Intelligent vehicle pedestrian light (IVPL): A deep reinforcement learning approach for traffic signal control
Deep reinforcement learning (RL) has been widely studied in traffic signal control. Despite
the promising results that indicate the superiority of deep RL in terms of the quality of …
the promising results that indicate the superiority of deep RL in terms of the quality of …
The real deal: A review of challenges and opportunities in moving reinforcement learning-based traffic signal control systems towards reality
Traffic signal control (TSC) is a high-stakes domain that is growing in importance as traffic
volume grows globally. An increasing number of works are applying reinforcement learning …
volume grows globally. An increasing number of works are applying reinforcement learning …
Exploring the impact of traffic signal control and connected and automated vehicles on intersections safety: A deep reinforcement learning approach
AH Karbasi, H Yang, S Razavi - arXiv preprint arXiv:2405.19236, 2024 - arxiv.org
In transportation networks, intersections pose significant risks of collisions due to conflicting
movements of vehicles approaching from different directions. To address this issue, various …
movements of vehicles approaching from different directions. To address this issue, various …
Alleviating traffic congestion: Developing and evaluating novel multi-agent reinforcement learning traffic light coordination techniques
Traffic congestion costs American cities tens of billions of dollars per year, not to mention its
negative impact on the environment or people's mental health. Novel Markov game models …
negative impact on the environment or people's mental health. Novel Markov game models …