Noise-induced Stop-and-Go Dynamics

TL;DR

This paper introduces a stochastic model with colored noise to explain pedestrian stop-and-go waves, eliminating the need for metastability or phase transitions, and aligns well with real pedestrian data.

Contribution

It presents a novel stochastic approach to model pedestrian stop-and-go dynamics without relying on metastability or phase transitions.

Findings

Stochastic noise induces realistic stop-and-go behavior.

Model matches real pedestrian trajectories.

Parameter discussion supports model plausibility.

Abstract

Stop-and-go waves are commonly observed in traffic and pedestrian flows. In traffic theory they are described by phase transitions of metastable models. The self-organization phenomenon occurs due to inertia mechanisms but requires fine tuning of the parameters. Here, a novel explanation for stop-and-go waves based on stochastic effects is presented for pedestrian dynamics. We show that the introduction of specific coloured noises in a stable microscopic model allows to describe realistic pedestrian stop-and-go behaviour without requirement of metastability and phase transition. We compare simulation results of the stochastic model to real pedestrian trajectories and discuss plausible values for the model's parameters.