Potential field cellular automata model for pedestrian flow

Abstract

This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.

A Potential Based Many-Particle Model for Pedestrian Flow

“…9, which suggests that pedestrians prefer following a person ahead in the same group to mingling with the other group, so as to minimize their cost. Similar phenomena were reproduced by using the continuum model in [6] and the Cellular Automate model in [7].…”

“…We note that similar path-choice strategy has been used in the continuum and Cellular Automata models for pedestrian dynamics (e.g. [4,5,6,7]). See [6] for detailed discussion.…”

Cellular automata (CA) simulation of the interaction of vehicle flows and pedestrian crossings on urban low-grade uncontrolled roads

“…In CA simulations, very simple models are capable of capturing the essential features of systems of extraordinary complexity [16]. CA microsimulations can be easily implemented using computers and have been successfully applied to the modeling of vehicular flows [17][18][19] and pedestrian flows [20][21][22]. In the CA model, the interactions among the particles are based on understandable behavioral rules rather than functions [11].…”

The Superposition Principle: A Conceptual Perspective on Pedestrian Stream Simulations

“…Many of these modifications try to mitigate the effects introduced by the physical nature, such as oscillations or inertia [12]. More or less independently of force-based models, several approaches based on cellular automata have been proposed [7][8][9][10][20][21][22]. The first one published known to the authors is the model by Gipps and Marksjö [7].…”