{"title":"引入人工神经网络对交通信号控制的影响","authors":"Maleanu Mihai, Racanel Carmen","doi":"10.2478/rjti-2023-0002","DOIUrl":null,"url":null,"abstract":"Abstract The urban and economic developments of recent years have generated changes in the development of road traffic, determined by the continuous growth of the vehicle fleet, the increase in the mobility index of the existing vehicle fleet and the increase in the number of vehicles transiting the main cities of the country, this having as consequences the decrease in the traffic capacity of the streets. Through the application of innovative technologies, which allow the anticipation and control of road traffic, traffic jams are avoided, this leads to an increase in the quality of life. In this article, a case study was analyzed, in which an artificial neural network was implemented within a traffic model, with the help of which predictions were made on traffic light times. The results obtained are satisfactory, and are highlighted by the performance parameters exported from the traffic models.","PeriodicalId":40630,"journal":{"name":"Romanian Journal of Transport Infrastructure","volume":"25 1","pages":"0"},"PeriodicalIF":0.1000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The influence of the introduction of an artificial neural network for traffic signal control\",\"authors\":\"Maleanu Mihai, Racanel Carmen\",\"doi\":\"10.2478/rjti-2023-0002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The urban and economic developments of recent years have generated changes in the development of road traffic, determined by the continuous growth of the vehicle fleet, the increase in the mobility index of the existing vehicle fleet and the increase in the number of vehicles transiting the main cities of the country, this having as consequences the decrease in the traffic capacity of the streets. Through the application of innovative technologies, which allow the anticipation and control of road traffic, traffic jams are avoided, this leads to an increase in the quality of life. In this article, a case study was analyzed, in which an artificial neural network was implemented within a traffic model, with the help of which predictions were made on traffic light times. The results obtained are satisfactory, and are highlighted by the performance parameters exported from the traffic models.\",\"PeriodicalId\":40630,\"journal\":{\"name\":\"Romanian Journal of Transport Infrastructure\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Romanian Journal of Transport Infrastructure\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/rjti-2023-0002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Romanian Journal of Transport Infrastructure","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/rjti-2023-0002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
The influence of the introduction of an artificial neural network for traffic signal control
Abstract The urban and economic developments of recent years have generated changes in the development of road traffic, determined by the continuous growth of the vehicle fleet, the increase in the mobility index of the existing vehicle fleet and the increase in the number of vehicles transiting the main cities of the country, this having as consequences the decrease in the traffic capacity of the streets. Through the application of innovative technologies, which allow the anticipation and control of road traffic, traffic jams are avoided, this leads to an increase in the quality of life. In this article, a case study was analyzed, in which an artificial neural network was implemented within a traffic model, with the help of which predictions were made on traffic light times. The results obtained are satisfactory, and are highlighted by the performance parameters exported from the traffic models.