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Multi-Directional Continuous Traffic Model For Large-Scale Urban Networks

Liudmila Tumash 1 Carlos Canudas de Wit 1 Maria Laura Delle Monache 1
1 DANCE - Dynamics and Control of Networks
Inria Grenoble - Rhône-Alpes, GIPSA-PAD - GIPSA Pôle Automatique et Diagnostic
Abstract : In this paper we propose a new multi-direction traffic flow model called the NSWE-model. This macroscopic model is composed by a set of four partial differential equations (PDEs), each modelling the density propagation in one of the four cardinal directions: North, South, West and East. We show step-by-step the formal derivation of this continuous model from the classical cell transmission model at intersections. We use only the knowledge about the network topology (location of the roads) and network infrastructure parameters such as roads maximal speeds, number of lanes and capacities. The information about the flow direction is retrieved from the turning ratios at the intersections, which is then aggregated in four directions using projection matrices. Additionally, we discuss the mathematical properties of the NSWE-model. In particular, we show that this model is hyperbolic and corresponds to a conservation law, where the conserved quantity is the total vehicle density in the network. The model is validated using synthetic data from the microsimulator Aimsun that takes Grenoble downtown as a network input. Moreover, the model is also validated using real data collected from real sensors installed in Grenoble.
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Preprints, Working Papers, ...
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https://hal.archives-ouvertes.fr/hal-03236552
Contributor : Liudmila Tumash Connect in order to contact the contributor
Submitted on : Wednesday, May 26, 2021 - 12:06:02 PM
Last modification on : Friday, December 10, 2021 - 3:34:37 PM
Long-term archiving on: : Friday, August 27, 2021 - 7:17:17 PM

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ContinuationModel_draft_v9.pdf
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  • HAL Id : hal-03236552, version 1

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Liudmila Tumash, Carlos Canudas de Wit, Maria Laura Delle Monache. Multi-Directional Continuous Traffic Model For Large-Scale Urban Networks. 2021. ⟨hal-03236552v1⟩

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