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Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network
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 …
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
Public charging station occupancy prediction plays key importance in develo** a smart
charging strategy to reduce electric vehicle (EV) operator and user inconvenience. However …
charging strategy to reduce electric vehicle (EV) operator and user inconvenience. However …
Intelligent electric vehicle charging recommendation based on multi-agent reinforcement learning
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 …
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
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 …
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 …
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
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 …
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
Electric vehicles (EVs) are being rapidly adopted due to their economic and societal
benefits. Autonomous mobility-on-demand (AMoD) systems also embrace this trend …
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
Electric vehicles (EVs) play critical roles in autonomous mobility-on-demand (AMoD)
systems, but their unique charging patterns increase the model uncertainties in 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
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 …
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 …
improve the operation and energy-efficiency of transportation systems. This paper discusses …