Model on empirically calibrating stochastic traffic flow fundamental diagram

نویسندگان

چکیده

This paper addresses two shortcomings of the data-driven stochastic fundamental diagram for freeway traffic. The first shortcoming is related to least-squares methods which have been widely used in establishing traffic flow diagrams. We argue that these are not suitable generate percentile-based diagrams, because results generated by represent weighted sample mean, rather than percentile. second widespread use independent modeling methodology a family Existing inadequate coordinate diagrams same family, and consequently, alignment with basic rules probability theory statistics. To address issues, this proposes holistic framework based on concept mean absolute error minimization. established model convex, but non-differentiable. efficiently implement proposed methodology, we further reformulate as linear programming problem could be solved state-of-the-art solvers. Experimental using real-world data validate method.

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The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation, University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or the use thereof.

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ژورنال

عنوان ژورنال: Communications in transportation research

سال: 2021

ISSN: ['2772-4247']

DOI: https://doi.org/10.1016/j.commtr.2021.100015