{"title":"Model predictive control implementation and simulation for urban traffic networks","authors":"Chao Guo, Gang Xiong, Mei Zhang","doi":"10.1109/SOLI.2014.6960746","DOIUrl":null,"url":null,"abstract":"In this paper, we consider the problem of designing traffic network signal control systems for congested urban road networks, aiming to relieve traffic congestion and improve the utilization of the existing traffic infrastructures. A Model Predictive Control (MPC) method is introduced which is based on a microscopic store-and-forward modeling (SFM) paradigm. Moreover, a preliminary simulation of urban traffic flow management is implemented with the help of MATLAB/SIMULINK and PARAMICS. The results demonstrate the efficiency and feasibility of the MPC signal control method, which can take all the operational constraints into consideration easily. And the MPC control framework can also be applied for other infrastructure systems whose characteristics are common intelligent, from a generic point of view.","PeriodicalId":191638,"journal":{"name":"Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"245 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2014.6960746","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, we consider the problem of designing traffic network signal control systems for congested urban road networks, aiming to relieve traffic congestion and improve the utilization of the existing traffic infrastructures. A Model Predictive Control (MPC) method is introduced which is based on a microscopic store-and-forward modeling (SFM) paradigm. Moreover, a preliminary simulation of urban traffic flow management is implemented with the help of MATLAB/SIMULINK and PARAMICS. The results demonstrate the efficiency and feasibility of the MPC signal control method, which can take all the operational constraints into consideration easily. And the MPC control framework can also be applied for other infrastructure systems whose characteristics are common intelligent, from a generic point of view.