4 papers · 1 filter
Balancing Efficiency and Fairness in Traffic Light Control through Deep Reinforcement Learning
Matteo Cederle, Giacomo Scatto, Gian Antonio Susto
Urban traffic congestion presents a significant challenge for modern cities, which impacts mobility and sustainability. Traditional traffic light control systems often fail to adap…
Towards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control
Riccardo De Monte, Matteo Cederle, Gian Antonio Susto
State-of-the-art deep reinforcement learning (RL) methods have achieved remarkable performance in continuous control tasks, yet their computational complexity is often incompatible…
Explainable Anomaly Detection for Electric Vehicles Charging Stations
Matteo Cederle, Andrea Mazzucco, Andrea Demartini +4
Electric vehicles (EV) charging stations are one of the critical infrastructures needed to support the transition to renewable-energy-based mobility, but ensuring their reliability…
Towards Explainable Anomaly Detection in Shared Mobility Systems
Elnur Isgandarov, Matteo Cederle, Federico Chiariotti +1
Shared mobility systems, such as bike-sharing networks, play a crucial role in urban transportation. Identifying anomalies in these systems is essential for optimizing operations,…