Unlike commercial ridesharing, non-commercial peer-to-peer (P2P) ridesharing has been subject to limited research -- although it can promote viable solutions in non-urban communities. This paper focuses on the core problem in P2P ridesharing: the matching of riders and drivers. We elevate users' preferences as a first-order concern and introduce novel notions of fairness and stability in P2P ridesharing. We propose algorithms for efficient matching while considering user-centric factors, including users' preferred departure time, fairness, and stability. Results suggest that fair and stable solutions can be obtained in reasonable computational times and can improve baseline outcomes based on system-wide efficiency exclusively.

翻译：与商业搭车共享不同,非商业同行搭车共享(P2P)一直受到有限的研究 -- -- 尽管它可以在非城市社区推动可行的解决方案。本文侧重于P2P搭车共享的核心问题:搭车者和司机的配对。我们把用户的偏好提升为一阶问题,并在P2P搭车共享中引入公平和稳定的新概念。我们提出高效匹配的算法,同时考虑到以用户为中心的因素,包括用户首选的离开时间、公平性和稳定性。结果显示,公平和稳定的解决方案可以在合理的计算时间内获得,并且能够完全根据全系统效率改善基线结果。