4.4 Article

Kinetic Derivation of Aw-Rascle-Zhang-Type Traffic Models with Driver-Assist Vehicles

Journal

JOURNAL OF STATISTICAL PHYSICS
Volume 186, Issue 1, Pages -

Publisher

SPRINGER
DOI: 10.1007/s10955-021-02862-7

Keywords

Traffic models; Boltzmann-Enskog kinetic description; Second order hydrodynamic models; Driver-assist vehicles; Optimal control

Funding

  1. Italian Ministry for Education, University and Research (MIUR) through the Dipartimenti di Eccellenza Programme (2018-2022) -Department of Mathematical Sciences G. L. Lagrange, Politecnico di Torino [CUP: E11G18000350001]
  2. Department of Mathematics F. Casorati, University of Pavia [2017KKJP4X]
  3. Compagnia di San Paolo (Torino)

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In this paper, second order hydrodynamic traffic models are derived from kinetic-controlled equations for driver-assist vehicles, taking into account two main control strategies. The presence of driver-assist vehicles leads to an aggregate homogenisation of mean flow speed, optimizing flow and traffic stabilisation.
In this paper, we derive second order hydrodynamic traffic models from kinetic-controlled equations for driver-assist vehicles. At the vehicle level we take into account two main control strategies synthesising the action of adaptive cruise controls and cooperative adaptive cruise controls. The resulting macroscopic dynamics fulfil the anisotropy condition introduced in the celebrated Aw-Rascle-Zhang model. Unlike other models based on heuristic arguments, our approach unveils the main physical aspects behind frequently used hydrodynamic traffic models and justifies the structure of the resulting macroscopic equations incorporating driver-assist vehicles. Numerical insights show that the presence of driver-assist vehicles produces an aggregate homogenisation of the mean flow speed, which may also be steered towards a suitable desired speed in such a way that optimal flows and traffic stabilisation are reached.

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