[HTML][HTML] Reinforcement learning in urban network traffic signal control: A systematic literature review
Improvement of traffic signal control (TSC) efficiency has been found to lead to improved
urban transportation and enhanced quality of life. Recently, the use of reinforcement …
urban transportation and enhanced quality of life. Recently, the use of reinforcement …
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 …
Mixed flow of autonomous and human-driven vehicles: Analytical headway modeling and optimal lane management
R Mohajerpoor, M Ramezani - Transportation research part C: emerging …, 2019 - Elsevier
Presence of autonomous vehicles (AVs) affects traffic flow characteristics of a mixed traffic
stream comprising human-driven vehicles. To model the impact of AVs on the saturation flow …
stream comprising human-driven vehicles. To model the impact of AVs on the saturation flow …
Perimeter control with real-time location-varying cordon
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 …
location hinders the full potential of perimeter flow control based on network Macroscopic …
H∞ robust perimeter flow control in urban networks with partial information feedback
Perimeter control is an effective city-scale solution to tackle congestion problems in urban
networks. To accommodate the unpredictable dynamics of congestion propagation, it is …
networks. To accommodate the unpredictable dynamics of congestion propagation, it is …
Short-term traffic flow prediction based on faded memory Kalman Filter fusing data from connected vehicles and Bluetooth sensors
A Emami, M Sarvi, SA Bagloee - Simulation Modelling Practice and Theory, 2020 - Elsevier
This paper proposes a Kalman Filter (KF) technique to predict the short-term flow at urban
arterials based on the information of connected and Bluetooth equipped vehicles. Online …
arterials based on the information of connected and Bluetooth equipped vehicles. Online …
Real-time decentralized traffic signal control for congested urban networks considering queue spillbacks
This paper proposes a decentralized network-level traffic signal control method addressing
the effects of queue spillbacks. The method is traffic-responsive, does not require data …
the effects of queue spillbacks. The method is traffic-responsive, does not require data …
Adaptive network traffic control with an integrated model-based and data-driven approach and a decentralised solution method
This paper presents an adaptive traffic controller for stochastic road networks with an
integrated model-based and data-driven solution framework. The model-based optimisation …
integrated model-based and data-driven solution framework. The model-based optimisation …
CycLight: Learning traffic signal cooperation with a cycle-level strategy
This study introduces CycLight, a novel cycle-level deep reinforcement learning (RL)
approach for network-level adaptive traffic signal control (NATSC) systems. Traditional RL …
approach for network-level adaptive traffic signal control (NATSC) systems. Traditional RL …
Urban safety: an image-processing and deep-learning-based intelligent traffic management and control system
S Reza, HS Oliveira, JJM Machado, JMRS Tavares - Sensors, 2021 - mdpi.com
With the rapid growth and development of cities, Intelligent Traffic Management and Control
(ITMC) is becoming a fundamental component to address the challenges of modern urban …
(ITMC) is becoming a fundamental component to address the challenges of modern urban …