Directional motion of a self-steering active intruder in a dense crowd of cognitive active agents.

Kushwaha, VK; Iyer, P; Singh, SP; Gompper, G · 2026 · PubMed Central

DOI: 10.1038/s41598-026-52749-4

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Summary

This study investigates the directed motion of a self-steering active intruder navigating through a dense crowd of cognitive active agents. The research addresses the challenge of efficient navigation in crowded environments, a problem relevant to biological systems (e.g., leukocytes in blood) and engineered systems (e.g., emergency personnel in pedestrian crowds). The authors aim to elucidate how visual perception and avoidance steering influence the intruder’s ability to maintain goal-oriented motion amidst frequent collisions and collective rearrangements. The researchers employed overdamped Langevin dynamics simulations to model the system. Both the intruder and the agents were modeled as intelligent active Brownian particles (iABPs) possessing visual perception and directional steering capabilities to avoid collisions. The interactions are non-reciprocal, as particles react differently based on their relative positions and specific maneuvering strategies. The intruder utilizes both vision-induced avoidance torque and goal-directed torque, while agents rely solely on vision-induced avoidance. Key control parameters included maneuverability (visual and directional), vision angle, agent density, and the Péclet number. The simulations were conducted in a two-dimensional geometry with periodic boundary conditions, using a high packing fraction to ensure strong interactions. The results demonstrate that the intruder’s attempt to increase directional speed by actively steering around agents is counterproductive; such avoidance maneuvers actually reduce the intruder’s directional speed. Instead, efficient navigation requires that the intruder be perceived by the agents, allowing them to move out of the way. The study found that the intruder’s speed and transverse diffusivity depend critically on the maneuverability ratio and vision angles. Notably, the agents’ self-steering behavior to avoid collisions enhances the hyperuniformity (class III) of the agent distribution. This increased uniformity facilitates easier directional navigation for the intruder by creating a more structured environment. The findings highlight that the intruder’s success relies less on its own avoidance capabilities and more on the agents’ ability to detect and yield to the intruder. The significance of this work lies in its contribution to the understanding of active matter and navigation in complex, crowded environments. By identifying that agent perception and the resulting hyperuniformity are key to efficient intruder motion, the study provides insights applicable to designing micro-machines, targeted drug delivery systems, and crowd management strategies. The results underscore the importance of non-reciprocal interactions and cognitive responses in active systems, distinguishing them from passive or purely mechanical obstacle avoidance scenarios.

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