首页|Enhancing convergence efficiency of self-propelled agents using direction preference
Enhancing convergence efficiency of self-propelled agents using direction preference
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NSTL
Elsevier
In this paper, we investigate the effect of direction preference on self-propelled agents. In the well-known Vicsek model, an agent treats its neighbors equally and updates its direction by the average direction of its neighbors. Whereas, in this study, agents prefer to synchronize with their neighbors moving in a certain direction, which is called preference direction. The center agent judges the influence value from its neighbor according to the direction angle between them. We assume that there exists a preference direction angle beta. When the direction angle between the neighbor and the center agent is closer to beta, the neighbor has greater influence on the center agent. The modified Vicsek model with preference direction angle is called direction preference model. We use the parameter alpha (0 < alpha <= 1) to adjust the effect of direction preference. The larger the value of alpha, the weaker the effect of direction preference. If alpha = 1, the direction preference will lose its effect. In the simulation experiments, different values of beta and alpha are discussed. Simulation results demonstrate that in noise-free environment the direction preference model with optimal beta = 3.7 pi /8 can accelerate the synchronization speed; in noise environment the direction preference model with beta be in [3 pi/8, 5 pi /8] has stronger robustness than the original Vicsek model and the optimal value of beta is altered. (C) 2021 Elsevier B.V. All rights reserved.
NSTL
Elsevier
