Hydrodynamic traffic flow models including random accidents: A kinetic derivation
Felisia Angela Chiarello, Simone Göttlich, T. Schilliger, Andrea Tosin
Abstract
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Felisia Angela Chiarello, Simone Göttlich, T. Schilliger, Andrea Tosin
Abstract
Open-access reader
We present a formal kinetic derivation of a second order macroscopic traffic model from a stochastic particle model. The macroscopic model is given by a system of hyperbolic partial differential equations (PDEs) with a discontinuous flux function, in which the traffic density and the headway are the averaged quantities. A numerical study illustrates the performance of the second order model compared to the particle approach. We also analyse numerically uncertain traffic accidents by considering statistical measures of the solution to the PDEs.
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We present a formal kinetic derivation of a second order macroscopic traffic model from a stochastic particle model. The macroscopic model is given by a system of hyperbolic partial differential equations (PDEs) with a discontinuous flux function, in which the traffic density and the headway are the averaged quantities. A numerical study illustrates the performance of the second order model compared to the particle approach. We also analyse numerically uncertain traffic accidents by considering statistical measures of the solution to the PDEs.
Key concepts: Microscopic traffic flow model, Traffic flow (computer networking), Headway, Partial differential equation, Applied mathematics, Statistical physics, Traffic model, Flow (mathematics)