Generalization Second Order Macroscopic Traffic Models via Relative Velocity of the Congestion Propagation

Yaroslav Kholodov, Andrey Alekseenko, Viktor Kazorin and Alexander Kurzhanskiy
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Yaroslav Kholodov: Division of Applied Mathematics, Moscow Institute of Physics and Technology, Innopolis University, 420500 Innopolis, Russia
Andrey Alekseenko: Institute for Computer Aided Design of RAS, 123056 Moscow, Russia
Viktor Kazorin: Lab of Data Analysis and Bioinformatics, Innopolis University, 420500 Innopolis, Russia
Alexander Kurzhanskiy: California Partners for Advanced Transportation Technology, University of California, Berkeley, CA 94720, USA

Mathematics, 2021, vol. 9, issue 16, 1-14

Abstract: This paper presents a generalized second-order hydrodynamic traffic model. Its central piece is the expression for the relative velocity of the congestion (compression wave) propagation. We show that the well-known second-order models of Payne–Whitham, Aw–Rascal and Zhang are all special cases of the featured generalized model, and their properties are fully defined by how the relative velocity of the congestion is expressed. The proposed model is verified with traffic data from a segment of the Interstate 580 freeway in California, USA, collected by the California DOT’s Performance Measurement System (PeMS).

Keywords: traffic flow; macroscopic hydrodynamical models; velocity of congestion propagation; numerical simulations (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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