A modified Vicsek model for self-propelled agents with exponential neighbor weight and restricted visual field

Large flocks of wild beings can have coordinated motion with neither leading center nor global information. The Vicsek model and its new versions explained such collective behavior of self-propelled agents with the mechanism of un-weighted influence of neighbors and global visual field (GVF), which may not always fit the reality. In the present work, we take both exponential (λλ) neighbor weight (ENW) and restricted visual field (RVF) into account, and investigate the combinatory effect of them. Based on this mechanism, in most cases of our simulation, stationary direction consensus VaVa exhibits a maximum or decreases with VFVF, and a minimum convergence time TminTmin appears in RVF, which demonstrates that GVF is not necessary for coordinated motion, while RVF matched ENW would be reasonable. Moreover, we simulated various recipes for optimizing VaVa and TT in unfavorable cases, and found critical points separating inverse λλ-dependent variations of TT. The present work may be useful in improving the efficiency of direction consensus of large flocks of artificial individuals besides the understanding of biological collective motion in nature.

► Exponential neighbor weight (ENW) and restricted visual field (RVF) are considered simultaneously for the first time to study the coordinated motion.
► Global visual field rarely is any good for achieving the direction consensus VaVa and shorting the convergence time TT with the weighted mechanism.
► Various recipes for optimizing VaVa and TT in unfavorable cases are simulated.