Accelerating consensus of self-driven swarm via adaptive speed

Abstract

In resent years, Vicsek model has attracted more and more attention and been well developed. However, the in-depth analysis on the convergence time are scarce thus far. In this paper, we study some certain factors that mainly govern the convergence time of Vicsek model. By extensively numerical simulations, we find the convergence time scales in a power law with $r^2\ln N$ in the noise-free case, where $r$ and $N$ are horizon radius and the number of particles. Furthermore, to accelerate the convergence, we propose a new model in which the speed of each particle is variable. The convergence time can be remarkably shortened compared with the standard Vicsek model.

11 pages, 6 figures

References in corpus (3)

• Novel type of phase transition in a system of self-driven particles
• Onset of collective and cohesive motion
• Phase transitions in systems of self-propelled agents and related network models

Cited by in corpus (5)

• Collective dynamics of self-propelled particles with variable speed
• Optimal View Angle in Collective Dynamics of Self-propelled Agents
• Consensus of self-driven agents with avoidance of collisions
• Body size affects the strength of social interactions and spatial organisation of a schooling fish (Pseudomugil signifer)
• Local interactions in active matter are reinforced by spatial structure