[HTML][HTML] Two-layer adaptive signal control framework for large-scale dynamically-congested networks: Combining efficient Max Pressure with Perimeter Control

D Tsitsokas, A Kouvelas, N Geroliminis - Transportation Research Part C …, 2023 - Elsevier
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 …

N-MP: A network-state-based Max Pressure algorithm incorporating regional perimeter control

H Liu, VV Gayah - Transportation Research Part C: Emerging …, 2024 - Elsevier
Abstract The Max Pressure (MP) framework has been shown to be an effective real-time
decentralized traffic signal control algorithm. However, despite its superior performance and …

OCC-MP: A Max-Pressure framework to prioritize transit and high occupancy vehicles

T Ahmed, H Liu, VV Gayah - Transportation Research Part C: Emerging …, 2024 - Elsevier
Max-pressure (MP) is a decentralized adaptive traffic signal control approach that has been
shown to maximize throughput for private vehicles. However, MP-based signal control …

Smoothing-MP: A novel max-pressure signal control considering signal coordination to smooth traffic in urban networks

T Xu, S Barman, MW Levin - Transportation Research Part C: Emerging …, 2024 - Elsevier
Decentralized traffic signal control methods, such as max-pressure (MP) control or back-
pressure (BP) control, have gained increasing attention in recent years. MP control, in …

A max pressure algorithm for traffic signals considering pedestrian queues

H Liu, VV Gayah, MW Levin - Transportation Research Part C: Emerging …, 2024 - Elsevier
This paper proposes a novel max-pressure (MP) algorithm that incorporates pedestrian
traffic into the MP control architecture. Pedestrians are modeled as being included in one of …

[HTML][HTML] Backpressure or no backpressure? Two simple examples

MJ Smith, R Mounce - Transportation research part C: emerging …, 2024 - Elsevier
Many responsive traffic signal control strategies are “pressure-driven”. These strategies
move green-time from stages with a lower pressure to stages with a higher pressure, at each …

Cooperative Traffic Signal Control Using a Distributed Agent-Based Deep Reinforcement Learning With Incentive Communication

B Zhou, Q Zhou, S Hu, D Ma, S **… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Deep Reinforcement Learning has shown some promise in dynamic traffic signal control by
adapting to real-time traffic conditions. However, multi-intersection control presents …

Fusing crowdsourced data to an adaptive wireless traffic signal control system architecture

A Agarwal, D Sahu, A Nautiyal, M Gupta, P Agarwal - Internet of Things, 2024 - Elsevier
In this study, a novel wireless adaptive traffic signal control System architecture is proposed,
in which crowdsourced data is integrated to detect the traffic state on each approach of an …

C-MP: A decentralized adaptive-coordinated traffic signal control using the Max Pressure framework

T Ahmed, H Liu, VV Gayah - arxiv preprint arxiv:2407.01421, 2024 - arxiv.org
Coordinated traffic signals seek to provide uninterrupted flow through a series of closely
spaced intersections, typically using pre-defined fixed signal timings and offsets. Adaptive …

[HTML][HTML] Identification of optimal locations of adaptive traffic signal control using heuristic methods

T Ahmed, H Liu, VV Gayah - International journal of transportation science …, 2024 - Elsevier
Abstract Adaptive Traffic Signal Control (ATSC) adjusts signal timings to real-time traffic
measurements, increasing operational efficiency within a network. However, ATSC is both …