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Mesoscopic-informed residual reinforcement learning for adaptive CAV headway control in mixed-autonomy traffic

Classical constant-time-headway control limits each connected automated vehicle to predecessor-relative information, so disturbances …

Sheida Nozari, Mustafa Kamal, Charelle Khoury, Stefania Fresca, Alessio Iovine, Filippo Gatti

Graph surrogate modeling for closed-loop microscopic-macroscopic control of mixed traffic

We propose a graph neural surrogate framework that replaces the macroscopic partial differential equation solver inside a closed-loop …

Sheida Nozari, Alessio Iovine, Stefania Fresca, Filippo Gatti

Correcting neural operator spectral bias via diffusion posterior sampling with sparse observations

Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral …

Niccolo Perrone, Fanny Lehmann, Stefania Fresca, Filippo Gatti

From microscopic interactions to macroscopic feedback: Real-time traffic control via neural operators

Real-time multi-scale traffic control requires capturing how microscopic vehicle interactions give rise to macroscopic flow dynamics …

Sheida Nozari, Stefania Fresca, Filippo Gatti, Alessio Iovine

HypeR adaptivity: Joint hr-adaptive meshing via hypergraph multi-agent deep reinforcement learning

Adaptive mesh refinement is central to the efficient solution of partial differential equations (PDEs) via the finite element method …

Niccolo Grillo, James Rowbottom, Pietro Lio, Carola-Bibiane Schönlieb, Stefania Fresca

HypeRL: Parameter-informed reinforcement learning for parametric PDEs

In this work, we devise a new, general-purpose reinforcement learning strategy for the optimal control of parametric partial …

Niccolo Botteghi, Stefania Fresca, Mengwu Guo, Andrea Manzoni