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A DATA-DRIVEN APPROACH FOR ESTIMATING THE FUNDAMENTAL DIAGRAM

机译：一种估算基本图的数据驱动方法

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摘要

The fundamental diagram links average speed to density or traffic flow. An analytic form of this diagram, with its comprehensive and predictive power, is required in a number of problems. This paper argues, however, that, in some assessment studies, such a form is an unnecessary constraint resulting in a loss of accuracy. A non-analytical fundamental diagram which best fits the empirical data and respects the relationships between traffic variables is developed in this paper. In order to obtain an unbiased fundamental diagram, separating congested and non-congested observations is necessary. When defining congestion in parallel with a safety constraint, the density separating congestion and non-congestion appears as a decreasing function of the flow and not as a single critical density value. This function is here identified and used. Two calibration techniques - a shortest path algorithm and a quadratic optimization with linear constraints - are presented, tested, compared and validated.
机译：基本图将平均速度链接到密度或交通流量。该图的分析形式，具有全面和预测的功率，在许多问题中需要。然而，本文认为，在一些评估研究中，这种形式是不必要的约束，导致准确性丧失。本文开发了一个最适合经验数据的非分析基础图，并尊重流量变量之间的关系。为了获得非偏见的基本图，需要分离拥塞和非拥塞观察。当与安全约束并行地定义拥塞时，密度分离拥塞和非拥塞看起来是流量的降低而不是单个临界密度值。此处识别并使用此功能。两个校准技术 - 呈现，测试，测试，比较和验证了两个校准技术 - 最短路径算法和具有线性约束的二次优化。

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