{"title":"基于车道的隔离交叉口延迟最小化固定时间信号模型的凸性与全局优化","authors":"Haiming Hao, Hui Jin","doi":"10.1080/23249935.2023.2259014","DOIUrl":null,"url":null,"abstract":"AbstractLane-based fixed-time signal is basic to various signal control strategies. It performs well in maximizing road capacity, but is faced with significant challenge in minimizing traffic delay. This study validates the convexity of lane-based fixed-time signal model for delay minimization, when lane markings are determined as well as flow factors. Thus Breadth first search algorithm is developed to enumerate the feasible lane markings, which are then screened with flow factors. Cutting plane algorithm is applied to the CMINLP for each feasible lane markings, where the non-linear delay function is converted to a series of linear ones, until the relaxed delay converges to the actual delay. Branch pruning strategy is established for efficiency, to eliminate the lane markings with uncompetitive delay. Numerical analyses follow to validate the proposed algorithm. This research promotes the redesign of lane-based fixed-time signal control.KEYWORDS: Lane-based fixed-time signaldelay minimisationconvexitycutting planebranch pruning Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work has been funded by the National Natural Science Foundation of China [NO. 52002261] and by the Key Laboratory of Road and Traffic Engineering of the Ministry of Education of Tongji University [NO. K202105] and China Postdoctoral Science Foundation [NO. 2020M671581].","PeriodicalId":49416,"journal":{"name":"Transportmetrica","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Convexity and global optimisation of lane-based fixed-time signal model for delay minimisation at an isolated intersection\",\"authors\":\"Haiming Hao, Hui Jin\",\"doi\":\"10.1080/23249935.2023.2259014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractLane-based fixed-time signal is basic to various signal control strategies. It performs well in maximizing road capacity, but is faced with significant challenge in minimizing traffic delay. This study validates the convexity of lane-based fixed-time signal model for delay minimization, when lane markings are determined as well as flow factors. Thus Breadth first search algorithm is developed to enumerate the feasible lane markings, which are then screened with flow factors. Cutting plane algorithm is applied to the CMINLP for each feasible lane markings, where the non-linear delay function is converted to a series of linear ones, until the relaxed delay converges to the actual delay. Branch pruning strategy is established for efficiency, to eliminate the lane markings with uncompetitive delay. Numerical analyses follow to validate the proposed algorithm. This research promotes the redesign of lane-based fixed-time signal control.KEYWORDS: Lane-based fixed-time signaldelay minimisationconvexitycutting planebranch pruning Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work has been funded by the National Natural Science Foundation of China [NO. 52002261] and by the Key Laboratory of Road and Traffic Engineering of the Ministry of Education of Tongji University [NO. K202105] and China Postdoctoral Science Foundation [NO. 2020M671581].\",\"PeriodicalId\":49416,\"journal\":{\"name\":\"Transportmetrica\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportmetrica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23249935.2023.2259014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportmetrica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23249935.2023.2259014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convexity and global optimisation of lane-based fixed-time signal model for delay minimisation at an isolated intersection
AbstractLane-based fixed-time signal is basic to various signal control strategies. It performs well in maximizing road capacity, but is faced with significant challenge in minimizing traffic delay. This study validates the convexity of lane-based fixed-time signal model for delay minimization, when lane markings are determined as well as flow factors. Thus Breadth first search algorithm is developed to enumerate the feasible lane markings, which are then screened with flow factors. Cutting plane algorithm is applied to the CMINLP for each feasible lane markings, where the non-linear delay function is converted to a series of linear ones, until the relaxed delay converges to the actual delay. Branch pruning strategy is established for efficiency, to eliminate the lane markings with uncompetitive delay. Numerical analyses follow to validate the proposed algorithm. This research promotes the redesign of lane-based fixed-time signal control.KEYWORDS: Lane-based fixed-time signaldelay minimisationconvexitycutting planebranch pruning Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work has been funded by the National Natural Science Foundation of China [NO. 52002261] and by the Key Laboratory of Road and Traffic Engineering of the Ministry of Education of Tongji University [NO. K202105] and China Postdoctoral Science Foundation [NO. 2020M671581].