{"title":"Adaptive signal control expert by artificial neural network training","authors":"Amoeba T S Chang","doi":"10.1109/VNIS.1995.518815","DOIUrl":null,"url":null,"abstract":"An advanced signal system, named INTELS (with subsystems, ITSS, IMSS, and MCC), has been proposed for several years and has been upgraded recently. Originally, it only used an expert system to generate a suitable phase during each beginning state of the timing determination; thus no cycle with a steady sequence was possible. Except for the above function, the system is being remodeled to possess the capability of planning optimal timing by using a reasonable traffic forecasting model via an artificial neural network. This paper describes the system's framework, executing process, and the abstract control structure, including the phase generation and the timing design.","PeriodicalId":337008,"journal":{"name":"Pacific Rim TransTech Conference. 1995 Vehicle Navigation and Information Systems Conference Proceedings. 6th International VNIS. A Ride into the Future","volume":"113 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pacific Rim TransTech Conference. 1995 Vehicle Navigation and Information Systems Conference Proceedings. 6th International VNIS. A Ride into the Future","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VNIS.1995.518815","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
An advanced signal system, named INTELS (with subsystems, ITSS, IMSS, and MCC), has been proposed for several years and has been upgraded recently. Originally, it only used an expert system to generate a suitable phase during each beginning state of the timing determination; thus no cycle with a steady sequence was possible. Except for the above function, the system is being remodeled to possess the capability of planning optimal timing by using a reasonable traffic forecasting model via an artificial neural network. This paper describes the system's framework, executing process, and the abstract control structure, including the phase generation and the timing design.