New methods of density estimation for vehicle traffic

Fevzi Yasin Kababulut, D. Kuntalp, Timur Duzenli
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Abstract

This study is prepared to produce solutions for estimating vehicle traffic density which is one of the biggest problems of urban life today. Four different algorithms are proposed for density estimation problem with different perspectives. All these proposed algorithms have been tried to estimate next state of the road by looking at history of density data. Algorithms are inspired by the methods used to estimate spectrum holes in cognitive radio channels. A similar approach is used for estimation of traffic density. In this study, Istanbul Metropolitan Municipality Traffic Control Center data received from the busiest roads of Istanbul in 2013, have been used as traffic data. Different simulations have been performed using these algorithms and results are evaluated based on several performance criteria.
交通密度估计的新方法
本研究旨在为估计当今城市生活中最大的问题之一的车辆交通密度提供解决方案。针对不同角度的密度估计问题,提出了四种不同的算法。所有这些提出的算法都试图通过查看历史密度数据来估计道路的下一个状态。算法的灵感来自于用于估计认知无线电信道中的频谱空洞的方法。类似的方法用于估计交通密度。在本研究中,伊斯坦布尔大都会市交通控制中心在2013年收到的伊斯坦布尔最繁忙道路的数据被用作交通数据。使用这些算法进行了不同的仿真,并根据几个性能标准对结果进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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