Modeling the Separating Pedestrian Flow in T-Shaped Passage Based on Guide Sign

Abstract

Considering the actual situation of separating pedestrian flow in T-shaped passage, the guide sign is set to guide the pedestrians and subconscious strength is introduced to show the effect of guide sign. Pedestrian subconscious strength model is established, and the subconscious strength calculation result is added to the pedestrian simulation model which is based on cellular automata. On the platform of MATLAB software, separating pedestrian flow simulation with the effect of guide sign is realized. Simulations indicate that, compared with the separating pedestrian flow without guide sign, the efficiency of pedestrians passing with guide sign is higher. Analyzing the effect of guide sign in different positions, the suitable position of guide sign is obtained.

Modelo de agentes inteligentes para simular el tránsito peatonal en ferias comerciales urbanas durante la pandemia del COVID-19

“…La línea recta es la forma básica de movimiento en un agente (Dias, et al, 2012;Jia et al, 2016;Shi et al, 2018), mientras que la dirección puede ser en uno, dos o múltiples ángulos. A mayor cantidad de direcciones de desplazamiento, mayor la complejidad de interacción entre agentes (Dias et al, 2014;Shi et al, 2018).…”

“…Para ello, el rango de visión para la percepción de un establecimiento comercial se estableció alrededor de 10 m (Kwak et al, 2015). Se asume que los peatones mantienen una expectativa diferenciada y que en las vueltas este rango puede reducirse hasta 6 m (Jia et al, 2016). El radio de consciencia considerada fue de 10 m. Se toma en cuenta que en promedio se puede reconocer una figura humana a 30 metros de distancia, aunque este valor es paramétrico.…”

Simulation of the Separating Crowd Behavior in a T-Shaped Channel Based on the Social Force Model

“…For this category, researchers have considered the influences of panic, smoke, fire evacuation and emergency signs on the movements of pedestrians with the ambition of finding ways to improve the evacuation efficiency based upon changes in the room structure and the design of guidance schemes. The final category of research involves the flow of pedestrians in a T-shaped channel [16]- [22]; this kind of research focuses on the merging and separating behaviors of crowds of pedestrians in T-shaped channels. The merging behavior represents the movements of a crowd of pedestrians joining together from multiple directions to form a single streamline based on the same moving pedestrian target; by contrast, the separating behavior constitutes the movements of a crowd of pedestrians from a single streamline into two different directions based on different moving pedestrian targets.…”

“…In the existing research on the separating crowd behaviour in a T-shaped channel, the research performed by Fu et al [21] is very representative, as it provides a valuable basis for subsequent research; in particular, they proposed a modified floor field cellular automaton (CA) model with a corresponding probability and studied the effect of the entrance density and the left-moving probability on the passing efficiency of pedestrians within a T-shaped channel through a simulation. In a follow-up study based on the research performed by Fu, Jia et al considered the use of guide signage to improve the separation efficiency of pedestrian flow in a T-shaped channel and established a modified CA model considering the impact strength of the guide signage [22]. Nevertheless, the research on the separating crowd behavior in a T-shaped channel is still in its infancy due to a lack of support from controlled laboratory experiments and the fact that the simulation models lack validation with empirical data.…”

Simulation model of self-organizing pedestrian movement considering following behavior

“…Previous studies showed that the pedestrian flow has self-organization characteristics from the macroscopic point of view (Lam et al, 2002;Seyfried et al, 2005;Fujiyama and Tyler, 2009;Iryo-Asano et al, 2015;Li et al, 2015;Jia et al, 2016;Tang et al, 2017). Typical self-organized phenomena of pedestrian flow include arch-like formation, bottleneck oscillation, lane formation, and stripe formation.…”