This paper proposes a simplified version of classical models for urban transportation networks, and studies the problem of controlling intersections with the goal of optimizing network-wide congestion. Differently from traditional approaches to control traffic signaling, our simplified framework allows a more tractable analysis of the network dynamics and, yet, accurately captures the behavior of traffic flows along roads and in proximity of intersections in regimes of free flow. We cast an optimization problem to describe the goal of optimally controlling automated intersections, and relate congestion objectives with the problem of optimizing a metric of controllability of the associated dynamical system. We characterize the system performance in relation to (sub)optimal configurations, and identify conditions that guarantee network stability. Lastly, we assess the benefits of the proposed modeling and optimization framework through a microscopic simulator.
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