Multi-agent reinforcement learning for connected and automated vehicles control: Recent advancements and future prospects

M Hua, D Chen, X Qi, K Jiang, ZE Liu, Q Zhou… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Connected and automated vehicles (CAVs) are considered a potential solution for future
transportation challenges, aiming to develop systems that are efficient, safe, and …

A cognitive-based trajectory prediction approach for autonomous driving

H Liao, Y Li, Z Li, C Wang, Z Cui… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
In autonomous vehicle (AV) technology, the ability to accurately predict the movements of
surrounding vehicles is paramount for ensuring safety and operational efficiency …

Safety performance evaluation of freeway merging areas under autonomous vehicles environment using a co-simulation platform

P Chen, H Ni, L Wang, G Yu, J Sun - Accident Analysis & Prevention, 2024‏ - Elsevier
Merging areas serve as the potential bottlenecks for continuous traffic flow on freeways.
Traffic incidents in freeway merging areas are closely related to decision-making errors of …

Physical-informed neural network for MPC-based trajectory tracking of vehicles with noise considered

L **, L Liu, X Wang, M Shang… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
The trajectory tracking plays a vital role in unmanned driving technology. Although
traditional control schemes may yield satisfactory outcomes in dealing with simple linear …

Bevgpt: Generative pre-trained foundation model for autonomous driving prediction, decision-making, and planning

P Wang, M Zhu, X Zheng, H Lu, H Zhong… - IEEE Transactions …, 2024‏ - ieeexplore.ieee.org
Prediction, decision-making, and motion planning are essential for autonomous driving. In
most contemporary works, they are considered individual modules or combined into a multi …

Improved consensus ADMM for cooperative motion planning of large-scale connected autonomous vehicles with limited communication

H Liu, Z Huang, Z Zhu, Y Li, S Shen… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
This paper investigates a cooperative motion planning problem for large-scale connected
autonomous vehicles (CAVs) under limited communications, which addresses the …

Human-like decision making for autonomous driving with social skills

C Zhao, D Chu, Z Deng, L Lu - IEEE Transactions on Intelligent …, 2024‏ - ieeexplore.ieee.org
There may exist long-term mixed traffic that consists of human-driven vehicles (HDV) and
autonomous driving vehicles (ADV). Hence, a formidable challenge arises: the effective …

Automated valet parking and charging: A dynamic pricing and reservation-based framework leveraging multi-agent reinforcement learning

GO Boateng, H Si, H **a, X Guo, C Chen… - IEEE Transactions …, 2024‏ - ieeexplore.ieee.org
Vehicle parking resource provisioning in major cities and urban areas has gradually
become a challenging issue in Intelligent Transportation Systems (ITS) due to the upward …

Collaborative planning and control of heterogeneous multi-ground unmanned platforms

P Xue, D Pi, C Wan, C Yang, B **e, H Wang… - … Applications of Artificial …, 2024‏ - Elsevier
With the rapid development of intelligent vehicles, mobile robots, warehousing and logistics,
exploration and testing and other industries, multi-platform collaborative work research has …

A homogeneous multi-vehicle cooperative group decision-making method in complicated mixed traffic scenarios

Y Wang, J Li, T Ke, Z Ke, J Jiang, S Xu… - … Research Part C …, 2024‏ - Elsevier
Abstract Connected and Automated Vehicles (CAVs) are expected to reshape the
transportation system, and cooperative group intelligence of CAVs has great potential for …