Development of high accuracy congestion prediction algorithm using series of camera detectors

K. Hi-ri-o-tappa, S. Thajchayapong, W. Pattara-Atikom, S. Narupiti
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引用次数: 3

Abstract

This paper proposes a high accuracy algorithm to predict short-term traffic congestion in highway using patterns of microscopic traffic variable, including speed and its standard deviation from series of camera detectors installed at the location before observing point. The performance of the proposed algorithm is compared with a single camera detector. The result from simulation data shows the prediction accuracy of the proposed algorithm that utilizing data from series of detectors is twice that of single detector with zero false alarm rate. The proposed algorithm also performs well when applied to real-world data that show an increase of prediction accuracy by approximately fifty percent while achieve very low false alarm rate.
基于系列摄像机检测器的高精度拥塞预测算法的开发
本文提出了一种高精度的高速公路短期交通拥堵预测算法,该算法利用安装在观测点前位置的一系列摄像机探测器的速度及其标准差等微观交通变量模式来预测高速公路短期交通拥堵。将该算法与单摄像机检测器的性能进行了比较。仿真结果表明,该算法利用多组检测器的数据进行预测,其预测精度是单检测器的两倍,且虚警率为零。当应用于实际数据时,该算法也表现良好,预测精度提高了约50%,同时实现了非常低的误报率。
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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