Modelling of self-driven particles: Foraging ants and pedestrians

Abstract

Models for the behavior of ants and pedestrians are studied in an unified way in this paper. Each ant follows pheromone put by preceding ants, hence creating a trail on the ground, while pedestrians also try to follow others in a crowd for efficient and safe walking. These following behaviors are incorporated in our stochastic models by using only local update rules for computational efficiency. It is demonstrated that the ant trail model shows an unusual non-monotonic dependence of the average speed of the ants on their density, which can be well analyzed by the zero-range process. We also show that this anomalous behavior is clearly observed in an experiment of multiple robots. Next, the relation between the ant trail model and the floor field model for studying evacuation dynamics of pedestrians is discussed. The latter is regarded as a two-dimensional generalization of the ant trail model, where the pheromone is replaced by footprints. It is shown from simulations that small perturbations to pedestrians will sometimes avoid congestion and hence allow safe evacuation.

Ant traffic rules

“…In recent years research on ant traffic organization has provided new insights for the study of traffic in pedestrians (Nishinari et al, 2006) and vehicles (Peters et al, 2006). Of course, ants do not move like pedestrians or vehicles and there are some important differences to consider when comparing their traffic organization.…”

Forecasting pedestrian evacuation times by using swarm intelligence

“…have been successfully used to study the problem. A few of these, among others, are the Lattice Gas Model [6,7], Social Force Model [8], Cellular automata [9,10], Discrete Choice Model [3] and Ant Trail Model [11].…”

Modeling crowd evacuation of a building based on seven methodological approaches

“…Thirdly, herding behavior has been studied. Nishinari et al [17] proposed a stochastic cellular automata model to investigate pedestrians following each other during an evacuation. Georgoudas et al [18] used a computational intelligent technique-based cellular automata to simulate pedestrian dynamics during the evacuation of large areas and reproduce some phenomena of crowd dynamics such as clogging and mass behavior; Kirchner and Schadschneider [19] proposed a bionicsinspired cellular automata model to describe the interaction among the pedestrians, and simulate the evacuation from a large room with one or two doors; it is found that for achieving optimal evacuation times a proper combination of herding behavior and use of knowledge about the surrounding is necessary.…”