Macroscopic modeling and dynamic control of on-street cruising-for-parking of autonomous vehicles in a multi-region urban road network

C Zhao, F Liao, X Li, Y Du - Transportation Research Part C: Emerging …, 2021 - Elsevier
The spatio-temporal imbalance of parking demand and supply results in unwanted on-street
cruising-for-parking traffic of conventional vehicles. Autonomous vehicles (AVs) can self …

Data efficient reinforcement learning and adaptive optimal perimeter control of network traffic dynamics

C Chen, YP Huang, WHK Lam, TL Pan, SC Hsu… - … Research Part C …, 2022 - Elsevier
Existing data-driven and feedback traffic control strategies do not consider the heterogeneity
of real-time data measurements. Besides, traditional reinforcement learning (RL) methods …

[HTML][HTML] Modeling, estimation, and control in large-scale urban road networks with remaining travel distance dynamics

II Sirmatel, D Tsitsokas, A Kouvelas… - … Research Part C …, 2021 - Elsevier
City-scale control of urban road traffic poses a challenging problem. Dynamical models
based on the macroscopic fundamental diagram (MFD) enable development of model …

Perimeter control with real-time location-varying cordon

Y Li, R Mohajerpoor, M Ramezani - Transportation Research Part B …, 2021 - Elsevier
With unbalanced travel demand distribution over time and space, a stationary cordon
location hinders the full potential of perimeter flow control based on network Macroscopic …

An actor-critic deep reinforcement learning approach for metro train scheduling with rolling stock circulation under stochastic demand

C Ying, AHF Chow, KS Chin - Transportation Research Part B …, 2020 - Elsevier
This paper presents a novel actor-critic deep reinforcement learning approach for metro train
scheduling with circulation of limited rolling stock. The scheduling problem is modeled as a …

Hierarchical control for stochastic network traffic with reinforcement learning

ZC Su, AHF Chow, CL Fang, EM Liang… - … Research Part B …, 2023 - Elsevier
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 …

Percolation-based dynamic perimeter control for mitigating congestion propagation in urban road networks

H Hamedmoghadam, N Zheng, D Li, HL Vu - Transportation research part …, 2022 - Elsevier
Perimeter control regulates the traffic flows between different regions of a road network by
coordinating the signal timings at region boundaries with the aim of improving the overall …

Scalable multi-region perimeter metering control for urban networks: A multi-agent deep reinforcement learning approach

D Zhou, VV Gayah - Transportation Research Part C: Emerging …, 2023 - Elsevier
Perimeter metering control based on macroscopic fundamental diagrams has attracted
increasing research interests over the past decade. This strategy provides a convenient way …

Resilient perimeter control for hyper-congested two-region networks with MFD dynamics

S Gao, D Li, N Zheng, R Hu, Z She - Transportation Research Part B …, 2022 - Elsevier
Understanding the resilience of transportation networks has received considerable research
attention. Nevertheless in the field of network traffic flow control, few control approaches …

Model-free perimeter metering control for two-region urban networks using deep reinforcement learning

D Zhou, VV Gayah - Transportation Research Part C: Emerging …, 2021 - Elsevier
Various perimeter metering control strategies have been proposed for urban traffic networks
that rely on the existence of well-defined relationships between network productivity and …