Strategic interaction in congested systems is commonly modelled using Stackelberg games, where competing leaders anticipate the behaviour of self-interested followers. A key limitation of existing models is that they typically ignore agents who do not directly participate in market competition, yet both contribute to and adapt to congestion. Although such non-follower agents do not generate revenue or respond to market incentives, their behaviour reshapes congestion patterns, which in turn affects the decisions of leaders and followers through shared resources. We argue that overlooking non-followers leads to systematically distorted equilibrium predictions in congestion-coupled markets. To address this, we introduce a three-level Stackelberg framework with heterogeneous leaders differing in decision horizons and feasible actions, strategic followers, and non-follower agents that captures bidirectional coupling between infrastructure decisions, competition, and equilibrium congestion. We instantiate the framework in the context of electric vehicle (EV) charging infrastructure, where charging providers compete with rivals, while EV and non-EV traffic jointly shape congestion. The model illustrates how explicitly accounting for non-followers and heterogeneous competitors qualitatively alters strategic incentives and equilibrium outcomes. Beyond EV charging, the framework applies to a broad class of congestion-coupled multi-agent systems in mobility, energy, and computing markets.

翻译：拥塞系统中的策略交互通常采用Stackelberg博弈建模，其中相互竞争的领导层会预判自利跟随者的行为。现有模型的一个关键局限在于，它们通常忽略那些不直接参与市场竞争，却同时加剧并适应拥塞的智能体。尽管这类非跟随者智能体既不产生收益也不响应市场激励，但其行为会重塑拥塞模式，进而通过共享资源影响领导者与跟随者的决策。我们认为，忽略非跟随者将导致拥塞耦合市场的均衡预测出现系统性偏差。为解决此问题，我们提出了一个包含异质领导者（其决策视野与可行行动存在差异）、策略性跟随者以及非跟随者智能体的三层Stackelberg框架，该框架能捕捉基础设施决策、市场竞争与均衡拥塞之间的双向耦合关系。我们将该框架实例化于电动汽车充电基础设施场景：充电服务商相互竞争，而电动汽车与非电动汽车交通流共同塑造道路拥塞。该模型揭示了明确考虑非跟随者及异质竞争者如何从本质上改变策略激励与均衡结果。除电动汽车充电领域外，本框架可广泛应用于交通、能源和计算市场中具有拥塞耦合特性的多智能体系统。