{"title":"智能交通分析:从监测到控制","authors":"Sheng Wang, Yunzhuang Shen, Z. Bao, X. Qin","doi":"10.1145/3289600.3290615","DOIUrl":null,"url":null,"abstract":"In this paper, we would like to demonstrate an intelligent traffic analytics system called T4, which enables intelligent analytics over real-time and historical trajectories from vehicles. At the front end, we visualize the current traffic flow and result trajectories of different types of queries, as well as the histograms of traffic flow and traffic lights. At the back end, T4 is able to support multiple types of common queries over trajectories, with compact storage, efficient index and fast pruning algorithms. The output of those queries can be used for further monitoring and analytics purposes. Moreover, we train the deep models for traffic flow prediction and traffic light control to reduce traffic congestion. A preliminary version of T4 is available at https://sites.google.com/site/shengwangcs/torch.","PeriodicalId":143253,"journal":{"name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Intelligent Traffic Analytics: From Monitoring to Controlling\",\"authors\":\"Sheng Wang, Yunzhuang Shen, Z. Bao, X. Qin\",\"doi\":\"10.1145/3289600.3290615\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we would like to demonstrate an intelligent traffic analytics system called T4, which enables intelligent analytics over real-time and historical trajectories from vehicles. At the front end, we visualize the current traffic flow and result trajectories of different types of queries, as well as the histograms of traffic flow and traffic lights. At the back end, T4 is able to support multiple types of common queries over trajectories, with compact storage, efficient index and fast pruning algorithms. The output of those queries can be used for further monitoring and analytics purposes. Moreover, we train the deep models for traffic flow prediction and traffic light control to reduce traffic congestion. A preliminary version of T4 is available at https://sites.google.com/site/shengwangcs/torch.\",\"PeriodicalId\":143253,\"journal\":{\"name\":\"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining\",\"volume\":\"106 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3289600.3290615\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3289600.3290615","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent Traffic Analytics: From Monitoring to Controlling
In this paper, we would like to demonstrate an intelligent traffic analytics system called T4, which enables intelligent analytics over real-time and historical trajectories from vehicles. At the front end, we visualize the current traffic flow and result trajectories of different types of queries, as well as the histograms of traffic flow and traffic lights. At the back end, T4 is able to support multiple types of common queries over trajectories, with compact storage, efficient index and fast pruning algorithms. The output of those queries can be used for further monitoring and analytics purposes. Moreover, we train the deep models for traffic flow prediction and traffic light control to reduce traffic congestion. A preliminary version of T4 is available at https://sites.google.com/site/shengwangcs/torch.