Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 26 min ago
PreprintCC0arXiv

Micro-to-macro derivation and stability analysis of an Aw-Rascle-Zhang-type model with driver-dependent acceleration

Abstract

We introduce a new traffic flow model. The main idea is to describe acceleration effects in the Aw-Rascle-Zhang model through an additional driver-dependent equation, thereby allowing individual driver characteristics to evolve dynamically rather than being prescribed solely by the traffic density. The resulting system provides a hyperbolic description of traffic dynamics and admits an explicit analysis of its characteristic structure, Riemann problem, and entropy properties. To investigate the stability of the proposed model, we perform a Chapman-Enskog expansion up to second order and derive the corresponding diffusive and higher-order corrections. This analysis reveals how the stability properties depend on the underlying velocity and pressure functions. Several examples are presented to illustrate the theoretical results.

Related

  1. On micro-macro derivation of traffic flow models with (A,B)-connection and its stability
    F. Ancona, P. Cardaliaguet, A. Cesaroni
    arXivPreprintarXiv licenceFull textAnalysis & PDEsarXiv
  2. The Multiple Timescales of Gradient Descent on the Edge of Stability: A Perturbative Derivation of the Central Flow
    Raphaël Berthier
    HALPreprintCC BY 4.0Full textOptimisation & controlStatisticsHALarXiv
  3. Analysis of RCLUPPr: stability, robustness and acceleration
    Haoran Guan, Zhenyu Zou, Yufeng Wei +3
    arXivPreprintarXiv licenceFull textNumerical analysis & scientific computingarXiv
  4. A Solvable Model of Adaptive Learning Rate Rescaling: Acceleration, Stability & Scaling
    Itay Lavie, Clarissa Lauditi, Cengiz Pehlevan
    arXivPreprintCC BY 4.0Full textStatisticsCondensed matterarXiv
  5. Stability results for distribution-dependent stochastic Volterra equations
    Martin Bergerhausen, David J. Prömel
    arXivPreprintarXiv licenceFull textProbabilityarXiv
BibTeX
@misc{gerster2026microtomacro,
  title = {{Micro-to-macro derivation and stability analysis of an Aw-Rascle-Zhang-type model with driver-dependent acceleration}},
  author = {Stephan Gerster and Giuseppe Visconti},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.15934},
  eprint = {2609.15934},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.15934},
  note = {CC0},
}
RIS
TY  - UNPB
TI  - Micro-to-macro derivation and stability analysis of an Aw-Rascle-Zhang-type model with driver-dependent acceleration
AU  - Stephan Gerster
AU  - Giuseppe Visconti
PY  - 2026
DA  - 2026/09/14
PB  - arXiv
DO  - 10.48550/arxiv.2609.15934
UR  - https://arxiv.org/abs/2609.15934
AB  - We introduce a new traffic flow model. The main idea is to describe acceleration effects in the Aw-Rascle-Zhang model through an additional driver-dependent equation, thereby allowing individual driver characteristics to evolve dynamically rather than being prescribed solely by the traffic density. The resulting system provides a hyperbolic description of traffic dynamics and admits an explicit analysis of its characteristic structure, Riemann problem, and entropy properties. To investigate the stability of the proposed model, we perform a Chapman-Enskog expansion up to second order and derive the corresponding diffusive and higher-order corrections. This analysis reveals how the stability properties depend on the underlying velocity and pressure functions. Several examples are presented to illustrate the theoretical results.
ER  -