In this paper, we consider fair assignment of complex requests for Mobility-On-Demand systems. We model the transportation requests as temporal logic formulas that must be satisfied by a fleet of vehicles. We require that the assignment of requests to vehicles is performed in a distributed manner based only on communication between vehicles while ensuring fair allocation. Our approach to the vehicle-request assignment problem is based on a distributed auction scheme with no centralized bidding that leverages utility history correction of bids to improve fairness. Complementarily, we propose a rebalancing scheme that employs rerouting vehicles to more rewarding areas to increase the potential future utility and ensure a fairer utility distribution. We adopt the max-min and deviation of utility as the two criteria for fairness. We demonstrate the methods in the mid-Manhattan map with a large number of requests generated in different probability settings. We show that we increase the fairness between vehicles based on the fairness criteria without degenerating the servicing quality.

翻译：本文研究了按需出行系统中复杂请求的公平分配问题。我们将运输请求建模为必须由车队满足的时序逻辑公式，并要求请求与车辆的分配仅基于车辆间通信以分布式方式执行，同时确保公平分配。针对车辆-请求分配问题，我们提出了一种基于分布式拍卖方案的方法，该方法无需集中式竞标，通过利用出价的历史效用修正来提升公平性。作为补充，我们提出了一种再平衡方案，通过将车辆重新调度至更具收益性的区域来提高潜在未来效用，并确保更公平的效用分配。我们采用最大最小化与效用偏差作为公平性的两个判据。在曼哈顿中城地图上，通过不同概率设置下生成的大量请求对所提方法进行了验证。结果表明，在不降低服务质量的前提下，基于公平性判据提升了车辆间的公平性。