An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control

Abstract Traffic Signal Control (TSC) is a fundamental task in modern intelligent transport systems. TSC is often formulated as a bi‐level optimization problem, comprised by the signal timing at the upper level and the Dynamic User Equilibrium (DUE) traffic assignment at the lower level. Since DUE i...

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Main Authors: Wei‐Li Liu, Yue‐Jiao Gong, Wei‐Neng Chen, Jun Zhang, Zhi Dou
Format: Article
Language:English
Published: Wiley 2021-05-01
Series:IET Intelligent Transport Systems
Online Access:https://doi.org/10.1049/itr2.12049
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spelling doaj-072bc894b15f42568ad63444bae931b92021-07-14T13:20:13ZengWileyIET Intelligent Transport Systems1751-956X1751-95782021-05-0115561963410.1049/itr2.12049An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal controlWei‐Li Liu0Yue‐Jiao Gong1Wei‐Neng Chen2Jun Zhang3Zhi Dou4School of Computer Science and Engineering South China University of Technology Guangzhou ChinaSchool of Computer Science and Engineering South China University of Technology Guangzhou ChinaSchool of Computer Science and Engineering South China University of Technology Guangzhou ChinaUniversity of Victoria Melbourne AustraliaCollege of Computer and Information Engineering Henan Normal University Xinxiang ChinaAbstract Traffic Signal Control (TSC) is a fundamental task in modern intelligent transport systems. TSC is often formulated as a bi‐level optimization problem, comprised by the signal timing at the upper level and the Dynamic User Equilibrium (DUE) traffic assignment at the lower level. Since DUE is non‐convex, existing methods either formulate approximation models or adopt traffic simulators. However, approximation models may oversimplify the practical situations, while traffic simulators are usually time‐consuming. This paper formulates a vehicle‐based DUE (vDUE) model and proposes an agile method that can simultaneously maintain the computational simplicity and the traffic dynamics for the traffic assignment. Further, an agile TSC system is built by combining the vDUE at the lower level for the traffic assignment with an adaptive differential evolution algorithm at the upper level for the signal timing optimization. To enhance the effectiveness of optimization, the TSC problem formulation is also improved to make it better characterize the practical requirements. In the experiments undertaken, comparisons of different TSC methods are carried out on both real‐world and synthetic transportation networks. The experimental results validate the effectiveness of the proposed agile TSC system in various traffic situations.https://doi.org/10.1049/itr2.12049
collection DOAJ
language English
format Article
sources DOAJ
author Wei‐Li Liu
Yue‐Jiao Gong
Wei‐Neng Chen
Jun Zhang
Zhi Dou
spellingShingle Wei‐Li Liu
Yue‐Jiao Gong
Wei‐Neng Chen
Jun Zhang
Zhi Dou
An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control
IET Intelligent Transport Systems
author_facet Wei‐Li Liu
Yue‐Jiao Gong
Wei‐Neng Chen
Jun Zhang
Zhi Dou
author_sort Wei‐Li Liu
title An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control
title_short An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control
title_full An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control
title_fullStr An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control
title_full_unstemmed An agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control
title_sort agile vehicle‐based dynamic user equilibrium scheme for urban traffic signal control
publisher Wiley
series IET Intelligent Transport Systems
issn 1751-956X
1751-9578
publishDate 2021-05-01
description Abstract Traffic Signal Control (TSC) is a fundamental task in modern intelligent transport systems. TSC is often formulated as a bi‐level optimization problem, comprised by the signal timing at the upper level and the Dynamic User Equilibrium (DUE) traffic assignment at the lower level. Since DUE is non‐convex, existing methods either formulate approximation models or adopt traffic simulators. However, approximation models may oversimplify the practical situations, while traffic simulators are usually time‐consuming. This paper formulates a vehicle‐based DUE (vDUE) model and proposes an agile method that can simultaneously maintain the computational simplicity and the traffic dynamics for the traffic assignment. Further, an agile TSC system is built by combining the vDUE at the lower level for the traffic assignment with an adaptive differential evolution algorithm at the upper level for the signal timing optimization. To enhance the effectiveness of optimization, the TSC problem formulation is also improved to make it better characterize the practical requirements. In the experiments undertaken, comparisons of different TSC methods are carried out on both real‐world and synthetic transportation networks. The experimental results validate the effectiveness of the proposed agile TSC system in various traffic situations.
url https://doi.org/10.1049/itr2.12049
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