论文标题
一个离散的集体游行模型
A Discrete Model of Collective Marching on Rings
论文作者
论文摘要
我们研究自动移动代理在环环境上的集体运动。代理的动力学灵感来自已知的实验室实验,这些实验对蝗虫群的动力学进行了启发。在这些实验中,观察到位于任意位置的蝗虫和环形竞技场上的初始方向最终都朝着相同的方向前进。在这项工作中,我们询问是否以及类似现象的速度发生在随机群中,其目标是尽可能长时间地保持相同的运动方向。这些代理是在宽环形区域上随机启动的,无论是顺时针还是逆时针,我们将其模拟为$ k $“窄”同心轨道。碰撞导致代理改变其运动方向。为了避免这种情况,代理商可能会决定切换轨道,以便与朝向他们的方向行进的特工合并。 我们证明,这样的代理必须最终融合到有关其运动方向的本地共识,这意味着每个狭窄轨道上的所有试剂最终都必须朝着相同的方向前进。我们给出了这种收敛或“稳定”发生所需的预期时间,这取决于代理的数量,轨道的长度和轨道数量。我们表明,当代理也具有“不稳定”,随机轨道跳跃行为的概率时,最终将达到所有轨道运动方向的全球共识。最后,我们在数值模拟中验证了我们的理论发现。
We study the collective motion of autonomous mobile agents on a ringlike environment. The agents' dynamics is inspired by known laboratory experiments on the dynamics of locust swarms. In these experiments, locusts placed at arbitrary locations and initial orientations on a ring-shaped arena are observed to eventually all march in the same direction. In this work we ask whether, and how fast, a similar phenomenon occurs in a stochastic swarm of simple agents whose goal is to maintain the same direction of motion for as long as possible. The agents are randomly initiated as marching either clockwise or counterclockwise on a wide ring-shaped region, which we model as $k$ "narrow" concentric tracks on a cylinder. Collisions cause agents to change their direction of motion. To avoid this, agents may decide to switch tracks so as to merge with platoons of agents marching in their direction. We prove that such agents must eventually converge to a local consensus about their direction of motion, meaning that all agents on each narrow track must eventually march in the same direction. We give asymptotic bounds for the expected amount of time it takes for such convergence or "stabilization" to occur, which depends on the number of agents, the length of the tracks, and the number of tracks. We show that when agents also have a small probability of "erratic", random track-jumping behaviour, a global consensus on the direction of motion across all tracks will eventually be reached. Finally, we verify our theoretical findings in numerical simulations.