Jetendra Joshi, M. Harsha, Urijit Kurulkar, A. Reddy, D. Akhil, Byreddy Nikhil Reddy, Shreyansh, V. Sahithi
{"title":"Intelligent Parking Allotment System Based on Traffic Prediction","authors":"Jetendra Joshi, M. Harsha, Urijit Kurulkar, A. Reddy, D. Akhil, Byreddy Nikhil Reddy, Shreyansh, V. Sahithi","doi":"10.1109/ICCCE.2016.75","DOIUrl":null,"url":null,"abstract":"Traffic congestion is one of the biggest concerns that almost everyone faces in their daily lives. We are not aware about the traffic conditions and scenarios of a particular area we wish to travel due to which we often spend a lot of time, waiting for the congestion to finish, leading to massive wastage of time and energy. The paper proposes a model for controlling the traffic congestion by accurate prediction of tourist traffic with the help of Radius Base Function(RBF) Neural Network which can help us maintain a traffic flow and have a quantitative analysis and relation with other factors. This paper also works on adaptive parking techniques that can be used to avoid the delay time of a vehicle and use slot allocation to park the vehicles at the available parking slots. We have checked our service in real test bed in Bus station parking Delhi.","PeriodicalId":360454,"journal":{"name":"2016 International Conference on Computer and Communication Engineering (ICCCE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Computer and Communication Engineering (ICCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCE.2016.75","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Traffic congestion is one of the biggest concerns that almost everyone faces in their daily lives. We are not aware about the traffic conditions and scenarios of a particular area we wish to travel due to which we often spend a lot of time, waiting for the congestion to finish, leading to massive wastage of time and energy. The paper proposes a model for controlling the traffic congestion by accurate prediction of tourist traffic with the help of Radius Base Function(RBF) Neural Network which can help us maintain a traffic flow and have a quantitative analysis and relation with other factors. This paper also works on adaptive parking techniques that can be used to avoid the delay time of a vehicle and use slot allocation to park the vehicles at the available parking slots. We have checked our service in real test bed in Bus station parking Delhi.