State-of-art review of traffic signal control methods: challenges and opportunities
Introduction Due to the menacing increase in the number of vehicles on a daily basis,
abating road congestion is becoming a key challenge these years. To cope-up with the …
abating road congestion is becoming a key challenge these years. To cope-up with the …
[HTML][HTML] A survey on clustering methods for distributed and networked control systems
Clustering strategies are becoming increasingly relevant to boost the scalability of
distributed control methods by focusing the cooperation efforts on highly coupled agents …
distributed control methods by focusing the cooperation efforts on highly coupled agents …
[HTML][HTML] Stabilization of city-scale road traffic networks via macroscopic fundamental diagram-based model predictive perimeter control
II Sirmatel, N Geroliminis - Control Engineering Practice, 2021 - Elsevier
Traffic control for large-scale urban road networks remains a challenging problem.
Aggregated dynamical models of city-scale traffic, based on the macroscopic fundamental …
Aggregated dynamical models of city-scale traffic, based on the macroscopic fundamental …
Data efficient reinforcement learning and adaptive optimal perimeter control of network traffic dynamics
Existing data-driven and feedback traffic control strategies do not consider the heterogeneity
of real-time data measurements. Besides, traditional reinforcement learning (RL) methods …
of real-time data measurements. Besides, traditional reinforcement learning (RL) methods …
[HTML][HTML] Two-layer adaptive signal control framework for large-scale dynamically-congested networks: Combining efficient Max Pressure with Perimeter Control
Traffic-responsive signal control is a cost-effective, easy-to-implement, network management
strategy, bearing high potential to improve performance in heavily congested networks with …
strategy, bearing high potential to improve performance in heavily congested networks with …
[HTML][HTML] Hybrid perimeter control with real-time partitions in heterogeneous urban networks: An integration of deep learning and MPC
S Jiang, M Keyvan-Ekbatani - Transportation Research Part C: Emerging …, 2023 - Elsevier
Network-wide perimeter control strategies have been shown promise in recent years. These
perimeter control strategies are mostly based on networks with fixed boundaries. However …
perimeter control strategies are mostly based on networks with fixed boundaries. However …
[HTML][HTML] Modeling, estimation, and control in large-scale urban road networks with remaining travel distance dynamics
City-scale control of urban road traffic poses a challenging problem. Dynamical models
based on the macroscopic fundamental diagram (MFD) enable development of model …
based on the macroscopic fundamental diagram (MFD) enable development of model …
Data driven model free adaptive iterative learning perimeter control for large-scale urban road networks
Most perimeter control methods in literature are the model-based schemes designing the
controller based on the available accurate macroscopic fundamental diagram (MFD) …
controller based on the available accurate macroscopic fundamental diagram (MFD) …
Hierarchical control for stochastic network traffic with reinforcement learning
This study proposes a hierarchical control framework to maximize the throughput of a road
network driven by travel demand with uncertainties. In the upper level, a perimeter controller …
network driven by travel demand with uncertainties. In the upper level, a perimeter controller …
Network-scale traffic prediction via knowledge transfer and regional MFD analysis
Network traffic flow prediction on a fine-grained spatio-temporal scale is essential for
intelligent transportation systems, and extensive studies have been carried out in this area …
intelligent transportation systems, and extensive studies have been carried out in this area …