Research on the Safety Evacuation near the Building Exit

Abstract:

The paper presents an improved cellular automaton model according to the feature of evacuation near the outlet. We studied friction and turning factors that affect pedestrian evacuation speed. By using mathematical methods to derive expressions of friction function and turning function. The average pedestrian outflow of the simulation that includes the effect of both the frictional function and the turning function agrees well with experiment result. On the contrary, the simulation results that only include the effect of the frictional function are not corresponding to the experiment results well. Simulation results show that friction and turning can not be ignored. By analyzing the simulation results, it verified that the model can accurately reflect the actual evacuation process and has practical value.

• Periodical: Applied Mechanics and Materials (Volume 686)
• Pages: 587-593
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.686.587
• Online since: October 2014
• Authors: Shi Da Zhao, Nan Zhang, Ying Zhao
• Keywords: Cellular Automaton, Evacuation Simulation, Friction Function, Pedestrian Evacuation, Turning Function

References

[1] Zhao Shida, et al. Development of emergency shelters query software based on Android [J]. Application of Electronic Technique, 2014, 40(3): 133-136.

[2] Zhu Gang, Ma Liang. Location model of logistics system [J]. Journal of University of Shanghai for Science and Technology, 2006 (1): 19-22.

[3] Yang Zhaosheng, Gao Xueying, Sun Di. Cellular automata model of city traffic emergency evacuation and rescue [J]. Journal of traffic and Transportation Engineering, 2011, 2(4): 114-120.

[4] Yue Hao. Study on the simulation model of pedestrian flow based on Cellular Automata [D]. Beijing, Beijing Jiaotong University. 2008 : 14-25.

[5] Heather Betel, Paola Flocchini. On the asymptoti behavior of fuzzy cellular Automata[J]. Electronic Notes in Theoretical Computer Science, 2009, 252: 23-40.

DOI: 10.1016/j.entcs.2009.09.012

[6] Gong Q L, MENDEL J M. Interval type-2 fuzzy logic systems: theory and design[J]. IEEE Transactions on Fuzzy Systems, 2000, 8(5): 535-550.

DOI: 10.1109/91.873577

[7] Zhu Yi, Yang Lizhong, Li Jian. Cellular Automata simulation of occupant evacuation in different rooms [J]. Fire Safety Science, 2007, 16(3): 175-179.

[8] ZHANG Junna, FAN Haiju. Crowd evacuation system simulation based on artificial potential field and Agent[J]. Journal of Computer Applications, 2012, 32(6): 1753-1756.

DOI: 10.3724/sp.j.1087.2012.01753

[9] B. Steffen, A. Seyfried Methods for measuring pedestrian density, flow, speed and direction with minimal scatter[J]. Physica A: Statistical Mechanics and its Applications, 2009, 12: 015.

DOI: 10.1016/j.physa.2009.12.015

[10] Daichi Yanagisawa, et al. Mean-field theory for pedestrian outflow through an exit[J].  Physical Review E - PHYS REV E , vol. 76, no. 6, (2007).

DOI: 10.1103/physreve.76.061117

[11] Ansgar Kirchner, et al. Friction effects and clogging in a cellular automaton model for pedestrian dynamics[J]. Physical Review E - PHYS REV E , Vol. 67, p.056122, (2003).

DOI: 10.1103/physreve.67.056122

[12] Daichi Yanagisawa, et al. Analysis on Pedestrian Outflow through an Exit with an Obstacle[C]. ICROS-SICE International Joint Conference 2009, 8: 5040-5045.

[13] Yushi Suma, et al. Anticipation effect in pedestrian dynamics: Modeling and experiments[J].  Physica A: Statistical Mechanics and its Applications 2012, 391(1): 248-263.

DOI: 10.1016/j.physa.2011.07.022