Towards explainable traffic signal control for urban networks through genetic programming
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 …
control (TSC), which can enhance the efficiency of the entire network by properly switching …
EvoTSC: An evolutionary computation-based traffic signal controller for large-scale urban transportation networks
Abstract Traffic Signal Control (TSC) is a crucial component in the modern intelligent
transportation systems. Typically, the TSC can be formulated as a bilevel optimization …
transportation systems. Typically, the TSC can be formulated as a bilevel optimization …
Boosted genetic algorithm using machine learning for traffic control optimization
T Mao, AS Mihăită, F Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traffic control optimization is a challenging task for various traffic centers around the world
and the majority of existing approaches focus only on developing adaptive methods for …
and the majority of existing approaches focus only on developing adaptive methods for …
PlanLight: learning to optimize traffic signal control with planning and iterative policy improvement
Intelligent traffic signal control (TSC) is essential for transportation efficiency in modern road
networks. There is an emerging trend of using deep reinforcement learning techniques to …
networks. There is an emerging trend of using deep reinforcement learning techniques to …
[HTML][HTML] Advance traffic signal control systems with emerging technologies
J Jin - 2018 - diva-portal.org
Nowadays, traffic congestion poses critical problems including the undermined mobility and
sustainability efficiencies. Mitigating traffic congestions in urban areas is a crucial task for …
sustainability efficiencies. Mitigating traffic congestions in urban areas is a crucial task for …
Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal control
Many studies confirmed that a proper traffic state representation is more important than
complex algorithms for the classical traffic signal control (TSC) problem. In this paper, we (1) …
complex algorithms for the classical traffic signal control (TSC) problem. In this paper, we (1) …
Reinforcement learning for traffic signal control: Incorporating a virtual mesoscopic model for depicting oversaturated traffic conditions
H Lee, Y Han, Y Kim - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Recently, with increasing urban traffic congestion, there has been an upsurge in studies on
reinforcement learning for traffic signal control (RL-TSC), which enables efficient traffic …
reinforcement learning for traffic signal control (RL-TSC), which enables efficient traffic …
Traffic signal control for smart cities using reinforcement learning
H Joo, SH Ahmed, Y Lim - Computer Communications, 2020 - Elsevier
Traffic congestion is increasing globally, and this problem needs to be addressed by the
traffic management system. Traffic signal control (TSC) is an effective method among various …
traffic management system. Traffic signal control (TSC) is an effective method among various …
Presslight: Learning max pressure control to coordinate traffic signals in arterial network
Traffic signal control is essential for transportation efficiency in road networks. It has been a
challenging problem because of the complexity in traffic dynamics. Conventional …
challenging problem because of the complexity in traffic dynamics. Conventional …
A survey on traffic signal control methods
Traffic signal control is an important and challenging real-world problem, which aims to
minimize the travel time of vehicles by coordinating their movements at the road …
minimize the travel time of vehicles by coordinating their movements at the road …