Evolution of road traffic congestion control: A survey from perspective of sensing, communication, and computation
Road traffic congestion can inevitably degrade road infrastructure and decrease travel
efficiency in urban traffic networks, which can be relieved by employing appropriate …
efficiency in urban traffic networks, which can be relieved by employing appropriate …
Adversarial safety-critical scenario generation using naturalistic human driving priors
K Hao, W Cui, Y Luo, L Xie, Y Bai… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Evaluating the decision-making system is indispensable in developing autonomous
vehicles, while realistic and challenging safety-critical test scenarios play a crucial role …
vehicles, while realistic and challenging safety-critical test scenarios play a crucial role …
Smart edge-enabled traffic light control: Improving reward-communication trade-offs with federated reinforcement learning
Traffic congestion is a costly phenomenon of every-day life. Reinforcement Learning (RL) is
a promising solution due to its applicability to solving complex decision-making problems in …
a promising solution due to its applicability to solving complex decision-making problems in …
Multi-agent Deep Reinforcement Learning collaborative Traffic Signal Control method considering intersection heterogeneity
Abstract Traffic Signal Control (TSC) plays a crucial role in mitigating congestion. The
extensive integration of Deep Reinforcement Learning (DRL) into TSC, fueled by the …
extensive integration of Deep Reinforcement Learning (DRL) into TSC, fueled by the …
DQL-based intelligent scheduling algorithm for automatic driving in massive MIMO V2I scenarios
Y Liao, Z Yin, Z Yang, X Shen - China Communications, 2023 - ieeexplore.ieee.org
Connected and autonomous vehicle (CAV) vehicle to infrastructure (V2I) scenarios have
more stringent requirements on the communication rate, delay, and reliability of the Internet …
more stringent requirements on the communication rate, delay, and reliability of the Internet …
Multi-agent meta-reinforcement learning with coordination and reward shaping for traffic signal control
X Du, J Wang, S Chen - Pacific-Asia Conference on Knowledge Discovery …, 2023 - Springer
Traffic signal control (TSC) plays an important role in alleviating heavy traffic congestion
problem. It is helpful to provide an effective transportation system by optimizing traffic signals …
problem. It is helpful to provide an effective transportation system by optimizing traffic signals …
Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach
Reinforcement Learning (RL) is currently one of the most commonly used techniques for
traffic signal control (TSC), which can adaptively adjust traffic signal phase and duration …
traffic signal control (TSC), which can adaptively adjust traffic signal phase and duration …
Arelative position descriptor for multi-agent reinforcement learning
B Xi, J Liu, S Chen, Y Long, F Gao… - 2023 42nd Chinese …, 2023 - ieeexplore.ieee.org
Since there exists cooperation or competition between the agents in multi-agent systems,
relative position based information becomes very important for agents to learn collaborative …
relative position based information becomes very important for agents to learn collaborative …
Cooperative Learning with Difference Reward in Large-Scale Traffic Signal Control
S Wang, W Yue, Y Chen, X Ji… - 2022 IEEE 25th …, 2022 - ieeexplore.ieee.org
Adaptive traffic signal control (ATSC) can ease the increasing congestion to relieve pressure
on metropolitan transportation systems. In a large-scale road network, ATSC has a high …
on metropolitan transportation systems. In a large-scale road network, ATSC has a high …
Decentralized Multi Agent Deep Reinforcement Q-Learning for Intelligent Traffic Controller
B Thamilselvam, S Kalyanasundaram… - … Conference on Artificial …, 2023 - Springer
Recent development of deep reinforcement learning models has impacted many fields,
especially decision based control systems. Urban traffic signal control minimizes traffic …
especially decision based control systems. Urban traffic signal control minimizes traffic …