Individual actions and collective movement on ant trails

Navigating through crowds is a major challenge for collective movement across various domains, from large animal migrations to intracellular transport systems. Experiments have shown that Argentine ants possess an unusual capability to evade common traffic jamming patterns at high densities, sustaining a stable two-way flow between their nest and a food source (Poissonnier et al., eLife 8:e48945, 2019). These ants do not exhibit large-scale spatiotemporal arrangements such as lane formation or oscillatory flow, suggesting the presence of a different dynamic process allowing them to maneuver efficiently without jamming.

In this work, we combine individual-based analysis of extant experimental data with agent-based modeling to explore individual ant movements and characteristics that contribute to the colony's collective behavior. By assessing spatiotemporal metrics such as density, interaction rate, and velocity, we examine how interaction types and their rates affect the colony's overall traffic dynamics. Our results lead us to suggest feedback mechanisms in which individual ants adjust their actions based on local environmental conditions over time. These mechanisms likely underpin the efficient bidirectional movement observed in crowded ant traffic.