Hierarchical Strategic Decision-Making in Layered Mobility Systems
Mingjia He, Zhiyu He, Jan Ghadamian, Florian D\"orfler, Emilio Frazzoli, Gioele Zardini

TL;DR
This paper introduces a hierarchical game-theoretic model combined with feedback optimization to improve decision-making in complex urban mobility systems, demonstrating better outcomes than traditional methods.
Contribution
It presents a novel tri-level Stackelberg game approach with a model-free feedback scheme for scalable, constraint-enforcing policy optimization in mobility systems.
Findings
Our method outperforms Bayesian optimization and genetic algorithms in municipal objectives.
It increases multimodal usage and operator objectives through feedback-based regulation.
The approach achieves tangible welfare gains in a real Zurich mobility network.
Abstract
Mobility systems are complex socio-technical environments influenced by multiple stakeholders with hierarchically interdependent decisions, rendering effective control and policy design inherently challenging. We bridge hierarchical game-theoretic modeling with online feedback optimization by casting urban mobility as a tri-level Stackelberg game (travelers, operators, municipality) closed in a feedback loop. The municipality iteratively updates taxes, subsidies, and operational constraints using a projected two-point (gradient-free) scheme, while lower levels respond through equilibrium computations (Frank-Wolfe for traveler equilibrium; operator best responses). This model-free pipeline enforces constraints, accommodates heterogeneous users and modes, and scales to higher-dimensional policy vectors without differentiating through equilibrium maps. On a real multimodal network for…
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