Simulation of High Density Pedestrian Flow: A Microscopic Model


In recent years, modelling crowd and evacuation dynamics has become very important, with increasing huge numbers of people gathering around the world for many reasons and events. The fact that our global population grows dramatically every year and the current public transport systems are able to transport large amounts of people heightens the risk of crowd panic or crush. Pedestrian models are based on macroscopic or microscopic behaviour. In this paper, we are interested in developing models that can be used for evacuation control strategies. This model will be based on microscopic pedestrian simulation models, and its evolution and design requires a lot of information and data. The people stream will be simulated, based on mathematical models derived from empirical data about pedestrian flows. This model is developed from image data bases, so called empirical data, taken from a video camera or data obtained using human detectors. We consider the individuals as autonomous particles interacting through social and physical forces, which is an approach that has been used to simulate crowd behaviour. The target of this work is to describe a comprehensive approach to model a huge number of pedestrians and to simulate high density crowd behaviour in overcrowding places, e.g. sport, concert and pilgrimage places, and to assist engineering in the resolution of complicated problems through integrating a number of models from different research domains.

Share and Cite:

Dridi, M. (2015) Simulation of High Density Pedestrian Flow: A Microscopic Model. Open Journal of Modelling and Simulation, 3, 81-95. doi: 10.4236/ojmsi.2015.33009.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Helbing, D., Farkas, I.J., Molnar, P. and Vicsek, T. (2002) Simulation of Pedestrian Crowds in Normal and Evacuation Situations. In: Schreckenberg, M. and Sharma, S.D., Eds., Pedestrian and evacuation dynamics, Springer, Berlin, 21- 58.
[2] Fukui, M. and Ishibashi, Y. (1999) Self-Organized Phase Transitions in CA-Models for Pedestrians. Journal of the Physical Society of Japan, 8, 2861-2863.
[3] Muramatsu, M. and Nagatani, T. (2000) Jamming Transition in Two-Dimensional Pedestrian Traffic. Physica A: Statistical Mechanics and Its Applications, 275, 281-291.
[4] Yuhaski, S.J. and Smith, J.M. (1989) Modeling Circulation Systems in Buildings Using State Dependent Queueing Models. Queueing Systems, 4, 319-338.
[5] Treuille, A., Cooper, S. and Popovic, Z. (2006) Continuum Crowds. ACM Transactions on Graphics, 25, 1160-1168.
[6] Helbing, D. (2001) Traffic and Related Self-Driven Manyparticle Systems. Reviews of Modern Physics, 73, 1067-1141.
[7] Lohner, R. (2010) On the Modeling of Pedestrian Motion. Applied Mathematical Modelling, 34, 366-382.
[8] Pecol, P., Argoul, P., Dal Pont, S. and Erlicher, S. (2013) The Non-Smooth View for Contact Dynamics by Michel Fremond Extended to the Modeling of Crowd Movements. Discrete and Continuous Dynamical Systems—Series S (DCDS-S), AIMS, 6, 547-565.
[9] Campus Police (2013) General Evacuation Procedures. Technical Report, Oxford College of Emory University, Oxford.
[10] Saudi Arabia Government (2013) Makkah City Profile.
[11] Ministry of Hajj, Saudi Arabia (2013) Supreme Hajj Committee.
[12] Dridi, M.H. (2015) Tracking Individual Targets in High Density Crowd Scenes; Analysis of a Video Recording in Hajj2009. Current Urban Studies (CUS), 3, 35-53.
[13] Predtechenski, W.M. and Milinski, A.I. (1971) Personenstrome in Gebauden. Verlagsgesellschaft Rudolf Muller, Koln.
[14] Dridi, M.H. (2014) Pedestrian Flow Simulation Validation and Verification Techniques. arXiv:1410.0603 []

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.