Search

Abstract Understanding the navigation through semi-dense crowds at intersections poses a significant challenge in pedestrian dynamics, with implications for facility design and insights into emergent collective behavior. To tackle this problem, a system of cognitive active agents at a crowded three-way intersection is studied using Langevin simulations of intelligent active Brownian particles (iABPs) with directed visual perception (resulting in non-reciprocal interactions) and self-steering avoidance—without volume exclusion. We find that the emergent self-organization depends on agent maneuverability, goal fixation, and vision angle, and identify several forms of collective behavior, including localized flocking, jamming and percolation, and self-organized rotational flows. Additionally, we demonstrate that the motion of individual agents can be characterized by fractional Brownian motion and Lévy walk models across different parameter regimes. Moreover, despite the rich variety of collective behavior, the fundamental flow diagram shows a universal curve for different vision angles. Our research highlights the impact of collision avoidance, goal following, and vision angle on the individual and collective dynamics of interacting pedestrians.

Abstract The collective motion of interacting self-driven particles describes many types of coordinated dynamics and self-organisation. Prominent examples are alignment or lane formation which can be observed alongside other ordered structures and nonuniform patterns. In this article, we investigate the effects of different types of heterogeneity in a two-species self-driven particle system. We show that heterogeneity can generically initiate segregation in the motion and identify two heterogeneity mechanisms. Longitudinal lanes parallel to the direction of motion emerge when the heterogeneity statically lies in the agent characteristics (quenched disorder). While transverse bands orthogonal to the motion direction arise from dynamic heterogeneity in the interactions (annealed disorder). In both cases, non-linear transitions occur as the heterogeneity increases, from disorder to ordered states with lane or band patterns. These generic features are observed for a first and a second order motion model and different characteristic parameters related to particle speed and size. Simulation results show that the collective dynamics occur in relatively short time intervals, persist stationary, and are partly robust against random perturbations.

It has been realized that the distinction between social-psychological effects and physical effects in pedestrian crowds is complex, and so the relevance of social psychology for the properties of pedestrian streams is still discussed controversially. Although physics-based models appear to capture many properties rather accurately, it was argued that simple systems of self-driven particles could not explain certain emergent phenomena. In particular, results from a recent empirical study of pedestrian flow at bottlenecks have been interpreted as indicating the relevance of social psychology even in relatively simple scenarios of crowd dynamics. The study showed a surprising dependence of the density near the bottleneck on the width of the corridor leading to it. The density increased with increasing corridor width, although a wider corridor provides more space for pedestrians. It has been argued that this observation is a consequence of social norms, which trigger the effect by a preference for queuing in such situations. However, convincing evidence for this hypothesis is still missing. Here, we reconsider this scenario from a physics perspective using computer simulations of a simple microscopic velocity-based model.