An Analysis of a Modified Social Force Model in Crowd Emergency Evacuation Simulation

Hamizan Sharbini, Roselina Salleh, Habibollah Harun


In crowd evacuation simulation, a number of exit point and obstacles play an important role that can influence the result in the evacuation simulation. This paper focuses on the movement of the crowd’s emergency evacuation based on a modified social force model (SFM) via optimising the obstacles interaction parameter in one the SFM component. The simulation also compared original SFM (without obstacles) and modified SFM (with obstacles). The results show the impact can minimize the concept of arching phenomenon (faster-is-slower). For an obstacles issue, it is proven that obstacles can help to reduce evacuation time in regards to its proper position and exit width.


Crowd evacuation; Crowd simulation; Emergency evacuation; Faster-is-slower; Social force model.

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C. W. Reynolds, Flocks, herds, and schools: A distributed behavioral model, Proceedings of 14th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'87), Anaheim, CA, 1987, pp. 25-34.

L. Can, Z. Kejun, G. Haixiang and T. Jian, Simulation research on safe flow rate of bidirectional crowds using Bayesian-Nash equilibrium, Complexity, 1-15, 2019.

D. Helbing, I. J. Farkas, P. Molnar and T. Vicsek, Simulation of pedestrian crowds in normal and evacuation situations, Pedestrian and Evacuation Dynamics, 21(2), 21-58, 2002.

W. M. Predtetschenski and A. I. Milinski, Personenstr¨ome in Geb¨auden Berechnungsmethoden fur¨ die Projektierung. Rudolf Muller, ¨ K¨oln-Braunsfeld, 1971.

X. Song, L. Ma, Y. Ma, C. Yang and H. Ji, Selfishness and selflessness-based models of pedestrian room evacuation, Physica A: Statistical Mechanics and its Applications, 447, 455-466, 2016.

Y. Han, H. Liu and P. Moore, Extended route choice model based on available evacuation route set and its application in crowd evacuation simulation, Simulation Modelling Practice and Theory, 75, 1-6, 2017.

A. M. Ibrahim, I. Wenkat and P. D. Wilde, The impact of potential crowd behaviours on emergency evacuation: an evolutionary game-theoretic approach, Journal of Artificial Societies and Social Simulation, 22(1), 1-3, 2019.

G. Frank and C. Dorso, Room evacuation in the presence of an obstacle, Physica A: Statistical Mechcanics and its Applications, 390, 2135-2145, 2011.

N. Shiwakoti, M. Sarvi, G. Rose and M. Burd, Animal dynamics-based approach for modeling pedestrian crowd egress under panic conditions, Transporation Research Part B: Methodological, 45, 438-461, 2011.

D. Helbing, L Buzna, A. Johansson and T. Werner, Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions, Transportation Science, 39(1), 1-24, 2005.

X. Shi, Z. Ye, N. Shiwakoti and O. Grembek, A state-of-the art review on empirical data collection for external governed pedestrians complex movement, Journal of Advanced Transportation, 1-43, 2018.

J. Patrix, A. I. Mouaddib and S. Gatepaille, Detection of primitive collective behaviours in a crowd panic simulation based on multi-agent approach, International Journal of Swarm Intelligence Research (IJSIR), 3(3), 50-65, 2012.

M. C. Toyama, A. L. C. Bazzan, and R. da Silva, An agent-based simulation of pedestrian dynamics: from lane formation to auditorium evacuation, Proceedings of 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Honolulu, 2006, pp. 108-110;

T. Werner and D. Helbing, The social force pedestrian model applied to real life scenarios, Proceedings of 2nd International Conference on Pedestrians and Evacuation Dynamics, Greenwich, 2003, pp. 17–26.

B. Chopard, Cellular automata and lattice Boltzmann modeling of physical systems, in: Handbook of Natural Computing, G. Rozenberg, T. Bäck and J. N. Kok, Eds. Berlin: Springer, 2012, pp. 287-331.

