[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 …
Optimal fast charging station locations for electric ridesharing with vehicle-charging station assignment
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 …
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 …
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 …
[PDF][PDF] A robust and constrained multi-agent reinforcement learning framework for electric vehicle 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 …
A framework for integrated dispatching and charging management of an autonomous electric vehicle ride-hailing fleet
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 …
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 …
Joint charging and relocation recommendation for e-taxi drivers via multi-agent mean field hierarchical reinforcement learning
Nowadays, most of the taxi drivers have become users of the relocation recommendation
service offered by online ride-hailing platforms (eg, Uber and Didi Chuxing), which could …
service offered by online ride-hailing platforms (eg, Uber and Didi Chuxing), which could …
Robust electric vehicle balancing of autonomous mobility-on-demand system: A multi-agent reinforcement learning approach
Electric autonomous vehicles (EAVs) are getting attention in future autonomous mobility-on-
demand (AMoD) systems due to their economic and societal benefits. However, EAVs' …
demand (AMoD) systems due to their economic and societal benefits. However, EAVs' …