文章基本信息

标题：A Survey on Measureable Density Prediction in Traffic Networks
本地全文：下载
作者：Sujit A. Navale ; Vinodkumar J. Shinde
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：3
页码：3266
DOI：10.15680/IJIRCCE.2016.0403058
出版社：S&S Publications
摘要：As of late, advanced following strategies began to permit catching the position of huge quantities of moving objects. Given this data, it is conceivable to break down also, anticipate the movement thickness in a system which offers significant data for activity control, blockage expectation and avoidance. In this paper, we propose a novel measurable way to deal with foresee the thickness on any edge of such a system sooner or later. Our strategy depends on brief time perceptions of the movement history. In this way, knowing the destination of each voyaging individual is not required. Rather, we accept that the people will act reasonably and pick the most limited way from their beginning stages to their destinations. In light of this supposition, we present a measurable way to deal with depict the probability of any given individual in the system to be situated at a certain position at a specific time. Since deciding this probability is very costly when done in a clear way, we propose a productive technique to speed up the expectation which depends on an addition tree. In our tests, we demonstrate the ability of our methodology to make helpful fore casts about the activity thickness furthermore, delineate the effectiveness of our new calculation when ascertaining these expectations
关键词：Mobility based clustering; traffic detection; vehicle; crowdedness