Towards explainable traffic signal control for urban networks through genetic programming

WL Liu, J Zhong, P Liang, J Guo, H Zhao… - Swarm and Evolutionary …, 2024‏ - Elsevier
The increasing number of vehicles in urban areas draws significant attention to traffic signal
control (TSC), which can enhance the efficiency of the entire network by properly switching …

Aiotml: A unified modeling language for aiot-based cyber–physical systems

M Hu, E Cao, H Huang, M Zhang… - IEEE transactions on …, 2023‏ - ieeexplore.ieee.org
Due to deeply intertwined physical and hardware/software components together with an
increasing number of interconnected heterogeneous devices powered by artificial …

DTUMOS, digital twin for large-scale urban mobility operating system

H Yeon, T Eom, K Jang, J Yeo - Scientific reports, 2023‏ - nature.com
The advancement of digital twin technology has significantly impacted the utilization of
virtual cities in the realm of smart cities and mobility. Digital twins provide a platform for the …

Dynamic traffic signal control for heterogeneous traffic conditions using Max Pressure and Reinforcement Learning

A Agarwal, D Sahu, R Mohata, K Jeengar… - Expert Systems with …, 2024‏ - Elsevier
Optimization of green signal timing for each phase at a signalized intersection in an urban
area is critical for efficacious traffic management and congestion mitigation. Many algorithms …

Multiple intersections traffic signal control based on cooperative multi-agent reinforcement learning

J Liu, S Qin, M Su, Y Luo, Y Wang, S Yang - Information Sciences, 2023‏ - Elsevier
For the multi-agent traffic signal controls, the traffic signal at each intersection is controlled
by an independent agent. Since the control policy for each agent is dynamic, when the traffic …

Fairlight: Fairness-aware autonomous traffic signal control with hierarchical action space

Y Ye, J Ding, T Wang, J Zhou, X Wei… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Although reinforcement learning (RL) approaches are promising in autonomous traffic signal
control (TSC), they often suffer from the unfairness problem that causes extremely long …

MonitorLight: Reinforcement learning-based traffic signal control using mixed pressure monitoring

Z Fang, F Zhang, T Wang, X Lian, M Chen - Proceedings of the 31st …, 2022‏ - dl.acm.org
Although Reinforcement Learning (RL) has achieved significant success in the Traffic Signal
Control (TSC), most of them focus on the design of RL elements while the impact of the …

Traffic signal optimization control method based on adaptive weighted averaged double deep Q network

Y Chen, H Zhang, M Liu, M Ye, H **e, Y Pan - Applied Intelligence, 2023‏ - Springer
As a critical node and major bottleneck of the urban traffic networks, the control of traffic
signals at road intersections has an essential impact on road traffic flow and congestion …

Towards fast and accurate federated learning with non-iid data for cloud-based iot applications

T Liu, J Ding, T Wang, M Pan, M Chen - Journal of Circuits, Systems …, 2022‏ - World Scientific
As a promising method of central model training on decentralized device data while
securing user privacy, Federated Learning (FL) is becoming popular in the Internet of Things …

A citywide TD‐learning based intelligent traffic signal control for autonomous vehicles: Performance evaluation using SUMO

S Reza, MC Ferreira, JJM Machado… - Expert …, 2025‏ - Wiley Online Library
An autonomous vehicle can sense its environment and operate without human involvement.
Its adequate management in an intelligent transportation system could significantly reduce …