[HTML][HTML] Leveraging reinforcement learning for dynamic traffic control: A survey and challenges for field implementation
In recent years, the advancement of artificial intelligence techniques has led to significant
interest in reinforcement learning (RL) within the traffic and transportation community …
interest in reinforcement learning (RL) within the traffic and transportation community …
Cooperative Route Guidance and Flow Control for Mixed Road Networks Comprising Expressway and Arterial Network
Facing the congestion challenges of mixed road networks comprising expressways and
arterial road networks, traditional control solutions fall short. To effectively alleviate traffic …
arterial road networks, traditional control solutions fall short. To effectively alleviate traffic …
[HTML][HTML] Advancing Traffic Simulation Precision and Scalability: A Data-Driven Approach Utilizing Deep Neural Networks
R Hao, T Ruan - Sustainability, 2024 - mdpi.com
In traditional traffic simulation studies, vehicle behavior has typically been modeled using
complex analytical frameworks, which often struggle to encompass the full range of …
complex analytical frameworks, which often struggle to encompass the full range of …
An Attention Reinforcement Learning–Based Strategy for Large-Scale Adaptive Traffic Signal Control System
This paper proposes a reinforcement learning (RL)-based traffic control strategy integrated
with attention mechanism for large-scale adaptive traffic signal control (ATSC) system. The …
with attention mechanism for large-scale adaptive traffic signal control (ATSC) system. The …