The increasing complexity of urban transportation systems, driven by connected and automated vehicles, calls for new modeling paradigms and scalable control strategies. We propose a non-monetary control framework that leverages autonomous intersection management to influence routing decisions without tolls. The approach uses timestamp-based scheduling adjustments at roadside units (RSUs) to introduce path-dependent delays or advancements, steering traffic toward socially efficient flows. We develop a hierarchical architecture that separates real-time intersection control from network-level coordination. The resulting model admits a congestion-game formulation with path-dependent node costs. We establish the existence and essential uniqueness of equilibrium flows, eliminating ambiguities due to multiple equilibria and enabling a scalable and tractable bilevel optimization formulation for system-level incentive design. Experiments on the Sioux Falls network show that the proposed approach reduces the efficiency gap between user equilibrium and system-optimal flows by up to 71% under realistic constraints. These results demonstrate the potential of non-monetary, infrastructure-light control for next-generation intelligent transportation and urban mobility systems.

翻译：城市交通系统因互联与自动化车辆的普及而日益复杂，亟需新的建模范式和可扩展控制策略。本文提出一种非货币化控制框架，利用自主交叉口管理技术在不征收通行费的情况下影响路径选择决策。该框架通过路侧单元（RSU）施加基于时间戳的调度调整，引入路径依赖的延迟或提前机制，引导交通流向社会最优状态。我们构建了分离实时交叉口控制与网络级协调的分层架构，由此建立的模型可转化为具有路径依赖节点成本的拥塞博弈形式。我们证明了均衡流的存在性与本质唯一性，消除了多重均衡带来的歧义，并构建了用于系统级激励设计的可扩展双层优化模型。在苏福尔斯路网上的实验表明，在现实约束条件下，该方法可将用户均衡与系统最优流之间的效率差距最高降低71%。这些结果证明了非货币化、轻量基础设施控制在下一代智能交通与城市出行系统中的潜力。