Zhiyuan Sun, Zhicheng Wang, Xin Qi, Duo Wang, Yue Li, Huapu Lu
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A double-layer nested genetic algorithm (DN-GA) is designed to solve this model. In the second stage, applying real-time period data and multi-day same-period historical data, a robust optimal dynamic traffic signal control model based on MSD model (MSD-RDT model) is put forward to obtain the dynamic TSC scheme. Three modes which reflect the different weights of historical period and real-time period in this MSD-RDT model are presented to improve the model stability, and a multi-mode genetic algorithm (MM-GA) is designed. Finally, a case study is presented to demonstrate the efficiency and applicability of the proposed models and algorithms.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 4","pages":"723-742"},"PeriodicalIF":2.3000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12465","citationCount":"0","resultStr":"{\"title\":\"A two-stage robust optimal traffic signal control with reversible lane for isolated intersections\",\"authors\":\"Zhiyuan Sun, Zhicheng Wang, Xin Qi, Duo Wang, Yue Li, Huapu Lu\",\"doi\":\"10.1049/itr2.12465\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The integrated design of traffic signal control (TSC) and reversible lane (RL) is an effective way to solve the problem of tidal congestion with uncertainty at isolated intersections, because of its advantage in making full use of temporal-spatial transportation facilities. Considering the contradiction between the dynamic TSC scheme and the fixed RL scheme in one period, a two-stage optimization method based on improved mean-standard deviation (MSD) model for isolated intersections with historical and real-time uncertain traffic flow is proposed. In the first stage, applying the same-period historical data of multiple days, a robust optimal traffic signal control model with reversible lane based on MSD model (MSD-RTR model) is put forward to obtain the fixed RL scheme and the compatible initial TSC scheme. A double-layer nested genetic algorithm (DN-GA) is designed to solve this model. In the second stage, applying real-time period data and multi-day same-period historical data, a robust optimal dynamic traffic signal control model based on MSD model (MSD-RDT model) is put forward to obtain the dynamic TSC scheme. Three modes which reflect the different weights of historical period and real-time period in this MSD-RDT model are presented to improve the model stability, and a multi-mode genetic algorithm (MM-GA) is designed. 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A two-stage robust optimal traffic signal control with reversible lane for isolated intersections
The integrated design of traffic signal control (TSC) and reversible lane (RL) is an effective way to solve the problem of tidal congestion with uncertainty at isolated intersections, because of its advantage in making full use of temporal-spatial transportation facilities. Considering the contradiction between the dynamic TSC scheme and the fixed RL scheme in one period, a two-stage optimization method based on improved mean-standard deviation (MSD) model for isolated intersections with historical and real-time uncertain traffic flow is proposed. In the first stage, applying the same-period historical data of multiple days, a robust optimal traffic signal control model with reversible lane based on MSD model (MSD-RTR model) is put forward to obtain the fixed RL scheme and the compatible initial TSC scheme. A double-layer nested genetic algorithm (DN-GA) is designed to solve this model. In the second stage, applying real-time period data and multi-day same-period historical data, a robust optimal dynamic traffic signal control model based on MSD model (MSD-RDT model) is put forward to obtain the dynamic TSC scheme. Three modes which reflect the different weights of historical period and real-time period in this MSD-RDT model are presented to improve the model stability, and a multi-mode genetic algorithm (MM-GA) is designed. Finally, a case study is presented to demonstrate the efficiency and applicability of the proposed models and algorithms.
期刊介绍:
IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following:
Sustainable traffic solutions
Deployments with enabling technologies
Pervasive monitoring
Applications; demonstrations and evaluation
Economic and behavioural analyses of ITS services and scenario
Data Integration and analytics
Information collection and processing; image processing applications in ITS
ITS aspects of electric vehicles
Autonomous vehicles; connected vehicle systems;
In-vehicle ITS, safety and vulnerable road user aspects
Mobility as a service systems
Traffic management and control
Public transport systems technologies
Fleet and public transport logistics
Emergency and incident management
Demand management and electronic payment systems
Traffic related air pollution management
Policy and institutional issues
Interoperability, standards and architectures
Funding scenarios
Enforcement
Human machine interaction
Education, training and outreach
Current Special Issue Call for papers:
Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf
Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf
Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf