Simulation of pedestrian dynamics using a two dimensional cellular automaton

By Carsten Burstedde, K. Klauck, Andreas Schadschneider, J. Zittartz. 2001

1,730 citations recorded by the source corpus.

We propose a two-dimensional cellular automaton model to simulate pedestrian traffic. It is a vmax=1 model with exclusion statistics and parallel dynamics. Long-range interactions between the pedestrians are mediated by a so-called floor field which modifies the transition rates to neighbouring cells. This field, which can be discrete or continuous, is subject to diffusion and decay. Furthermore it can be modified by the motion of the pedestrians. Therefore, the model uses an idea similar to chemotaxis, but with pedestrians following a virtual rather than a chemical trace. Our main goal is to show that the introduction of such a floor field is sufficient to model collective effects and self-organization encountered in pedestrian dynamics, e.g. lane formation in counterflow through a large corridor. As an application we also present simulations of the evacuation of a large room with reduced visibility, e.g. due to failure of lights or smoke.

Subfields: Building and Construction, Control and Systems Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/8e9004f777a7aeff7d8ff96fafef46d71d572238

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Citations in the corpus

Evacuation Dynamics: Empirical Results, Modeling and Applications (2008, methodology): “The floor field CA [13, 14, 86, 167] can also be considered as an extension of the ASEP.”
From Crowd Dynamics to Crowd Safety: a Video-Based Analysis (2008, background): “Nevertheless, it has been shown that many stylized facts of pedestrian crowds can be well understood by so-called “social force models” [14] and other modeling approaches such as cellular automata [1,23].”
Floor Fields for Tracking in High Density Crowd Scenes (2008, background): “The concept of a floor field is inspired by the field of evacuation dynamics [1, 2], where floor fields are manually designed to simulate behaviors of pedestrians in panic situations.”
Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram (2011, background): “A large number o f models [1, 2, 3, 4, 5, 6] have been developed to understand the basic characteristics rel ated to bidirectional flow including lane formation [5, 7,?], jamming transition [2, 6, 9, 10] and fundamental diagram [ 11].”
Modeling crowd evacuation of a building based on seven methodological approaches (2009, background): “[65] have proposed a stochastic cellular automata model to simulate pedestrian behavior, where the key mechanism is the floor field that acts as a substitute for pedestrian intelligence.”
Basics of Modelling the Pedestrian Flow (2005, background): “ design of pedestrian facilities and the study of more theoretical questions. For a ﬁrst overview see [1, 2]. The corresponding models can be classiﬁed in two categories: the cellular automata models [3, 4, 5, 6, 7] and models in a continuous space [8, 9, 10, 11]. We focus on models continuous in sp”
Cellular automaton model for evacuation process with obstacles (2007, background): “In spite of its importance, relatively few research has been devoted to this problem [5,19,24].”
Modifications of the Helbing-Molnár-Farkas-Vicsek Social Force Model for Pedestrian Evolution (2005, background): “We emphasize that both the HMFV model and that of Burstedde et al. do not provide pedestrians with any " intelligence " or decision-making capabilities.”