Distributed Traffic Signal Control for Maximum Network Throughput [PDF]
, 2012 We propose a distributed algorithm for controlling traffic signals. Our algorithm is adapted from backpressure routing, which has been mainly applied to communication and power networks.
Frazzoli, Emilio +4 more
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Model-Based Deep Reinforcement Learning with Traffic Inference for Traffic Signal Control
Applied Sciences, 2023 In the modern world, the extremely rapid growth of traffic demand has become a major problem for urban traffic development. Continuous optimization of signal control systems is an important way to relieve traffic pressure in cities. In recent years, with
Hao Wang, Jinan Zhu, Bao Gu
doaj +1 more source
Traffic signal control using queueing theory [PDF]
, 2018 Traffic signal control has drawn considerable attention in the literatures thanks to its ability to improve the mobility of urban networks. Queueing models are capable of capturing performance or effectiveness of a queueing system. In this report, SOCPs (
Liu, Hao
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Traffic Signal Control Based on Deep Reinforcement Learning A2C Integrated with State Prediction [PDF]
Jisuanji gongchengExisting reinforcement learning-based traffic signal control methods primarily utilize historical and real-time traffic states at the current time step to determine the control strategy for the next time step.
YE Baolin, SUN Ruitao, LI Lingxi, WU Weimin
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A Person-Based Adaptive Traffic Signal Control Method with Cooperative Transit Signal Priority
Journal of Advanced Transportation, 2022 Real-time traffic signal control has long been a critical way to improve traffic congestion. Transit Signal Priority (TSP) is seen as a cost-effective way to reduce travel time variability.
Wei-Hsun Lee, Hsuan-Chih Wang
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Multiple traffic signal control using a genetic algorithm [PDF]
, 1999 Optimising traffic signal timings for a multiple-junction road network is a difficult but important problem. The essential difficulty of this problem is that the traffic signals need to coordinate their behaviours to achieve the common goal of optimising
Cumming, A, Kalganova, T, Russell, G
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An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review
Information, 2017 In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion.
Peng Jing, Hao Huang, Long Chen
doaj +1 more source
Impact of traffic management on black carbon emissions: a microsimulation study [PDF]
, 2015 This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black ...
Beckx, C +7 more
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Human‐centric multimodal deep (HMD) traffic signal control
IET Intelligent Transport Systems, 2023 Reinforcement learning (RL)‐based models have been widely studied for traffic signal control with objectives, such as minimizing vehicle delay and queue length, maximizing vehicle throughput, and improving road safety, through tailored reward designs ...
Leizhen Wang +3 more
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A bi-level model of dynamic traffic signal control with continuum approximation [PDF]
, 2015 This paper proposes a bi-level model for traffic network signal control, which is formulated as a dynamic Stackelberg game and solved as a mathematical program with equilibrium constraints (MPEC).
Friesz, TL +4 more
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