{"title":"高速公路视频监控盲区事件预测方法","authors":"Liyao Ma, Xiao Wang, Ding Li, M. Gao","doi":"10.1109/IAEAC.2017.8054041","DOIUrl":null,"url":null,"abstract":"Based on the actual traffic detection data of the upstream and downstream video monitor blind area, Support Vector Machines (SVM) algorithm was used to realize the short-term traffic flow forecasting, and VISSIM simulation technology was used build the traffic blind area prediction model. The video blind spot detection algorithm with practical engineering application value and the traffic incident monitoring solution under non-full-range video monitoring condition are put forward.","PeriodicalId":432109,"journal":{"name":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Event prediction method of expressway in video monitoring-blind area\",\"authors\":\"Liyao Ma, Xiao Wang, Ding Li, M. Gao\",\"doi\":\"10.1109/IAEAC.2017.8054041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the actual traffic detection data of the upstream and downstream video monitor blind area, Support Vector Machines (SVM) algorithm was used to realize the short-term traffic flow forecasting, and VISSIM simulation technology was used build the traffic blind area prediction model. The video blind spot detection algorithm with practical engineering application value and the traffic incident monitoring solution under non-full-range video monitoring condition are put forward.\",\"PeriodicalId\":432109,\"journal\":{\"name\":\"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAEAC.2017.8054041\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC.2017.8054041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Event prediction method of expressway in video monitoring-blind area
Based on the actual traffic detection data of the upstream and downstream video monitor blind area, Support Vector Machines (SVM) algorithm was used to realize the short-term traffic flow forecasting, and VISSIM simulation technology was used build the traffic blind area prediction model. The video blind spot detection algorithm with practical engineering application value and the traffic incident monitoring solution under non-full-range video monitoring condition are put forward.