Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-agent Deep Reinforcement Learning Approach

1 code implementation • 11 Nov 2022 • Man Luo, Bowen Du, Wenzhe Zhang, Tianyou Song, Kun Li, HongMing Zhu, Mark Birkin, Hongkai Wen

This is particularly challenging in the context of expanding systems, because i) the range of the EVs is limited while charging time is typically long, which constrain the viable rebalancing operations; and ii) the EV stations in the system are dynamically changing, i. e., the legitimate targets for rebalancing operations can vary over time.

Multi-agent Reinforcement Learning

Deployment Optimization for Shared e-Mobility Systems with Multi-agent Deep Neural Search

no code implementations • 3 Nov 2021 • Man Luo, Bowen Du, Konstantin Klemmer, HongMing Zhu, Hongkai Wen

Shared e-mobility services have been widely tested and piloted in cities across the globe, and already woven into the fabric of modern urban planning.