Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network

S Wang, A Chen, P Wang, C Zhuge - Transportation Research Part C …, 2023 - Elsevier
Abstract Short-term Electric Vehicle (EV) charging demand prediction is an essential task in
the fields of smart grid and intelligent transportation systems, as understanding the …

[HTML][HTML] Multistep electric vehicle charging station occupancy prediction using hybrid LSTM neural networks

TY Ma, S Faye - Energy, 2022 - Elsevier
Public charging station occupancy prediction plays key importance in develo** a smart
charging strategy to reduce electric vehicle (EV) operator and user inconvenience. However …

Intelligent electric vehicle charging recommendation based on multi-agent reinforcement learning

W Zhang, H Liu, F Wang, T Xu, H **n, D Dou… - Proceedings of the Web …, 2021 - dl.acm.org
Electric Vehicle (EV) has become a preferable choice in the modern transportation system
due to its environmental and energy sustainability. However, in many large cities, EV drivers …

Fleet rebalancing for expanding shared e-mobility systems: A multi-agent deep reinforcement learning approach

M Luo, B Du, W Zhang, T Song, K Li… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The electrification of shared mobility has become popular across the globe. Many cities have
their new shared e-mobility systems deployed, with continuously expanding coverage from …

Optimal fast charging station locations for electric ridesharing with vehicle-charging station assignment

TY Ma, S **e - Transportation Research Part D: Transport and …, 2021 - Elsevier
Electrified shared mobility services need to handle charging infrastructure planning and
manage their daily charging operations to minimize total charging operation time and cost …

An intelligent recommendation for intelligently accessible charging stations: Electronic vehicle charging to support a sustainable smart tourism city

P Suanpang, P Jamjuntr, P Kaewyong, C Niamsorn… - Sustainability, 2022 - mdpi.com
The world is entering an era of awareness of the preservation of natural energy
sustainability. Therefore, electric vehicles (EVs) have become a popular alternative in …

Data-driven distributionally robust electric vehicle balancing for autonomous mobility-on-demand systems under demand and supply uncertainties

S He, Z Zhang, S Han, L Pepin, G Wang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Electric vehicles (EVs) are being rapidly adopted due to their economic and societal
benefits. Autonomous mobility-on-demand (AMoD) systems also embrace this trend …

A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems

S He, Y Wang, S Han, S Zou, F Miao - arxiv preprint arxiv:2209.08230, 2022 - arxiv.org
Electric vehicles (EVs) play critical roles in autonomous mobility-on-demand (AMoD)
systems, but their unique charging patterns increase the model uncertainties in AMoD …

RLCharge: Imitative multi-agent spatiotemporal reinforcement learning for electric vehicle charging station recommendation

W Zhang, H Liu, H **ong, T Xu, F Wang… - … on Knowledge and …, 2022 - ieeexplore.ieee.org
Electric Vehicle (EV) has become a preferable choice in the modern transportation system
due to its environmental and energy sustainability. However, in many large cities, EV drivers …

A framework for integrated dispatching and charging management of an autonomous electric vehicle ride-hailing fleet

Z Yi, J Smart - Transportation Research Part D: Transport and …, 2021 - Elsevier
The convergence of electrification and automated driving will introduce opportunities to
improve the operation and energy-efficiency of transportation systems. This paper discusses …