D. Zhao, Y. Lizhong and J. Li, Exit dynamics of occupant evacuation in an emergency, Physica A: Statistical Mechanics and its Applications, 363(2), 501-511, 2006.

S. Liu, L. Yang, T. Fang and J. Li, Evacuation from a classroom considering the occupant density around exits, Physica A: Statistical Mechanics and its Applications, 388(9), 1921-1928, 2009.

A. Ferscha and K. Zia, Lifebelt: Silent directional guidance for crowd evacuation, International Symposium on Wearable Computers (ISWC’09), Linz, Austria, 2009, pp.19-26.

H. Dong, X. Gao, T. Gao, X. Sun and Q. Wang, Crowd evacuation optimization by leader-follower model, IFAC Proceedings Volumes, 47(3), 12116-12121, 2014.

D. Helbing and P. Molnar, Social force model for pedestrian dynamics, Physical Review E, 51(5), 4282-4286, 1995.

L. Jiang, J. Li, C. Shen, S. Yang and Z. Han, Obstacle optimization for panic flow–reducing the tangential momentum increases the escape speed, PloS One, 9(12), e115463, 2014.

I. Zuriguel, et. al., Clogging transition of many-particle systems flowing through bottlenecks, Scientific Reports, 4(1), 2014, doi:10.1038/srep07324.

D. Helbing, Social Self-Organization: Agent-Based Simulations and Experiments to Study Emergent Social Behavior, Berlin: Springer-Verlag, 2012.

N. Khamis, H. Selamat, R, Yusof and F. S. Ismail, Magnetic force model approach with path finding feature for an improved crowd movement simulation, Proceedings of 2017 Asian Simulation Conference (AsiaSim 2017), Melaka, 2017, pp. 157–168.

A. Garcimartín, I. Zuriguel, J. M. Pastor, C. Martín-Gómez and D. R. Parisi, Experimental evidence of the “faster is slower” effect, Transportation Research Procedia, 2, 760-767, 2014.

I. M. Sticco, F. E. Cornes, G. A. Frank and C. O. Dorso, Beyond the faster-is-slower effect, Physical Review E, 96(5), 052303, 2017.

H. Oh and J. Park, Main factor causing “faster-is-slower” phenomenon during evacuation: rodent experiment and simulation, Scientific Reports, 7(1), 13724, 2017.

J. M. Chen, P. Lin, F. Y. Wu, D. L. Gao and G. Y. Wang, Revisit the faster-is-slower effect for an exit at a corner, Journal of Statistical Mechanics: Theory and Experiment, 2018(2), 023404, 2018.

Y. C. Zhang, J. Ma, Y. L. Si, T. Ran, F. Y. Wu, G.Y. Wang and P. Lin, Required width of exit to avoid the faster-is-slower effect in highly competitive evacuation, Chinese Physics B, 26, 084504, 2017.

I. Hassan, Effective heuristics for ant colony optimization to handle large-scale problems, Swarm and Evolutionary Computation, 32, 2140-149, 2017.

M. Haghani and M. Sarvi, Simulating pedestrian flow through narrow exits, Physics Letters A, 383(2-3), 110-120, 2019.

B. D. Dubois and B. M. Wiley, Modeling of Crowd Behavior: The Creation of a Program to Predict the Movements of Individuals within a Crowd(rep), Worcester Polytechnic Institute, Retrieved from, 2008.

F. E. Cornes, G. A. Frank and C. O. Dorso, Panic contagion and the evacuation dynamics,,, 2018.

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

A. Trivedi and S. Rao, Agent-based modeling of emergency evacuations considering human panic behavior, IEEE Transactions on Computational Social Systems, 5(1), 277–288, 2018.

Y. Zhao, M. Li, X. Lu, L. Tian, Z. Yu, K. Huang, Y. Wang and T. Li, Optimal layout design of obstacles for panic evacuation using differential evolution, Physica A: Statistical Mechanics and its Applications, 465, 175–194, 2017.


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