Intelligent Exit-Selection Behaviors during a Room Evacuation

A modified version of the existing cellular automata (CA) model is proposed to simulate an evacuation procedure in a classroom with and without obstacles. Based on the numerous literature on the implementation of CA in modeling evacuation motions, it is notable that most of the published studies do not take into account the pedestrian's ability to select the exit route in their models. To resolve these issues, we develop a CA model incorporating a probabilistic neural network for determining the decision-making ability of the pedestrians, and simulate an exit-selection phenomenon in the simulation. Intelligent exit-selection behavior is observed in our model. From the simulation results, it is observed that occupants tend to select the exit closest to them when the density is low, but if the density is high they will go to an alternative exit so as to avoid a long wait. This reflects the fact that occupants may not fully utilize multiple exits during evacuation. The improvement in our proposed model is valuable for further study and for upgrading the safety aspects of building designs.

[1]  Donald F. Specht,et al.  Probabilistic neural networks and the polynomial Adaline as complementary techniques for classification , 1990, IEEE Trans. Neural Networks.

[2]  Shing Chung Josh Wong,et al.  Collection, spillback, and dissipation in pedestrian evacuation: A network-based method , 2011 .

[3]  Abdullah Zawawi Talib,et al.  A cellular automata model for circular movements of pedestrians during Tawaf , 2011, Simul. Model. Pract. Theory.

[4]  J. M. Jurado,et al.  Characterisation of tea leaves according to their total mineral content by means of probabilistic neural networks , 2010 .

[5]  F F Nobre,et al.  Comparison among probabilistic neural network, support vector machine and logistic regression for evaluating the effect of subthalamic stimulation in Parkinson disease on ground reaction force during gait. , 2010, Journal of biomechanics.

[6]  Hai-Jun Huang,et al.  Route choice in pedestrian evacuation: formulated using a potential field , 2011 .

[7]  José Rogan,et al.  Cellular automaton model for evacuation process with obstacles , 2007 .

[8]  Bing-Hong Wang,et al.  Simulation of evacuation processes using a multi-grid model for pedestrian dynamics , 2006 .

[9]  Hao Wu,et al.  Experiment and modeling of exit-selecting behaviors during a building evacuation , 2010 .

[10]  Chung-I Chou,et al.  Simulation of pedestrian flow through a "T" intersection: A multi-floor field cellular automata approach , 2011, Comput. Phys. Commun..

[11]  Guo Ren-Yong,et al.  Logit-based exit choice model of evacuation in rooms with internal obstacles and multiple exits , 2010 .

[12]  R. Alizadeh,et al.  A dynamic cellular automaton model for evacuation process with obstacles , 2011 .

[13]  Shin Morishita,et al.  A Learning Algorithm for the Simulation of Pedestrian Flow by Cellular Automata , 2010, ACRI.

[14]  Hai-Jun Huang,et al.  Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exits. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.