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Single-Agent Actor Critic for Decentralized Cooperative Driving
To bridge this gap and advance the field of active traffic management towards greater decentralization, we introduce a novel asymmetric actor-critic model aimed at learning decentralized cooperative driving policies for autonomous vehicles using single-agent reinforcement learning.
Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning
Our reinforcement learning agent learns a policy for a centralized controller to let connected autonomous vehicles at unsignalized intersections give up their right of way and yield to other vehicles to optimize traffic flow.
Efficiency and Equity are Both Essential: A Generalized Traffic Signal Controller with Deep Reinforcement Learning
In this paper we present an approach to learning policies for signal controllers using deep reinforcement learning aiming for optimized traffic flow.
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