[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 …
Macroscopic network-level traffic models: Bridging fifty years of development toward the next era
Network macroscopic fundamental diagrams (NMFD) and related network-level traffic
dynamics models have received both theoretical support and empirical validation with the …
dynamics models have received both theoretical support and empirical validation with the …
Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control
Real traffic data and simulation analysis reveal that for some urban networks a well-defined
Macroscopic Fundamental Diagram (MFD) exists, which provides a unimodal and low …
Macroscopic Fundamental Diagram (MFD) exists, which provides a unimodal and low …
Max pressure control of a network of signalized intersections
P Varaiya - Transportation Research Part C: Emerging …, 2013 - Elsevier
The control of a network of signalized intersections is considered. Vehicles arrive in iid
(independent, identically distributed) streams at entry links, independently make turns at …
(independent, identically distributed) streams at entry links, independently make turns at …
Enhancing model-based feedback perimeter control with data-driven online adaptive optimization
Most feedback perimeter control approaches that are based on the Macroscopic
Fundamental Diagram (MFD) and are tested in detailed network structures restrict inflow …
Fundamental Diagram (MFD) and are tested in detailed network structures restrict inflow …
[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 …
Economic model predictive control of large-scale urban road networks via perimeter control and regional route guidance
II Sirmatel, N Geroliminis - IEEE Transactions on Intelligent …, 2017 - ieeexplore.ieee.org
Local traffic control schemes fall short of achieving coordination with other parts of the urban
road network, whereas a centralized controller based on the detailed traffic models would …
road network, whereas a centralized controller based on the detailed traffic models would …
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 …
Equilibrium analysis and route guidance in large-scale networks with MFD dynamics
Recent studies have demonstrated that Macroscopic Fundamental Diagram (MFD), which
provides an aggregated model of urban traffic dynamics linking network production and …
provides an aggregated model of urban traffic dynamics linking network production and …
[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 …