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Noise-induced stop-and-go traffic dynamics: Modelling and control

Published 2 days agoVersion 1arXiv:2512.04073

Authors

Raphael Korbmacher, Parthib Khound, Antoine Tordeux, Frank Gronwald

Categories

physics.soc-ph

Abstract

This contribution investigates an original stochastic approach for the emergence of stop-and-go waves in traffic flow, a collective phenomenon with significant safety and environmental implications. Using a stable nonlinear car-following model, the study shows that minimal white Gaussian noise can destabilise the flow, leading to a phase transition from laminar to periodic dynamics through a nonlinear instability phenomenon, analogous to Kapitza's pendulum. Furthermore, a simple linear transformation of the model, which amplifies the response and introduces a positive acceleration bias, counteracts noise-induced effects and recovers the stability of uniform solutions. The findings are supported by simulations, offering new insights into the modelling and mitigation of oscillatory traffic dynamics.

Noise-induced stop-and-go traffic dynamics: Modelling and control

2 days ago
v1
4 authors

Categories

physics.soc-ph

Abstract

This contribution investigates an original stochastic approach for the emergence of stop-and-go waves in traffic flow, a collective phenomenon with significant safety and environmental implications. Using a stable nonlinear car-following model, the study shows that minimal white Gaussian noise can destabilise the flow, leading to a phase transition from laminar to periodic dynamics through a nonlinear instability phenomenon, analogous to Kapitza's pendulum. Furthermore, a simple linear transformation of the model, which amplifies the response and introduces a positive acceleration bias, counteracts noise-induced effects and recovers the stability of uniform solutions. The findings are supported by simulations, offering new insights into the modelling and mitigation of oscillatory traffic dynamics.

Authors

Raphael Korbmacher, Parthib Khound, Antoine Tordeux et al. (+1 more)

arXiv ID: 2512.04073
Published Dec 3, 2025

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