Cellular automaton simulation of pedestrian counter flow with different walk velocities

Abstract

This paper presents a cellular automaton model without step back for pedestrian dynamics considering the human behaviors which can make judgments in some complex situations. This model can simulate pedestrian movement with different walk velocities through update at different time-step intervals. Two kinds of boundary conditions including periodic and open boundary for pedestrian counter flow are considered, and their dynamical characteristics are discussed. Simulation results show that for periodic boundary condition there are three phases of pedestrian patterns, i.e., freely moving phase, lane formation phase, and perfectly stopped phase at some certain total density ranges. In the stage of lane formation, the phenomenon that pedestrians exceed those with lower walk velocity through a narrow walkway can be found. For open boundary condition, at some certain entrance densities, there are two steady states of pedestrian patterns; but the first is metastable. Spontaneous fluctuations can break the first steady state, i.e., freely moving phase, and run into the second steady state, i.e., perfectly stopped phase.

Cellular automaton model for evacuation process with obstacles

“…Notice that some locations are impossible (not enough space for a double door). Two traditional locations to place such a door have been labeled a (occupying cells [12][13] and b (at cells [16][17] by a 5% probability of not moving. Also, when pedestrian motions are in conflict, they are resolved by a random choice.…”

“…Collective behaviors studied include jam formation, clogging, ''faster-is-slower'' effect, oscillation at doors and lane formation, among others [5][6][7][8][9][10][11]. Various scenarios have been considered, such as escape panic [12], evacuation in conditions of poor visibility [13], egress from aircraft [14], pedestrian counterflows [7,10,15,16], motion in T-shaped channels [9] or through bottlenecks [17], or the effects of kin behavior [18] and competitive/ cooperative behavior [14]. Several models have been proposed to study these systems, including molecular dynamics [6,12], lattice gas [7,9,13,17,19,20] and cellular automata (CA) models [5,11,[14][15][16][21][22][23].…”

“…Various scenarios have been considered, such as escape panic [12], evacuation in conditions of poor visibility [13], egress from aircraft [14], pedestrian counterflows [7,10,15,16], motion in T-shaped channels [9] or through bottlenecks [17], or the effects of kin behavior [18] and competitive/ cooperative behavior [14]. Several models have been proposed to study these systems, including molecular dynamics [6,12], lattice gas [7,9,13,17,19,20] and cellular automata (CA) models [5,11,[14][15][16][21][22][23]. CA models are a particularly interesting choice, since, in spite of its computational simplicity, they are able to model individual and collective behavior of pedestrian dynamics observed experimentally and described by other, more complex models [5,11,14,22,23].…”

Generalized index for spatial data sets as a measure of complete spatial randomness

“…The spatial distribution of a set of objects arises throughout physical, biological, and social processes, for example, in fluid mixing [1][2][3][4][5], cell biology [6][7][8][9], plant ecology [10][11][12][13][14], and pedestrian and traffic flow [15,16]. They also arise naturally in agent-based models, known as cellular automata (CA) models [17][18][19][20][21].…”

Design of People Evacuation From Rooms and Buildings

“…Egress modelling is one of the important means of egress investigation (Isobe 1992;Muramatsu et al 1999;Burstedde et al 2001;Tajima and Nagatani 2001;Kirchner and Schadschneider 2002;Nagatani and Nagai 2004;Kuligowski 2005;Nagai et al 2005;Nakayama et al 2005;Qiu et al 2005;Weng et al 2006;Yang et al 2006;Pelechano and Malkawi 2008;Tavares 2008). As typical models in evacuation modeling, the social force model (Helbing and Molnar 1995) and the discrete model (Isobe 1992), including lattice gas model and cellular automata model, are able to successfully simulate some typical phenomena observed in pedestrian dynamics.…”