Multiday User Equilibrium with Strategic Commuters
研究了联网自动驾驶时代通勤者利用计算能力进行多日策略性出行选择所导致的交通模式，提出了多日用户均衡概念，揭示了用户惯性对网络流量的影响及其与经典Wardrop均衡的联系。
In the era of connected and automated mobility, commuters possess strong computation power, enabling them to strategically make sequential travel choices over a planning horizon. This paper investigates the multiday traffic patterns that arise from such decision-making behavior. In doing so, we frame the commute problem as a mean-field Markov game and introduce a novel concept of multiday user equilibrium to capture the steady state of commuters’ interactions. The proposed model is general and can be tailored to various travel choices, such as route or departure time. We explore a range of properties of the multiday user equilibrium under mild conditions. The study reveals the fingerprint of user inertia on network flow patterns, causing between-day variations even at a steady state. Furthermore, our analysis establishes critical connections between the multiday user equilibrium and conventional Wardrop equilibrium. Funding: This work was supported by the National Science Foundation [Grants CMMI-1854684, CMMI-1904575, CMMI-2233057, and CMMI-2240981]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0488 .