Edge-enhanced Graph Attention Network for driving decision-making of autonomous vehicles via Deep Reinforcement Learning
Y Qiang, X Wang, X Liu, Y Wang… - Proceedings of the …, 2024 - journals.sagepub.com
Despite the rapid advancement in the field of autonomous driving vehicles, developing a
safe and sensible decision-making system remains a challenging problem. The driving …
safe and sensible decision-making system remains a challenging problem. The driving …
Graph Reinforcement Learning-Based Decision-Making Technology for Connected and Autonomous Vehicles: Framework, Review, and Future Trends
The proper functioning of connected and autonomous vehicles (CAVs) is crucial for the
safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully …
safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully …
Graph convolution-based deep reinforcement learning for multi-agent decision-making in mixed traffic environments
An efficient and reliable multi-agent decision-making system is highly demanded for the safe
and efficient operation of connected autonomous vehicles in intelligent transportation …
and efficient operation of connected autonomous vehicles in intelligent transportation …
Graph reinforcement learning application to co-operative decision-making in mixed autonomy traffic: Framework, survey, and challenges
Proper functioning of connected and automated vehicles (CAVs) is crucial for the safety and
efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous …
efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous …
SIF-STGDAN: A Social Interaction Force Spatial-Temporal Graph Dynamic Attention Network for Decision-Making of Connected and Autonomous Vehicles
Q Liu, Y Tang, X Li, F Yang, X Gao… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
The collaborative decision-making technology of connected and autonomous vehicles
(CAVs) is critical in today's autonomous driving. Recently, graph reinforcement learning …
(CAVs) is critical in today's autonomous driving. Recently, graph reinforcement learning …
Multi-agent decision-making modes in uncertain interactive traffic scenarios via graph convolution-based deep reinforcement learning
X Gao, X Li, Q Liu, Z Li, F Yang, T Luan - Sensors, 2022 - mdpi.com
As one of the main elements of reinforcement learning, the design of the reward function is
often not given enough attention when reinforcement learning is used in concrete …
often not given enough attention when reinforcement learning is used in concrete …
Graph convolution-based deep reinforcement learning for multi-agent decision-making in interactive traffic scenarios
A reliable multi-agent decision-making system is highly demanded for safe and efficient
operations of connected and autonomous vehicles (CAVs). In order to represent the mutual …
operations of connected and autonomous vehicles (CAVs). In order to represent the mutual …
Multi-Vehicles Decision-Making in Interactive Highway Exit: A Graph Reinforcement Learning Approach
X Gao, T Luan, X Li, Q Liu, Z Li… - 2022 IEEE 17th …, 2022 - ieeexplore.ieee.org
In the research of driverless decision-making, most of the current research is aimed at
following, changing lanes, overtaking, and other scenarios. In this paper, algorithms and …
following, changing lanes, overtaking, and other scenarios. In this paper, algorithms and …
Dueling deep Q network for highway decision making in autonomous vehicles: A case study
This work optimizes the highway decision making strategy of autonomous vehicles by using
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …
deep reinforcement learning (DRL). First, the highway driving environment is built, wherein …
DRL-GAT-SA: Deep reinforcement learning for autonomous driving planning based on graph attention networks and simplex architecture
Y Peng, G Tan, H Si, J Li - Journal of Systems Architecture, 2022 - Elsevier
Self-driving cars need to make decisions while sharing the road with human drivers whose
behavior is uncertain. However, the presence of uncertainty leads to a trade-off between two …
behavior is uncertain. However, the presence of uncertainty leads to a trade-off between two …
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