Autonomous driving system: A comprehensive survey

J Zhao, W Zhao, B Deng, Z Wang, F Zhang… - Expert Systems with …, 2024‏ - Elsevier
Automation is increasingly at the forefront of transportation research, with the potential to
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …

Smart City Charging Station allocation for electric vehicles using analytic hierarchy process and multiobjective goal-programming

M Algafri, A Alghazi, Y Almoghathawi, H Saleh… - Applied Energy, 2024‏ - Elsevier
In view of recent developments in urban transport systems, there has been a significant
increase in the presence of electric vehicles on the market. One of the major challenges …

Real-time fast charging station recommendation for electric vehicles in coupled power-transportation networks: A graph reinforcement learning method

P Xu, J Zhang, T Gao, S Chen, X Wang, H Jiang… - International Journal of …, 2022‏ - Elsevier
With the increasing penetration rate of electric vehicles, the fast charging demands of
electric vehicles will have a significant influence on the operation of coupled power …

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 …

Deep Transfer Learning for Detecting Electric Vehicles Highly-Correlated Energy Consumption Parameters

Z Teimoori, A Yassine, C Lu - IEEE Transactions on Artificial …, 2024‏ - ieeexplore.ieee.org
Implementation of advanced intelligent deep learning techniques for Electric Vehicles (EVs)
energy consumption analysis is obstructed by two main subjects. First, the problem of finding …

Online Prediction-Assisted Safe Reinforcement Learning for Electric Vehicle Charging Station Recommendation in Dynamically Coupled Transportation-Power …

Q Liao, G Li, J Yu, Z Gu, W Ma - arxiv preprint arxiv:2407.20679, 2024‏ - arxiv.org
With the proliferation of electric vehicles (EVs), the transportation network and power grid
become increasingly interdependent and coupled via charging stations. The concomitant …

Real-Time Distributed Charging Station Recommendation for Electric Vehicles: A Federated Meta-RL Approach

Y Zhang, J Hu, G Min, J Gao… - IEEE Transactions on …, 2025‏ - ieeexplore.ieee.org
The growth of Electric Vehicles (EVs) places an increasingly heavy burden on the limited
charging infrastructure, necessitating an effective charging station recommendation strategy …

A Reinforcement Learning-based Multistep Prediction Strategy for Burn-Through Point Using State Feature Extractor

J Mu, C Yang, F Yan, C Yang… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Sintering represents a critical link in the steel production process, with the produced sinter
ore serving as the core raw material for blast furnace ironmaking. Characterized by harsh …

Online Spatial-Temporal EV Charging Scheduling with Incentive Promotion

LPY Ting, HY Wang, JY Jhang… - ACM Transactions on …, 2024‏ - dl.acm.org
The growing adoption of electric vehicles (EVs) has resulted in an increased demand for
public EV charging infrastructure. Currently, the collaboration between these stations has …

PDQN: User Preference-Based Charging Station Recommendation

H Lin, X Li, Y Cao, H Labiod… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
With the advent of consumer electronics, Electric Vehicles (EVs) are gradually becoming
representative carriers for the next generation of consumer electronics. EVs are gaining …