Deep Reinforcement Learning for Traffic Light Control in Intelligent Transportation Systems

no code implementations • 4 Feb 2023 • Xiao-Yang Liu, Ming Zhu, Sem Borst, Anwar Walid

In this paper, we investigate deep reinforcement learning to control traffic lights, and both theoretical analysis and numerical experiments show that the intelligent behavior ``greenwave" (i. e., a vehicle will see a progressive cascade of green lights, and not have to brake at any intersection) emerges naturally a grid road network, which is proved to be the optimal policy in an avenue with multiple cross streets.

reinforcement-learning Reinforcement Learning (RL)

Deep Reinforcement Learning for Intelligent Transportation Systems

no code implementations • 3 Dec 2018 • Xiao-Yang Liu, Zihan Ding, Sem Borst, Anwar Walid

Intelligent Transportation Systems (ITSs) are envisioned to play a critical role in improving traffic flow and reducing congestion, which is a pervasive issue impacting urban areas around the globe.

Management reinforcement-learning +1

Transition time asymptotics of queue-based activation protocols in random-access networks

no code implementations • 16 Jul 2018 • Sem Borst, Frank den Hollander, Francesca R. Nardi, Matteo Sfragara

We show that the law of the transition time divided by its mean exhibits a trichotomy, depending on the activation rate functions.

Probability 60K25, 60K30, 90B15, 90B18