Multi-agent Decision-making at Unsignalized Intersections with Reinforcement Learning from Demonstrations
Intersections are key nodes and also bottlenecks of urban road networks, so improving the
traffic efficiency at intersections is beneficial to improving overall traffic throughput and …
traffic efficiency at intersections is beneficial to improving overall traffic throughput and …
Autonomous Intersection Management with Heterogeneous Vehicles: A Multi-Agent Reinforcement Learning Approach
K Chen, B Li, R Zhang, X Cheng - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
While autonomous intersection management (AIM) emerges to facilitate signal-free
scheduling for connected and autonomous vehicles (CAVs), several challenges arise for …
scheduling for connected and autonomous vehicles (CAVs), several challenges arise for …
Cooperative Decision-Making for CAVs at Unsignalized Intersections: A MARL Approach with Attention and Hierarchical Game Priors
The development of autonomous vehicles has shown great potential to enhance the
efficiency and safety of transportation systems. However, the decision-making issue in …
efficiency and safety of transportation systems. However, the decision-making issue in …
Hierarchical reinforcement learning for dynamic autonomous vehicle navigation at intelligent intersections
Recent years have witnessed the rapid development of the Cooperative Vehicle
Infrastructure System (CVIS), where road infrastructures such as traffic lights (TL) and …
Infrastructure System (CVIS), where road infrastructures such as traffic lights (TL) and …
Parameter sharing reinforcement learning for modeling multi-agent driving behavior in roundabout scenarios
F Konstantinidis, M Sackmann… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
Modeling other drivers' behavior in highly interactive traffic situations, such as roundabouts,
is a challenging task. We address this task using a Multi-Agent Reinforcement Learning …
is a challenging task. We address this task using a Multi-Agent Reinforcement Learning …
Learning from Oracle demonstrations—a new approach to develop autonomous intersection management control algorithms based on multiagent deep reinforcement …
A Guillen-Perez, MD Cano - IEEE Access, 2022 - ieeexplore.ieee.org
Worldwide, many companies are working towards safe and innovative control systems for
Autonomous Vehicles (AVs). A key component is Autonomous Intersection Management …
Autonomous Vehicles (AVs). A key component is Autonomous Intersection Management …
Coordination for connected and automated vehicles at non-signalized intersections: A value decomposition-based multiagent deep reinforcement learning approach
Z Guo, Y Wu, L Wang, J Zhang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The recent proliferation of the research on multi-agent deep reinforcement learning (MDRL)
offers an encouraging way to coordinate multiple connected and automated vehicles (CAVs) …
offers an encouraging way to coordinate multiple connected and automated vehicles (CAVs) …
Real-time intelligent autonomous intersection management using reinforcement learning
U Gunarathna, S Karunasekera… - 2022 IEEE Intelligent …, 2022 - ieeexplore.ieee.org
Autonomous intersection management has the ability to reduce congestion at intersections
significantly, compared to classical traffic signal control in the era of connected autonomous …
significantly, compared to classical traffic signal control in the era of connected autonomous …
Modeling Interaction-Aware Driving Behavior using Graph-Based Representations and Multi-Agent Reinforcement Learning
F Konstantinidis, M Sackmann… - 2023 IEEE 26th …, 2023 - ieeexplore.ieee.org
Modeling the driving behavior of traffic partici-pants in highly interactive traffic situations,
such as roundabouts, poses a significant challenge due to the complex interactions and the …
such as roundabouts, poses a significant challenge due to the complex interactions and the …
AF-DQN: A Large-Scale Decision-Making Method at Unsignalized Intersections with Safe Action Filter and Efficient Exploratory Training Strategy
K Wang, Q Liu, X Li, F Yang - 2024 IEEE Intelligent Vehicles …, 2024 - ieeexplore.ieee.org
Autonomous driving is an advanced field that attracts significant attention and engages
numerous researchers. However, relying solely on a single autonomous vehicle (AV) is …
numerous researchers. However, relying solely on a single autonomous vehicle (AV) is …