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stat.ML2020★ 4 cited
QTIP: Quick simulation-based adaptation of Traffic model per Incident Parameters
Inon Peled, Raghuveer Kamalakar, Carlos Lima Azevedo +1
Current data-driven traffic prediction models are usually trained with large datasets, e.g. several months of speeds and flows. Such models provide very good fit for ordinary road…
stat.ML2019
Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures
Filipe Rodrigues, Carlos Lima Azevedo
Reinforcement learning (RL) constitutes a promising solution for alleviating the problem of traffic congestion. In particular, deep RL algorithms have been shown to produce adaptiv…