计算机科学
流量(计算机网络)
蚁群
集体行为
蚂蚁
生态学
功能(生物学)
模拟
蚁群优化算法
人工智能
生物
计算机网络
人类学
进化生物学
社会学
作者
Laure Anne Poissonnier,Sébastien Motsch,Jacques Gautrais,Jérôme Buhl,Audrey Dussutour
出处
期刊:eLife
[eLife Sciences Publications, Ltd.]
日期:2019-10-22
卷期号:8
被引量:9
摘要
Efficient transportation is crucial for urban mobility, cell function and the survival of animal groups. From humans driving on the highway, to ants running on a trail, the main challenge faced by all collective systems is how to prevent traffic jams in crowded environments. Here, we show that ants, despite their behavioral simplicity, have managed the tour de force of avoiding the formation of traffic jams at high density. At the macroscopic level, we demonstrated that ant traffic is best described by a two-phase flow function. At low densities there is a clear linear relationship between ant density and the flow, while at large density, the flow remains constant and no congestion occurs. From a microscopic perspective, the individual tracking of ants under varying densities revealed that ants adjust their speed and avoid time consuming interactions at large densities. Our results point to strategies by which ant colonies solve the main challenge of transportation by self-regulating their behavior.
科研通智能强力驱动
Strongly Powered by AbleSci AI