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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Online Access: | https://doi.org/10.1049/itr2.12049 |
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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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