The PeMS algorithms for accurate, real-time estimates of g-factors and speeds from single-loop detectors

Zhanfeng Jia, Chao Chen, B. Coifman, P. Varaiya
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引用次数: 210

Abstract

Presents the PeMS algorithms for the accurate, adaptive, real-time estimation of the g-factor and vehicle speeds from single-loop detector data. The estimates are validated by comparison with independent, direct measurements of the g-factor and vehicle speeds from 20 double-loop detectors on I-80 over a three-month period. The algorithm is used to process data from all freeways in Caltrans District 12 (Orange County, CA) over a 20-month period beginning January 1998. Analysis of those data shows that the g-factors for different loops in the district differ by as much as 100 percent, and the g-factor for the same loop can vary up to 50 percent over a 24-hour period. Many transportation districts now post real-time speed and travel time estimates on the World Wide Web. Those estimates often are derived from single-loop detector data assuming a common g-factor for all detectors in the district. This study suggests that those estimates can be in error by 50 percent, and so they are of little value to travelers. The use of the PeMS algorithm will reduce those errors.
PeMS算法用于精确、实时地估计单回路探测器的g因子和速度
提出了基于单回路检测器数据准确、自适应、实时估计g因子和车速的PeMS算法。通过与I-80上20个双环探测器三个月来对g因子和车速的独立、直接测量进行比较,这些估计得到了验证。该算法用于处理Caltrans 12区(加利福尼亚州奥兰治县)从1998年1月开始的20个月期间的所有高速公路数据。对这些数据的分析表明,该地区不同环路的g因子差异可达100%,而同一环路的g因子在24小时内的差异可达50%。许多交通部门现在在万维网上发布实时速度和旅行时间估计。这些估计通常是根据单回路探测器数据得出的,假设该地区所有探测器的g因子都是相同的。这项研究表明,这些估计可能会有50%的误差,因此它们对旅行者来说没有什么价值。使用PeMS算法可以减少这些误差。
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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