no code implementations • 18 Mar 2024 • Shengchao Yan, Lukas König, Wolfram Burgard
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.
no code implementations • 11 Jun 2021 • Shengchao Yan, Tim Welschehold, Daniel Büscher, Wolfram Burgard
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.
no code implementations • 9 Mar 2020 • Shengchao Yan, Jingwei Zhang, Daniel Büscher, Wolfram Burgard
In this paper we present an approach to learning policies for signal controllers using deep reinforcement learning aiming for optimized traffic flow.