交通基本图在评估检测器性能中的应用

Katherine Riffle;Edward J. Smaglik;Steven Procaccio;Steven R. Gehrke;Brendan J. Russo;David Hurwitz
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引用次数: 0

摘要

本研究开发了基于事件输出和现有交通流理论的检测器健康评估新方法。在这项工作中,基于事件的检测器数据输出用于根据Greenshields基本模型开发经验车辆体积密度曲线。通过整合,将这些经验线与每个探测器的概念体积密度曲线进行比较,该曲线由平均车头距和公布的限速数据生成。探测器的性能和地点信息也被用来在经验观察的基础上对每个探测器的预测体积密度关系进行建模,然后以与经验线相同的方式与概念线进行比较。然后使用每次比较的结果创建一个数据库,用于在算法结构内评估检测器的健康状况。本文提出并讨论了该算法,随后给出了未来研究方向、实践应用、经验教训以及本工作的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of the Traffic Fundamental Diagram to Assess Detector Performance
This study develops new methods for evaluating detector health via event-based outputs and existing traffic flow theory. In this work, event-based detector data outputs were used to develop empirical vehicle volume-density curves per Greenshields fundamental model. Through integration, these empirical lines were compared with a conceptual volume-density curve for each detector, which was generated with average headway and posted speed limit data. The detector performance and site information were also used to model a predicted volume-density relationship for each detector on the basis of empirical observations, which was then compared with the conceptual line in the same manner as the empirical lines. The outcomes of each comparison were then used to create a database for assessing detector health within the structure of an algorithm. The algorithm is presented and discussed, followed by directions for future research, applications for practice, lessons learned, and limitations of this work.
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CiteScore
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