Antifragile Perimeter Control: Anticipating and Gaining from Disruptions with Reinforcement Learning

no code implementations • 20 Feb 2024 • Linghang Sun, Michail A. Makridis, Alexander Genser, Cristian Axenie, Margherita Grossi, Anastasios Kouvelas

While previous research works have dedicated efforts to improving the robustness or resilience of transportation systems against disruptions, this paper applies the cutting-edge concept of antifragility to better design a traffic control strategy for urban road networks.

Model Predictive Control Reinforcement Learning (RL)

The Fragile Nature of Road Transportation Systems

no code implementations • 1 Feb 2024 • Linghang Sun, Yifan Zhang, Cristian Axenie, Margherita Grossi, Anastasios Kouvelas, Michail A. Makridis

The continuous increase in traffic demand presents a substantial challenge to the optimal operation of urban road networks and the efficiency of traffic control strategies.