Learning to Move Cities: Deep Meta-Models and Reinforcement Policies for Calibration and Control in Urban Networks

arXiv:2609.21945 · cs.LG · Submitted 2026-09-18 · Read on arXiv

cs.LG

Submitted: 2026-09-18

Updated: 2026-09-18

Comments: 7 pages, 2 figures. Accepted for publication in the Proceedings of the 2026 IEEE 29th International Conference on Intelligent Transportation Systems (ITSC), Naples, Italy. (c) 2026 IEEE. Personal use of this material is permitted; permission from IEEE must be obtained for all other uses

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Calibration — 6× in this paper · explained in 7 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes

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