Sains Malaysiana 46(10)(2017): 1997–2005


Incorporating Intelligence into Exit Choice Model for Typical Evacuation

(Penggabungan Kecerdasan kepada Model Pilihan Keluar untuk Pemindahan Tipikal)




1College of Shari’a and Islamic Studies in Al Ahsaa, Department of Computer Sciences, Al-Imam Muhammad Ibn Saud Islamic University (IMSIU), AlAhsaa 31982, Kingdom of Saudi Arabia


2School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Pulau Pinang, Malaysia


Received: 30 August 2016/Accepted: 13 February 2017



Integrating an exit choice model into a microscopic crowd dynamics model is an essential approach for obtaining more efficient evacuation model. We describe various aspects of decision-making capability of an existing rule-based exit choice model for evacuation processes. In simulations, however, the simulated evacuees clogging at exits have behaved non-intelligently, namely they do not give up their exits for better ones for safer egress. We refine the model to endow the individuals with the ability to leave their exits due to dynamic changes by modifying the model of their excitement resulted from the source of panic. This facilitates the approximately equal crowd size at exits for being until the end of the evacuation process, and thereby the model accomplishes more optimal evacuation. For further intelligence, we introduce the prediction factor that enables higher probability of equally distributing evacuees at exits. A simulation to validate the contribution is performed, and the results are analyzed and compared with the original model.


Keywords: Decision making; evacuation; exit choice; prediction



Mengintegrasikan model pilihan keluar kepada model dinamik mikroskopik ramai adalah pendekatan penting untuk mendapatkan model pemindahan yang lebih cekap. Kami menerangkan pelbagai aspek keupayaan membuat keputusan bagi model pilihan keluar berasaskan peraturan sedia ada untuk proses pemindahan. Namun, dalam simulasi, mangsa yang dipindahkan tersangkut di pintu keluar telah bertindak tidak bijak, iaitu mereka tetap dengan jalan keluar mereka tanpa mendapatkan jalan keluar yang lebih selamat. Kami memperbaiki model untuk memberikan individu keupayaan untuk keluar disebabkan oleh perubahan dinamik dengan mengubah model keterujaan mereka yang dihasilkan daripada sumber panik. Ini memudahkan orang ramai di pintu keluar sehingga proses pemindahan berakhir dan dengan demikian model itu dapat melakukan pemindahan lebih optimum. Untuk kecerdasan lanjut, kami memperkenalkan faktor ramalan yang membolehkan kebarangkalian yang lebih tinggi untuk sama-sama mengagihkan mangsa di pintu keluar. Satu simulasi untuk pengesahan sumbangan dijalankan dan keputusan dianalisis dan dibandingkan dengan model asal.


Kata kunci: Membuat keputusan; pemindahan; pilihan keluar; ramalan


Bohannon, J. 2005. Directing the herd: Crowds and the science of evacuation. Science 310(5746): 219.

Burstedde, C., Klauck, K., Schadschneider, A. & Zittartz, J. 2001. Simulation of pedestrian dynamics using a two-dimensional cellular automaton. Physica A 295: 507-525.

Canter, D.V. 1985. Studies of human behavior in fire: Empirical results and their implications for education and design, Building Research Establishment Report, UK.

Ehtamo, H., Heli¨ovaara, S., Hostikka, S. & Korhonen, T. 2008. Modeling Evacuees’ exit selection with best response dynamics. Proc. 4th Intl. Con. on Pedestrian and Evacuation Dynamics. p. 27.

Elliott, D., & Smith, D. 1993. Football stadia disasters in the United Kingdom: learning from tragedy? Ind. Environ. Crisis Q 7(3): 205-229.

Guo, R.Y. & Huang, H.J. 2010. Logit-based exit choice model of evacuation in rooms with internal obstacles and multiple exits. Chin. Phys. B 19(3): 030501.

Huang, H.J. & Guo, R.Y. 2008. Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exits. Phys. Rev. E 78: Article ID. 021131.

Keating, J.P. 1982. The myth of panic. Fire J. 147: 57-61.

Helbing, D. & Molnár, P. 1995. Social force model for pedestrian dynamics. Physical Review E 51: 4282-4286.

Helbing, D., Farkas, I. & Vicsek, T. 2000. Simulating dynamical features of escape panic. Nature 407: 487-490.

Helbing, D., Farkas, I.J., Molnár, P. & Vicsek, T. 2002. Simulation of pedestrian crowds in normal and evacuation situations. In Pedestrian and Evacuation Dynamics, edited by Schreckenberg, M. & DeoSarma, S. Berlin: Springer- Verlag. pp. 21-58.

Hills, A. 1998. Seduced by recovery: The consequences of misunderstanding disaster. Journal of Contingencies and Crisis Management 6: 162-170.

Lakoba, T.I., Kaup, D.J. & Finkelstein, N.M. 2005. Modifications of the Helbing-Molnar-Farkas-Vicsek Social Force Model for pedestrian evolution. Simulation 81: 339-352.

Lo, S.M., Huang, H.C., Wang, P. & Yuen, K.K. 2006. A game theory based exit selection model for evacuation. Fire Safety J. 41: 364-396.

Luh, P., Wilkie, C. & Chang, S. 2012. Modeling and optimization of building emergency evacuation considering blocking effects on crowd movement. IEEE Trans. Autom. Sci. Eng 9(4): 687-700.

Mydans, S. 2009. At least 59 die in Bangkok club fire. New York: New York Times. Accessed on 1st January 2009.

Passini, R. 1984. Wayfinding in architecture. Canada: Van Nostrand Reinhold Co.

Proulx, G. 1993. A stress model for people facing a fire. J. Environmental Psychology 13: 137-147.

Shuaib, M.M. 2016. Modeling the capability of penetrating jammed crowd to eliminate freezing transition. Chin. Phy. B 25: 5.

Shuaib, M.M. 2014. Preserving socially expected crowd density in front of the exit for the reproduction of experimental data by modeling the pedestrians’ behind perception. J. Stat. Mech: 10037.

Sime, J.D. 1999. Crowd facilities, management and communications in disasters. Facilities 17: 313-324.

Wang, X.L., Guo, W., Cheng, Y. & Zheng, X.P. 2015a. Understanding the centripetal effect and evacuation efficiency of evacuation assistants: Using the extended dynamic communication field model. Safety Sci. 74: 150.

Wang, X.L., Guo, W. & Zheng, X. 2015b. Effects of evacuation assistant’s leading behavior on the evacuation efficiency: Information transmission approach. Chin. Phys. B 24(7): 070504.

Wang, J., Zhang, L., Shi, Q., Yang, P. & Huc, X. 2015c. Modeling and simulating for congestion pedestrian evacuation with panic. Physica A 428: 396-409.

Xiao, S., Liang, M., Yaofei, M., Chen, Y. & Hang, J. 2016. Selfishness- and selflessness-based models of pedestrian room evacuation. Physica A 447: 455-466.

Zainuddin, Z. & Shuaib, M.M.A. 2011. Modeling the independence factor and its effect on the preferred force of the social force model in emergency and non-emergency situations. Appl. Math. Inf. Sci. 5(1): 53-64.

Zainuddin, Z. & Shuaib, M. 2010. Modification of the decision making capability in the social force model for the evacuation process, Transport Theory and Statistical Physics 39: 1-24.

Zhang, L., Wang, J. & Shi, Q. 2014. Multi-agent based modeling and simulating for evacuation process in stadium. J. Syst. Sci. Complex 27(3): 430-444.


*Corresponding author; email: