A DATA-DRIVEN APPROACH FOR ESTIMATING THE FUNDAMENTAL DIAGRAM

被引:0
|
作者
Bhouri, Neila [1 ]
Aron, Maurice [1 ]
Hajsalem, Habib [1 ]
机构
[1] Univ Paris Est, IFSTTAR, COSYS Dept, GRETTIA Lab, 14-20 Blvd Newton, F-77447 Champs Sur Marne 2, France
来源
PROMET-TRAFFIC & TRANSPORTATION | 2019年 / 31卷 / 02期
关键词
non-analytical; calibration; empirical data; shortest-path algorithm; convex quadratic program; safety constraint; critical density function; TRAFFIC FLOW; MODELS; WAVES;
D O I
暂无
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
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.
引用
收藏
页码:117 / 128
页数:12
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