The evolution of existing transportation systems,mainly driven by urbanization and increased availability of mobility options, such as private, profit-maximizing ride-hailing companies, calls for tools to reason about their design and regulation. To study this complex socio-technical problem, one needs to account for the strategic interactions of the heterogeneous stakeholders involved in the mobility ecosystem and analyze how they influence the system. In this paper, we focus on the interactions between citizens who compete for the limited resources of a mobility system to complete their desired trip. Specifically, we present a game-theoretic framework for multi-modal mobility systems, where citizens, characterized by heterogeneous preferences, have access to various mobility options and seek individually-optimal decisions. We study the arising game and prove the existence of an equilibrium, which can be efficiently computed via a convex optimization problem. Through both an analytical and a numerical case study for the classic scenario of Sioux Falls, USA, we illustrate the capabilities of our model and perform sensitivity analyses. Importantly, we show how to embed our framework into a "larger" game among stakeholders of the mobility ecosystem (e.g., municipality, Mobility Service Providers, and citizens), effectively giving rise to tools to inform strategic interventions and policy-making in the mobility ecosystem.

翻译：现有交通系统的发展主要受城市化进程和出行选择多样化（如以利润最大化为目标的私营网约车公司）的推动，这要求我们开发用于分析其设计和监管的工具。为研究这一复杂的社会技术问题，需要考量出行生态系统中不同利益相关者的策略性互动，并分析这些互动如何影响整个系统。本文聚焦于为完成预期行程而竞争出行系统有限资源的市民之间的互动。具体而言，我们提出了一种针对多模式出行系统的博弈论框架。在该框架中，具有异质性偏好的市民可使用多种出行方式，并寻求个人最优决策。我们研究了由此产生的博弈行为，证明了均衡点的存在性，并表明该均衡可通过凸优化问题高效求解。通过经典场景——美国苏福尔斯的分析与数值案例研究，我们展示了模型的能力并进行了敏感性分析。重要的是，我们展示了如何将该框架嵌入出行生态系统中利益相关者（如市政当局、出行服务提供商和市民）之间的“更大规模”博弈，从而为出行生态系统中的策略性干预和政策制定提供有效工具。