will triple by 2050. This also dramatically impacts the environment as traffic is one of the primary sources of CO2 emission. Platooning, which is defined as driving automated vehicles in convoys with minimal inter-vehicle distance enabled by vehicular communication, offers several benefits like energy savings due to slipstream effects, homogenization of traffic flows, increased capacity of streets, as well as improved safety due to communication. However, as the vehicles at inner positions of a platoon experience higher benefits than the first and last vehicle, the compensation of the effects of different positions in a platoon have to be taken into account when integrating vehicles in a platoon. In this paper, we discuss several strategies on how to incentivize vehicles to participate in platooning based on directly or indirectly compensating vehicles for fewer benefits resulting from the integration into a platooning system. Our considerations integrate ideas from research about altruism, social sciences, organ donation, task scheduling on computers, as well as professional cycling sports. Our experiments show that the time spent in a position with negative effects is split equally among all vehicles when using our mechanisms. Additionally, we found that characteristics of the environment – e.g., the number of lanes or traffic density – impact the performance of the compensation mechanisms. We further provide a discussion of the identified challenges and on how to apply our proposed ideas to other systems which require self-integration.

在过去的几十年中，对客运和货运的需求急剧增长，到2050年将增长两倍。由于交通运输是CO2排放的主要来源之一，因此对环境也产生了巨大影响。排被定义为在车队中通过车辆通讯实现最小的车距行驶，从而带来了许多好处，例如由于滑流效应而节省了能源，交通流量均质化，街道通行能力提高以及安全性的提高。通讯。但是，由于排内位置的车辆比第一个和最后一个车辆具有更高的收益，因此在将车辆集成到排中时必须考虑对排中不同位置的影响的补偿。在本文中，我们讨论了几种基于直接或间接补偿车辆以减少因集成到排系统中而产生的收益的激励车辆的方法。我们的考虑因素融合了利他主义，社会科学，器官捐赠，计算机上的任务计划以及专业自行车运动等方面的研究思想。我们的实验表明，使用我们的机制时，在具有负面影响的位置上花费的时间在所有车辆之间平均分配。此外，我们发现环境特征（例如，车道数或交通密度）会影响补偿机制的性能。我们进一步讨论了已发现的挑战，以及如何将我们提出的想法应用于需要自我整合的其他系统。