A systematic study on reinforcement learning based applications

K Sivamayil, E Rajasekar, B Aljafari, S Nikolovski… - Energies, 2023 - mdpi.com
We have analyzed 127 publications for this review paper, which discuss applications of
Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural …

A comprehensive survey on multi-agent reinforcement learning for connected and automated vehicles

P Yadav, A Mishra, S Kim - Sensors, 2023 - mdpi.com
Connected and automated vehicles (CAVs) require multiple tasks in their seamless
maneuverings. Some essential tasks that require simultaneous management and actions …

Autonomous navigation at unsignalized intersections: A coupled reinforcement learning and model predictive control approach

R Bautista-Montesano, R Galluzzi, K Ruan, Y Fu… - … research part C …, 2022 - Elsevier
This paper develops an integrated safety-enhanced reinforcement learning (RL) and model
predictive control (MPC) framework for autonomous vehicles (AVs) to navigate unsignalized …

Cooperative decision-making of multiple autonomous vehicles in a connected mixed traffic environment: A coalition game-based model

M Fu, S Li, M Guo, Z Yang, Y Sun, C Qiu… - … research part C …, 2023 - Elsevier
Advances in vehicle-networking technologies have enabled vehicles to cooperate in mixed
traffic. However, realizing the cooperative decision-making of multiple connected …

[HTML][HTML] Dynamic adaptive vehicle re-routing strategy for traffic congestion mitigation of grid network

C Wang, T Atkison, H Park - International Journal of Transportation Science …, 2024 - Elsevier
This paper proposes a possible methodology for detecting and mitigating traffic congestion.
This method is carried out using a custom-designed traffic scenario model. The model is fully …

CVLight: Decentralized learning for adaptive traffic signal control with connected vehicles

Z Mo, W Li, Y Fu, K Ruan, X Di - Transportation research part C: emerging …, 2022 - Elsevier
This paper develops a decentralized reinforcement learning (RL) scheme for multi-
intersection adaptive traffic signal control (TSC), called “CVLight”, that leverages data …

[HTML][HTML] A logic Petri net model for dynamic multi-agent game decision-making

H Byeon, C Thingom, I Keshta, M Soni… - Decision Analytics …, 2023 - Elsevier
This study proposes a logical Petri net model to leverage the modeling advantages of Petri
nets in handling batch processing and uncertainty in value passing and to integrate relevant …

[HTML][HTML] Machine Learning in Information and Communications Technology: A Survey

E Dritsas, M Trigka - Information, 2024 - mdpi.com
The rapid growth of data and the increasing complexity of modern networks have driven the
demand for intelligent solutions in the information and communications technology (ICT) …

Digital twin for pedestrian safety warning at a single urban traffic intersection

Y Fu, MK Turkcan, V Anantha, Z Kostic… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
Ensuring the safety of Vulnerable Road Users (VRUs) at intersections is crucial to
enhancing urban traffic systems. This paper introduces a novel intelligent warning system …

[PDF][PDF] Learning Dual Mean Field Games on Graphs.

X Chen, S Liu, X Di - ECAI, 2023 - researchgate.net
Reinforcement learning (RL) has been developed for mean field games over graphs (G-
MFG) in social media and network economics, in which the transition of agents between a …