A Study on Impatient Pedestrian Effect on Bi-directional Pedestrian Movement by Using Ant Algorithms

Abstract

This paper aims to revisit the bidirectional walking of pedestrians to contribute to a more realistic definition of the case of the presence of impatient pedestrians and to depict the effect of including impatient walkers in the pure bi-directional system of “normal” walking pedestrians. It is found that when a trace amount of impatient pedestrians are added to the system, it affects traffic in a disruptive way at low densities, however, it affects constructively at medium and high densities interestingly. When adding a comparable amount of impatient pedestrians to the system it is seen that at low and medium densities, the flux of motion and the order parameter together change in parallel, conversely, at high densities, the high number of impatient pedestrians positively affects the lane formation, therefore, pedestrian mobility remains high despite high density and disorder. As a result, more impatient pedestrians may not always mean more congested traffic. Sometimes, a certain density of impatient pedestrians can positively affect the bi-directional pedestrian traffic flow.

Keywords

• Cellular Automata (CA)
• Computer Simulation
• Bi-Directional Pedestrian Flow

References

1. [1] Molnar P. Helbing D. Social force model for pedestrian dynamics. Phys. Rev. E, 51:4282, 1995.
2. [2] Vicsek T. Helbing D., Farkas I. Simulating dynamical features of escape panic. Nature, 407, 2000.
3. [3] Moldovan H. Parisi D. R., Gilman M. A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions. Physica A, 388:3600, 2009.
4. [4] Chao G. Xiaoping Z., Wei L. Simulation of evacuation processes in a square with a partition wall using a cellular automaton model for pedestrian dynamics. Physica A, 389:2177, 2010.
5. [5] Löhner R. On the modeling of pedestrian motion. Applied Mathematical Modelling, 34:366, 2010.
6. [6] Schadschneider A. Chraibi M., Seyfried A. Generalized centrifugal-force model for pedestrian dynamics. Phys. Rev. E, 82:046111, 2010.
7. [7] Schadschneider A. Seyfried A. Chraibi M., Wagoum U.K. Force-based models of pedestrian dynamics. Networks and Heterogeneous Media, 692:425, 2011.
8. [8] Nishinari K. Schadschneider A., Kirchner A. From Ant Trails to Pedestrian Dynamics. Applied Bionics and Biomechanics, 1(11), 2003.

9. [9] Nishinari K. Schadschneider A. Chowdhury D., Guttal V. A cellular-automata model of flow in ant trails: non-monotonic variation of speed with density. J.Phys. A, 35:573, 2002.
10. [10] Schadschneider A. Nishinari K., Chowdhury D. Cluster formation and anomalous fundamental diagram in an ant-trail model. Phys. Rev. E, 67:036120, 2003.
11. [11] Chowdhury D. Nishinari K. John A., Schadschneider A. Collective effects in traffic on bi-directional ant trails. Journal of Theoretical Biology, 231:279, 2004.
12. [12] Rose G. Burd M. Shiwakoti N., Sarvi M. Enhancing the Safety of Pedestrians during Emergency Egress: Can We Learn from Biological Entities? Transportation Research Record, page 2137, 2002.
13. [13] Rose G. Burd M. Shiwakoti N., Sarvi M. Biologically Inspired Modeling Approach for Collective Pedestrian Dynamics under Emergency Conditions. Transportation Research Record, 2196:176, 2010.
14. [14] Francis L. W. R. Duncan E. J. Communication in ants. Current Biology, 16:570, 2006.
15. [15] Schadschneider A. Nowak S. Quantitative analysis of pedestrian counterflow in a cellular automaton model. Phys. Rev. E, 85:066128, 2012.
16. [16] Nishinari K. Suma Y., Yanagisawa D. Pedestrian dynamics: Modeling and experiment. Physica A, 391:248, 2012.
17. [17] Kayacan O. A theoretical model for uni-directional ant trails. Physica A, 390:1111, 2011.
18. [18] Kayacan O. Kunduracı T. A Monte Carlo study of ant traffic in a uni-directional trail. Physica A, 392:1946, 2013.
19. [19] Kayacan O. Kunduracı T. Uni-directional trail sharing by two species of ants a Monte Carlo study. J. Stat. Mech., page P06038, 2015.
20. [20] Kayacan O. Gökce S. A cellular automata model for ant trails. Pramana, 80:909, 2013.
21. [21] Kayacan O. Gökce S. Study on bi-directional pedestrian movement using ant algorithms. Chinese Phys. B, 25:010508, 2016.
22. [22] Sun Y. Kinetic Monte Carlo simulations of bi-direction pedestrian flow with different walk speeds. Physica A, 549:124295, 2020.
23. [23] Hao Q. Y. et al. Phase behaviors of counterflowing stream of pedestrians with site-exchange in local vision and environment. Physica A, page 125688, 2021.
24. [24] You L. et al. A study of pedestrian evacuation model of impatient queueing with cellular automata. Phys. Scr., 95:095211, 2020.
25. [25] Kretz T. Pedestrian Traffic, Simulation and Experiments, 2007. PhD. thesis.
26. [26] Löwen H. Rex M. Lane formation in oppositely charged colloids driven by an electric field: Chaining and two-dimensional crystallization. Phys. Rev. E, 75:051402, 2007.